Pharmaceutical Sciences, Faculty of
DSpace
UBCV
Van, Minh Tri
Master of Science - MSc
University of British Columbia
Introduction: Heart failure with reduced ejection fraction (HFrEF) is a debilitating condition that can be managed with pharmacotherapy, consisting of an angiotensin receptor- neprilysin inhibitor (ARNI), a beta-blocker (BB), a mineralocorticoid receptor antagonist (MRA), and a sodium-glucose cotransporter-2 inhibitor (SGLT2I). However, the optimal process of initiating and titrating these medications, known as sequencing strategy, is widely debated. Methods and Results: A scoping review was conducted to identify ambulatory sequencing strategies for treatment-naïve, de novo HFrEF patients, revealing a trend in the selection of attributes from the identified strategies, with a focus on expediting the initiation of quadruple therapy. Two attributes were found to heavily influence this trend: the number of medications initiated during the first visit and whether to prioritize initiation or titration. Based on these attributes, we developed a framework to classify sequencing strategies into 3 strategy types, and proposed 2 profiles to represent each type. A benefit-harm and cost-utility analysis was performed using an individual-based state-transition microsimulation model, where each profile was modeled in 2 versions with medication adjustment made fortnightly (a) or weekly (b). Probabilistic analysis of 10,000 trials and 1,000 samples with a willingness-to-pay threshold of $50,000/QALY were conducted, along with one-way sensitivity analysis, and 2 scenario analyses. The analysis demonstrated that the incremental cost-effectiveness among the different strategies is minimal, favoring more intensive strategies after considering benefits, harms and costs. In the base scenario, âsimultaneousâ sequencing strategy with fortnightly adjustment (Profile 6a) was most likely to be cost-effective. However, in the scenario where sub-target doses were assumed to be ineffective, strategies involved weekly adjustment were more likely to be optimal compared to fortnightly adjustment. In the scenario where medication adjustments were stopped after 3 months, âtraditionalâ sequencing strategy with fortnightly adjustment (Profile 1a) failed to achieve quadruple therapy, resulting in substantially fewer benefits. Conclusions: There was a noticeable trend towards prioritizing the speed of sequencing HFrEF quadruple therapy in the literature. However, this analysis revealed that the incremental cost-effectiveness among the different strategies was marginal. The key factor determining optimal outcomes was the successful establishment of patients on quadruple therapy within a reasonable timeframe.
AN ANALYSIS OF HEART FAILURE REDUCED EJECTION FRACTION PHARMACOTHERAPY SEQUENCING STRATEGIES by Minh Tri Van Pharm.D., The University of Cincinnati, 2019 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Pharmaceutical Sciences) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) August 2023 © Minh Tri Van, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: An analysis of heart failure reduced ejection fraction pharmacotherapy sequencing strategies submitted by Minh Tri Van in partial fulfilment of the requirements for the degree of Master of Science in Pharmaceutical Sciences Examining Committee: Ricky Turgeon, Assistant Professor, Faculty of Pharmaceutical Sciences, UBC Supervisor Peter Shane Loewen, Associate Professor, Faculty of Pharmaceutical Sciences, UBC Co-supervisor Mohsen Sadatsafavi, Associate Professor, Faculty of Pharmaceutical Sciences, UBC Supervisory Committee Member Kate Johnson, Assistant Professor, Faculty of Pharmaceutical Sciences, UBC Additional Examiner Additional Supervisory Committee Members: Nathaniel Hawkins, Clinical Assistant Professor, Cardiology Division, UBC Supervisory Committee Member Wei Zhang, Associate Professor, Faculty of Pharmaceutical Sciences, UBC Supervisory Committee Member iii Abstract Introduction: Heart failure with reduced ejection fraction (HFrEF) is a debilitating condition that can be managed with pharmacotherapy, consisting of an angiotensin receptor- neprilysin inhibitor (ARNI), a beta-blocker (BB), a mineralocorticoid receptor antagonist (MRA), and a sodium-glucose cotransporter-2 inhibitor (SGLT2I). However, the optimal process of initiating and titrating these medications, known as sequencing strategy, is widely debated. Methods and Results: A scoping review was conducted to identify ambulatory sequencing strategies for treatment-naïve, de novo HFrEF patients, revealing a trend in the selection of attributes from the identified strategies, with a focus on expediting the initiation of quadruple therapy. Two attributes were found to heavily influence this trend: the number of medications initiated during the first visit and whether to prioritize initiation or titration. Based on these attributes, we developed a framework to classify sequencing strategies into 3 strategy types, and proposed 2 profiles to represent each type. A benefit-harm and cost-utility analysis was performed using an individual-based state-transition microsimulation model, where each profile was modeled in 2 versions with medication adjustment made fortnightly (a) or weekly (b). Probabilistic analysis of 10,000 trials and 1,000 samples with a willingness-to-pay threshold of $50,000/QALY were conducted, along with one-way sensitivity analysis, and 2 scenario analyses. The analysis demonstrated that the incremental cost-effectiveness among the different strategies is minimal, favoring more intensive strategies after considering benefits, harms and costs. In the base scenario, âsimultaneousâ sequencing strategy with fortnightly adjustment (Profile 6a) was most likely to be cost-effective. However, in the scenario where sub-target doses were iv assumed to be ineffective, strategies involved weekly adjustment were more likely to be optimal compared to fortnightly adjustment. In the scenario where medication adjustments were stopped after 3 months, âtraditionalâ sequencing strategy with fortnightly adjustment (Profile 1a) failed to achieve quadruple therapy, resulting in substantially fewer benefits. Conclusions: There was a noticeable trend towards prioritizing the speed of sequencing HFrEF quadruple therapy in the literature. However, this analysis revealed that the incremental cost-effectiveness among the different strategies was marginal. The key factor determining optimal outcomes was the successful establishment of patients on quadruple therapy within a reasonable timeframe. v Lay Summary HFrEF can be managed with a combination of 4 medication classes. However, there is debate about the best way to start and adjust these medications. We reviewed how doctors start and adjust these medications in people who have a new diagnosis of HFrEF and are not already taking any medications. We found common trends in the ways to start and adjust the medications, and described a plan to group them into 3 main types. We gave 2 examples for each type, which we called profiles. We did a study to compare the costs, benefits, and harms of each profile. The study found that being on all 4 medications remains the key to getting the best outcomes, regardless of the profiles used. The profile likely to provide the most benefit was to start 4 medications on the first visit. vi Preface The work presented in this thesis was conducted by the Mastersâ student, Minh Tri (Tri) Van. Tri designed the proposal, research questions, and methodology. He also performed the analysis, interpreted the results, drafted and revised the thesis. vii Table of Contents Abstract ...............................................................................................................................................iii Lay Summary ...................................................................................................................................... v Preface ................................................................................................................................................. vi Table of Contents .............................................................................................................................. vii List of Tables ....................................................................................................................................xiii List of Figures ................................................................................................................................... xiv List of Abbreviations ........................................................................................................................ xv Glossary ............................................................................................................................................. xvi Acknowledgements .........................................................................................................................xvii Dedication ...................................................................................................................................... xviii Chapter 1: Introduction..................................................................................................................... 1 1.1 HF background and impact ................................................................................................. 1 1.2 Moving from triple to quadruple therapy for HFrEF ......................................................... 2 1.3 Strategies for achieving quadruple therapy in HFrEF ....................................................... 2 1.3.1 Sequencing strategies and their trade-offs...................................................................... 2 1.3.2 Limited evidence for different sequencing strategies .................................................... 4 1.4 Thesis objectives and organization ..................................................................................... 6 Chapter 2: Scoping review ................................................................................................................ 8 2.1 Introduction .......................................................................................................................... 8 2.2 Methods ................................................................................................................................ 9 2.2.1 Protocol and registration ................................................................................................. 9 viii 2.2.2 Eligibility criteria ............................................................................................................. 9 2.2.3 Information sources ....................................................................................................... 10 2.2.4 Search strategy ............................................................................................................... 11 2.2.5 Selection of sources of evidence ................................................................................... 11 2.2.6 Data charting process..................................................................................................... 12 2.2.7 Data items extracted ...................................................................................................... 12 2.2.8 Data synthesis................................................................................................................. 13 2.3 Results ................................................................................................................................. 14 2.3.1 Selection of sources of evidence ................................................................................... 14 2.3.2 Characteristics of sources of evidence.......................................................................... 17 2.3.3 Synthesis of results and results of individual sources of evidence ............................. 17 2.3.3.1 Attributes of proposed sequencing strategies ...................................................... 17 2.3.3.2 Rationales for proposed sequencing strategies .................................................... 21 2.3.3.3 Classifying sequencing strategies type and profiles ............................................ 29 2.4 Discussion ........................................................................................................................... 38 2.4.1 Summary of evidence .................................................................................................... 38 2.4.1.1 Number of medications initiated during the first visit ........................................ 40 2.4.1.2 Order of medication initiation and prioritization ................................................. 41 2.4.1.3 The timing of starting titration relative to completing initiation ........................ 43 2.4.1.4 Approaches to medication adjustment ................................................................. 44 2.4.1.5 Other factors impacting the intensity and speed of sequencing strategies ......... 46 2.4.2 Limitations ..................................................................................................................... 48 2.5 Conclusion .......................................................................................................................... 48 ix Chapter 3: Microsimulation model ................................................................................................ 50 3.1 Introduction ........................................................................................................................ 50 3.2 Methods .............................................................................................................................. 51 3.2.1 Model design .................................................................................................................. 51 3.2.2 Model structure .............................................................................................................. 52 3.2.3 Sequencing strategy profile representation and therapy adjustment algorithm ......... 53 3.2.4 Base case ........................................................................................................................ 58 3.2.5 Comparators ................................................................................................................... 62 3.2.6 Model inputs and assumptions ...................................................................................... 63 3.2.6.1 Transition probabilities ......................................................................................... 63 3.2.6.2 Costs ....................................................................................................................... 64 3.2.6.3 Utilities ................................................................................................................... 64 3.2.7 Analysis .......................................................................................................................... 64 3.2.7.1 Compare the benefit-harm outcomes ................................................................... 64 3.2.7.2 Compare the cost-utility outcomes ....................................................................... 65 3.2.7.3 Variability and uncertainty.................................................................................... 65 3.2.7.4 Model validation .................................................................................................... 66 3.3 Results ................................................................................................................................. 67 3.3.1 Benefit-harm comparison of proposed sequencing strategies..................................... 67 3.3.2 Cost-utility comparison of proposed sequencing strategies ........................................ 71 3.3.3 Sensitivity analyses ........................................................................................................ 76 3.3.3.1 Probabilistic sensitivity analysis (PSA) ............................................................... 76 3.3.3.2 One-way sensitivity analysis................................................................................. 82 x 3.3.3.3 Scenario analyses ................................................................................................... 87 3.3.3.4 Model validation .................................................................................................... 88 3.4 Discussion ........................................................................................................................... 89 3.4.1 Summary of evidence .................................................................................................... 89 3.4.1.1 Benefit-harm outcomes ......................................................................................... 89 3.4.1.2 Cost-utility outcomes ............................................................................................ 91 3.4.1.3 Sensitivity and scenario analyses ......................................................................... 91 3.4.2 Strengths ......................................................................................................................... 93 3.4.3 Limitations ..................................................................................................................... 94 3.5 Conclusion .......................................................................................................................... 95 Chapter 4: Conclusion ..................................................................................................................... 96 4.1 Summary of thesis findings ............................................................................................... 96 4.1.1 Identify sequencing strategies for the quadruple therapy ............................................ 96 4.1.2 Categorize sequencing strategies for the quadruple therapy ....................................... 96 4.1.3 Modeling study overview .............................................................................................. 98 4.1.4 Benefit-harm of sequencing strategies ......................................................................... 98 4.1.5 Cost-utility of sequencing strategies ............................................................................. 99 4.2 Contribution and implications ......................................................................................... 100 4.3 Strengths and limitations ................................................................................................. 101 4.3.1 Strengths of the scoping review .................................................................................. 101 4.3.2 Limitations of the scoping review .............................................................................. 101 4.3.3 Strengths of modeling study........................................................................................ 102 4.3.4 Limitations of modeling study .................................................................................... 103 xi 4.4 Future research directions ................................................................................................ 103 4.5 Conclusion ........................................................................................................................ 104 References ........................................................................................................................................ 107 Appendices ....................................................................................................................................... 120 Appendix A - Background ........................................................................................................... 120 A.1 Table A1: HFrEF Standard Therapies ........................................................................ 120 Appendix B - Scoping review ...................................................................................................... 121 B.1 Table B1: Search strategy............................................................................................ 121 B.2 Table B2: Data collection guide ................................................................................. 124 B.3 Table B3: Full-text articles considered for eligibility and reason for exclusion...... 127 B.4 Table B4: Characteristics of included studies - Identification .................................. 134 B.5 Table B5: Characteristics of Included Studies - Categorization ............................... 138 B.6 Table B6: Characteristics of Included Studies - Rationalization .............................. 143 Appendix C - Modeling study ..................................................................................................... 152 C.1 Table C1: Inputs for one-way sensitivity analysis ..................................................... 152 C.2 Table C2: Inputs for scenario analyses ....................................................................... 153 C.3 Table C3: Benefit-harm analysis â Base scenario ..................................................... 154 C.4 Table C4: Benefit-harm analysis â Scenario 1........................................................... 155 C.5 Table C5: Cost-effectiveness ranking â Scenario 1 ................................................... 156 C.6 Table C6: Probabilistic sensitivity analysis â Scenario 1.......................................... 157 C.7 Table C7: Benefit-harm analysisâ Scenario 2............................................................ 158 C.8 Table C8: Cost-effectiveness ranking â Scenario 2 ................................................... 159 C.9 Table C9: Probabilistic sensitivity analysis â Scenario 2.......................................... 160 xii C.10 Figure C1: Cost-effectiveness acceptability curve â Scenario 1 PSA ...................... 161 C.11 Figure C2: Cost-effectiveness acceptability curve â Scenario 2 PSA ...................... 162 xiii List of Tables Table 2.1 Characteristics of included articles ................................................................................... 17 Table 2.2 Summary of proposed sequencing strategy attributes ..................................................... 19 Table 2.3 The relative order of medication initiation across strategies........................................... 21 Table 2.4 Sequencing strategy types and representative profiles .................................................... 33 Table 3.1 Model input ........................................................................................................................ 58 Table 3.2 Cost-utility analysis â Base scenario ................................................................................ 73 Table 3.3 Cost-effectiveness ranking â Base scenario ..................................................................... 74 Table 3.4 Probabilistic sensitivity analysis â Base Scenario ........................................................... 77 xiv List of Figures Figure 2.1 PRISMA flow diagram for the scoping review .............................................................. 16 Figure 2.2 Visual representation of sequencing strategy profiles.................................................... 36 Figure 3.1 State transition diagram.................................................................................................... 52 Figure 3.2 Visual representation of sequencing strategy profiles.................................................... 54 Figure 3.3 Medication adjustment algorithm .................................................................................... 57 Figure 3.4 Benefit-harm analysis â QALYs ..................................................................................... 68 Figure 3.5 Benefit-harm analysis - Life years .................................................................................. 68 Figure 3.6 Benefit-harm analysis â HFH .......................................................................................... 69 Figure 3.7 Benefit-harm analysis â Bradycardia (1-year medication adjustment period) ............. 69 Figure 3.8 Benefit-harm analysis â Hypotension (1-year medication adjustment period) ............ 70 Figure 3.9 Benefit-harm analysis â Hyperkalemia (1-year medication adjustment period) .......... 70 Figure 3.10 Benefit-harm analysis â Renal Impairment (1-year medication adjustment period) . 71 Figure 3.11 Cost-effectiveness plane ................................................................................................ 75 Figure 3.12 Cost-effectiveness acceptability curve â Base scenario PSA ...................................... 78 Figure 3.13 Incremental cost-effectiveness scatterplot, Profile 6a v. Profile 1a ............................ 79 Figure 3.14 Incremental cost-effectiveness scatterplot, Profile 6a v. Profile 4a ............................ 80 Figure 3.15 Incremental cost-effectiveness scatterplot, Profile 6a v. Profile 6b ............................ 81 Figure 3.16 Tornado diagram â Net monetary benefit ..................................................................... 83 Figure 3.17 Tornado diagram â ICER, Profile 1a vs. Profile 6a ..................................................... 84 Figure 3.18 Tornado diagram â ICER, Profile 4a vs. Profile 6a ..................................................... 85 Figure 3.19 Tornado diagram â ICER, Profile 6a vs. Profile 6b ..................................................... 86 xv List of Abbreviations ACEI Angiotensin-converting-enzyme inhibitor ARB Angiotensin receptor blocker ARNI Angiotensin receptor-neprilysin inhibitor BB Beta-blocker CCS Canadian Cardiovascular Society CEAC Cost-effectiveness acceptability curve CHEERS Consolidated Health Economic Evaluation Reporting Standards EV Expected value GDMT Guideline-directed medical therapy HF Heart failure HFH Heart failure hospitalization HFrEF Heart failure with reduced ejection fraction ICE Incremental cost effectiveness ICER Incremental cost effectiveness ratio LVEF Left ventricular ejection fraction MRA Mineralocorticoid receptor antagonist NMB Net monetary benefit PRISMA-ScR Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews PSA Probabilistic sensitivity analysis QALY Quality adjusted life year RCT Randomized controlled trial SGLT2I Sodium-glucose cotransporter-2 inhibitor . xvi Glossary Attribute An element t defines the characteristics of a sequencing strategy Cycle The default counter of the cycle when simulation is run Profile A sequencing strategy represents a type and identified in the scoping review, with standardization aimed at addressing any gaps in information. Sequencing strategy The process and order of initiate, titrate, adjust medication Step A unique combination of medications (and doses) defining a sequencing strategy Type A broad category that can be utilized to classify various possible strategies Walk A more detailed break-down of sequencing step when converted it into weekly interval xvii Acknowledgements I would like to express my deep appreciation to my two supervisors, Dr. Ricky Turgeon and Dr. Peter Loewen, for providing me with the opportunity to learn, grow and be inspired to pursue a career in research. Dr. Ricky Turgeon has played an instrumental role in offering me various opportunities and providing excellent guidance, which has helped me become a more confident and skilled researcher. I am grateful for his dedication and expertise which have been an inspiration to me. In addition, I would like to thank Dr. Peter Loewen for his unwavering support, guidance, and encouragement throughout this project. I am also deeply grateful to Dr. Mohsen Sadatsafavi for his invaluable guidance throughout my research, without which I could not have completed this project. I extend my heartfelt appreciation to the following individuals for their invaluable contributions to this project: Blair McDonald, for his valuable assistance in screening articles during the scoping review. Dr. Nathaniel Hawkins, Dr. Ricky Turgeon and Dr. Peter Loewen, for sharing their profound clinical expertise; Dr. Mohsen Sadatsafavi and Dr. Wei Zhang, for their invaluable insights into health economics and modeling expertise; all committee members for providing constructive feedback on the model structure, data inputs, and assumptions. My heartfelt thanks also go to the Mohsen Lab for adopting me and providing a great environment to learn and support during my MSc Thesis. I appreciate the emotional support and encouragement that they provided throughout my academic journey. Lastly, I would like to thank my family and friends for their constant love, support, and encouragement throughout my academic journey. Their unwavering support and belief in me have been a constant source of motivation and inspiration. xviii Dedication This thesis is dedicated to my loving family, whose unwavering support and encouragement have been the driving force behind my academic journey. Their love, understanding, and sacrifices have provided me with the strength and motivation to overcome challenges and pursue excellence in my studies. I am deeply grateful for their belief in me and for always being there to celebrate my accomplishments. 1 Chapter 1: Introduction 1.1 HF background and impact Heart failure (HF) is a clinical syndrome characterized by structural and/or functional cardiac abnormalities that lead to reduced cardiac output and pulmonary or systemic congestion, both at rest and during stress.1 HF is characterized by typical symptoms (e.g., dyspnea, ankle swelling, fatigue) and signs (e.g., elevated jugular venous pressure, pulmonary crackles, peripheral edema).1 HF causes significant morbidity and mortality, and consumes considerable healthcare resources. 2â5 In 2019/2020, the prevalence of HF in Canadian adults aged 40 years and older was 3.26%, and approximately 512 per 100,000 adults in this age group received a new diagnosis of HF every year.2 HF is the third most common reason for hospitalization in Canada,3 and hospitalization is a major driver of HF costs with a median length of stay of around 7 days.3,4 Despite advancements in medical and device therapy over the past decade, there has not been any significant change in the national rates of HF admissions, 30-day readmissions, and length of stay between 2009/2010 and 2018/2019.4 According to a report by the Heart and Stroke Foundation in 2016, the estimated annual direct healthcare cost for HF in Canada amounted to CA$2.8 billion.5 HF can be divided into 2 categories based on its temporal course: chronic HF and acute HF. Furthermore, HF can be classified based on ejection fraction (EF) which dictates different strategies for surveillance, treatment, and prognosis. HF with left ventricular EF (LVEF) â¥ 50%, 41%-49%, â¤ 40% are categorized as HF with preserved EF, HF with mildly-reduced EF, and HF with reduced ejection fraction (HFrEF) respectively.1 This project focuses on HFrEF and its standard pharmacotherapy management for newly diagnosed patients. 2 1.2 Moving from triple to quadruple therapy for HFrEF Pharmacotherapy has been shown to improve survival, reduce risk of hospitalization, and improve HF symptoms,6â10 and is therefore central to HFrEF patient care. Previously, the cornerstone of guideline-directed medical therapy (GDMT) for HFrEF was the use of triple therapy, consisting of: a angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB), a mineralocorticoid receptor antagonist (MRA), and a beta blocker (BB).6,11 In recent years, substituting an angiotensin receptor-neprilysin inhibitor (ARNI) for an ACEI/ARB and the addition of a sodium-glucose cotransporter-2 inhibitors (SGLT2I) were shown to further reduce hospitalization and mortality when compared to triple therapy.12,13 Introduction of these 2 classes re-defined the initial treatment paradigm of HFrEF. Currently, all major international guidelines recommend the quadruple therapy â a combination of an ARNI, a BB, a MRA, and a SGLT2I â as the standard HFrEF pharmacotherapy.7â10 Additional information about these standard therapies for HFrEF is provided in Table A1 (Appendix A). 1.3 Strategies for achieving quadruple therapy in HFrEF 1.3.1 Sequencing strategies and their trade-offs Although the ultimate goal is to achieve quadruple therapy for all patients with HFrEF, there is currently no consensus on the optimal approach to achieve this. For this project, we refer to these different approaches or processes of initiating, titrating, and adjusting the medications constituting the quadruple therapy as the âsequencing strategyâ. The traditional sequencing strategy involves initiating 1 medication and titrating it to the target dose (or maximum-tolerated dose) employed in landmark randomized controlled trials (RCTs) before starting the next medication. This approach mimics the order in which medications were tested in RCTs and is often implied in older guidelines.6,11,14,15 Older medications (e.g., 3 ACEI/ARB, BB) are started first, and newer medications are often only added or switched to (e.g., ARNI) if EF remains below 40% and patients remain symptomatic on existing medications.6,11,15 Assuming a change in medications is made every 2 weeks, as is typical, this approach will take a minimum of 3 to 6 months to complete.14,16 Aside from mimicking RCTs, other stated rationales for this approach include the assumption of greater benefits for target doses compared to sub-target doses for some of these medications, the perception that patients might better tolerate slow titration, the simplicity of focusing on 1 medication at a time, and also the belief that the need for additional medications might be obviated if patients become asymptomatic or normalize their LVEF on the current medications.17â19 However, this traditional approach to sequencing strategy is being increasingly challenged. In practice, large registries have shown that patients and clinicians often fail to reach dual, triple, or quadruple therapy, hindered by many reasons, one of which can be the long titration period.20,21 Additionally, the majority of adjustments (i.e., initiation and/or titration) are made early after diagnosis or hospitalization, followed by therapeutic inertia.20,21 The most common reason given by clinicians for choosing not to titrate or initiate additional HFrEF medications is that the patient is âclinically stableâ.22 This deprives patients of the additional morbidity and mortality reduction benefits shown in RCTs, which are conferred by additional medication exposure, as the prognostic benefits of therapy are not solely based on baseline symptoms alone.23 In summary, it has been argued that the traditional sequencing strategy poses a problem: the longer it takes for patients to be established on quadruple therapy, the higher the likelihood of treatment failures and risks of adverse clinical outcomes. Alternative sequencing strategies, which refer to any strategy different from the traditional sequencing strategy, seek to address some of these perceived problems by reducing the time it 4 takes for patients to be established on quadruple therapy. Proponents of alternative sequencing strategies argue that these new approaches can offer morbidity and mortality benefits by achieving quadruple therapy as soon as possible.24â33 The rationales for alternative sequencing strategies are often provided as follows: (1) each medication exerts its beneficial effects quickly (within the first few weeks) and (2) independently of other medications;24â26,28â38 (3) these medications are well-tolerated and tolerability may even be improved by taking them together; 24,25,28â32,34,36,38 and (4) lower doses for most of these medications confer the majority of the benefit of the target doses.24â26,28â34,36â38 Despite the potential advantages, various other factors that might limit or reduce the benefits of using these approaches are often not sufficiently discussed. One concern is that condensing the titration process might increase the rate of adverse events and discontinuation compared to what was observed in RCTs,39 and could potentially affect patients' adherence and satisfaction. Furthermore, these alternative strategies may be more complex to implement, especially for patients who can only access healthcare providers sporadically. Such patients may require more monitoring and support. To overcome this challenge, involving additional care providers such as pharmacists and nurse practitioners, as part of a HF clinic, can help coordinate medication adjustments.40,41 However, it is important to note that these additional services will come at an additional cost to the healthcare system. 1.3.2 Limited evidence for different sequencing strategies Currently, the available evidence in this area is predominantly derived from some observational studies. For instance, a study conducted by Ouwerkerk et al. in 2020 provided direct evidence supporting the notion that combining more than 50% of the recommended doses of ACEI/ARB and BB resulted in better outcomes compared to monotherapy at target doses. This study underscored the potential impact of initiating new medications rather than solely focusing on 5 titration.20 Savarese et al. conducted an observational cohort study using secondary data from electronic health records and claims data sources in the United States, United Kingdom, Sweden, and Japan, which showed that, despite the high risk of HF hospitalization (HFH) and death, under-dosing and slow titration of the quadruple therapy were common in patients hospitalized for HF who were new to these medications, and that initiation of novel medications (e.g, SGLT2I, ARNI) was delayed compared to other HF medications.42,43 As of the time of writing, the results of the Safety, Tolerability, and Efficacy of Up-titration of Guideline-directed Medical Therapy for Acute Heart Failure (STRONG-HF) trial have become available.39 This landmark clinical trial compared an intensive treatment strategy involving more rapid titration compared to the standard of care. The intensive care group required acute HF patients to initiate ACEI/ARB, ARNI, BB, and MRA during hospitalization and rapidly titrate these medications to optimal doses within 2 weeks of discharge, following a predefined algorithm.39 The results of this study showed that rapid titration could reduce symptoms, improve quality of life, and reduce the risk of 180-day all-cause death or HF readmission compared to the standard of care.39 However, the intensive care group was also associated with an increased incidence of adverse events, including blood pressure decreases, hyperkalemia, and renal impairment.39 Observational studies in this area are subject to common limitations, including a lack of control over confounding factors, and potential selection bias. Furthermore, most of these studies focused on specific aspects of sequencing strategies rather than directly comparing different strategies. The STRONG-HF trial is currently the only RCT conducted in this area. However, there are limitations in applying its results to our specific population of interest, namely patients newly diagnosed (de novo) with HFrEF in outpatient setting. Firstly, the trial primarily focused 6 on patients with acute HF, and the initiation and some of the adjustment processes occur during the inpatient setting prior to hospital discharge. This may limit the generalizability of the findings to other populations or settings where the initiation and titration occur in ambulatory settings. This is importance given that inpatient individuals could undergo more rigorous monitoring and that nearly 50% of incident HF may be diagnosed as an outpatient.44,45 Additionally, there is a lack of detailed information regarding the specific methods of medication titration, apart from the specified time frame. Lastly, it is worth noting that SGLT2I was only implemented late in the study and were not prescribed to the majority of patients. Considering these factors, there remains a need for additional evidence that compares the potential risks and benefits of different sequencing strategies in the ambulatory setting. 1.4 Thesis objectives and organization Currently, there is still insufficient research on the trade-offs of different sequencing strategies, including both traditional and alternative sequencing strategies, on factors such as tolerability, effectiveness, safety, and economic outcomes. Therefore, it remains unclear whether there are significant differences between approaches, and if so, which factors play the greatest role in determining those differences. Further investigation is necessary to provide clarity on these issues. The goal of this project is to compare the sequencing strategies for the HFrEF quadruple therapy, with the following objectives: 1. Identify and categorize sequencing strategies for the HFrEF quadruple therapy. 2. Compare the benefit-harm of sequencing strategies for the HFrEF quadruple therapy. 3. Compare the cost-utility of sequencing strategies for the HFrEF quadruple therapy. 7 In this chapter 1, I have presented an overview of the pathophysiology, classification, morbidity, mortality, and economic costs associated with HF. Additionally, I have provided a comprehensive discussion of the context surrounding the use of quadruple therapy in HFrEF, including considerations and the existing gaps in the literature regarding evidence supporting different sequencing strategies for the quadruple therapy. In chapter 2, I present a scoping review that identifies and examines alternative sequencing strategies for the quadruple therapy. This review involves extracting relevant information and proposing a framework for categorizing the HFrEF sequencing strategies into different strategy types, along with proposing a number of representative sequencing strategy profiles, based on dominant attribute trends (Objective 1). In chapter 3, I present the result of an analysis using a microsimulation model that compared previously proposed sequencing strategy profiles for the quadruple therapy. The analysis incorporates key clinical, safety, and economic factors, and provides insights into the benefit-harm and cost-utility outcomes of these strategies (Objective 2&3). In chapter 4, I summarize the findings from my thesis in terms of their implications for implementing the sequencing strategies, provide recommendations for future research and for design of initiatives in the field of HF. 8 Chapter 2: Scoping review 2.1 Introduction As outlined in Chapter 1, there are various theoretical permutations to implementing a standardized approach to sequence HFrEF quadruple therapy by varying either the order of medication prioritization, the timing and characteristics of initiation and titration, or both. Although the traditional sequencing strategy has been established, entailing the sequential initiation and titration of medications in the order they were tested in landmark trials, various authors have proposed alternative approaches to sequencing quadruple therapy. However, to date, there has been no effort to identify these alternative sequencing strategies and synthesize them into a cohesive framework. Our initial search reveals that the primary sources of information on this topic consist of commentaries and non-research articles. Given this context, scoping reviews offer a more flexible approach compared to traditional systematic reviews. The inherent advantage of a scoping review lies in its capacity for a broader scope, which allows us to ascertain not only the sequences that are currently being employed (which can be slower to catch up with newer recommendations) or evidence-based, but also those that are recommended, proposed, or discussed most recently. This is accomplished by applying more inclusive criteria, which encompass articles often excluded in systematic reviews, without necessarily evaluating the quality of the articles.46 The objectives of this scoping review were to identify the alternative sequencing strategies, categorize sequencing strategies into different strategy types based on dominant attribute trends, and provide sequencing strategy profiles as examples for each type. 9 2.2 Methods 2.2.1 Protocol and registration The scoping review was conducted in accordance with the Joanna Briggs Institute methodology for scoping reviews and was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews (PRISMA-ScR).47,48 The method described below followed a protocol developed a priori (not registered in PROSPERO, which does not accept scoping review protocols) with amendments made during data collection and extraction process. The final protocol is available upon request. 2.2.2 Eligibility criteria Based on the study objectives, we devised the inclusion criteria according to the framework of âpopulation â concept â contextâ. Full-text articles were considered for inclusion if the sequencing strategies being described in the articles met all of the following criteria: â¢ Population: All patients newly diagnosed (de novo) with HFrEF and not currently receiving or having any contraindications to the standard HFrEF quadruple therapy. â¢ Concept: Articles of any type that describe a non-traditional/alternative sequencing strategy that utilizes medication classes forming the standard HFrEF quadruple therapy (ACEI/ARB/ARNI, BB, MRA, and SGLT2I). The sequencing strategy should be applicable for the general population of de novo HFrEF and are independent of specific patient signs, symptoms, investigations (beyond echocardiographic confirmation of HFrEF), and lab values. o The sequencing strategies are sufficiently described so that all of the following attributes related to the order of medication prioritization can be extracted: The number and identity of medications initiated in the first visit, the order of 10 medication initiation. For the purpose of this review, a visit was defined as any physical or virtual contact between a patient and a healthcare practitioner in which medication adjustments were performed.49 This category of attributes provides valuable insights into the diverse approaches adopted by different strategies when determining which medications to initiate and the order in which they are administered. o Additionally, at least 1 of the following attributes related to the timing and characteristics of initiation and titration could be extracted: Timing of starting titration relative to completing initiation (i.e., whether to prioritize initiation or titration), the characteristics of medication adjustments (i.e., whether multiple medications are adjusted simultaneously in the same visit or sequentially one at a time), the frequency of medication adjustments (e.g., initiate, titrate), the minimum expected time to complete all medication initiations and titrations. This category of attributes provided insights into the different considerations and relationships between initiation and titration within the sequencing strategies. â¢ Context: The sequencing strategy is intended to be carried out primarily in the ambulatory settings. Sequencing strategies that explicitly requires any medications to be initiated in-hospital are excluded. 2.2.3 Information sources We searched MEDLINE and Embase via Ovid. Following the database search, a search of grey literature was done via Google/ Google Scholar, and 2 federated search engines, ACCESSSS.org and the Trip Database. Bibliographies of identified articles from databases were also checked for relevant references through the use of a Web of Science âcited referencesâ search. 11 2.2.4 Search strategy A research librarian was consulted to develop the initial search strategy for each information source using the aforementioned âpopulation â concept â contextâ framework. The search period was limited from January 2019 as this was the first year of publication of trials of SGLT2I (the most recent class of medications studied for HFrEF) in HFrEF became available.50 The content of articles passing the title and abstract screening stage available in other languages was translated to English using Google Translate. The search strategies and search dates for all information sources are provided in Table B1 (Appendix B). 2.2.5 Selection of sources of evidence For database sources, Covidence (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org.) was used to combine citations and remove any duplications from different sources.51 Titles and abstracts of the retrieved articles were screened in duplicate by 2 reviewers (Minh-Tri Van and Blair MacDonald). Articles that passed this stage were retrieved for full-text review and further assessed against the selection criteria. Reasons for exclusion were documented and reported. Any disagreements between the reviewers at each stage of the selection process were resolved through discussion, and unresolved conflicts were arbitrated by a third reviewer (Ricky Turgeon). For non-database and other sources, such as grey literature, one reviewer (Minh-Tri Van) manually screened, reviewed, and determined the inclusion of each article. Finally, multiple articles from both the database and non-database sources, describing the same sequencing strategy in regard to the main attributes, as determined by the review team, were combined for data extraction and analysis purposes.52 12 2.2.6 Data charting process The data extracting and charting process was performed by 1 reviewer (Minh-Tri Van) following the data collection guide provided in Table B2 (Appendix B). The guide was continually optimized throughout the data charting process. Whenever there was insufficient information to identify elements of an attribute and complete a data field, it was marked as "not reported". Articles describing similar strategies were grouped together, and the relevant data was extracted and organized accordingly. In cases where an article described multiple sequencing strategies that met the eligibility criteria, detailed attributes for each strategy were extracted separately. If a strategy provided the option to choose between ACEI, ARB, and ARNI, the ARNI option was selected as the representative of renin-angiotensin-aldosterone system inhibitors (RAASi), unless there was explicit mention of choosing ACEI/ARB; this principle also extended to strategies in which ACEI/ARB was immediately replaced by ARNI, without any other steps in-between. The data collection form was structured into 3 sections corresponding to the information of interest for extraction: (1) 'Identification', (2) 'Categorization', and (3) 'Rationalization'. 2.2.7 Data items extracted In the 'Identification' section, we extracted essential reference details of the article(s), including the first author's name, publication year, and primary article type. Additionally, the strategy name, as used by the original authors (if any), and description were also extracted. The strategy description was delineated based on the information extracted from the articles, outlining a series of individual steps that specified the initiation or titration of each medication class within the quadruple therapy. In the âCategorizationâ section, we further expanded the strategy description by extracting the details of sequencing strategies based on 8 attributes: (1) the number and (2) identity of 13 medications initiated during the first visit, (3) the order of medications initiation, (4) the timing of starting titration (relative to completing initiation) (5) the characteristics of medication adjustment, (6) the average frequency of medication adjustments, (7) the minimum expected time to complete all medication initiations, and (8) titrations. These 8 sequencing attributes were selected for extraction and used in the eligibility criteria after pilot searches due to their ability to capture all the elements and differentiate the proposed strategies. As noted in eligibility criteria, the first 3 attributes are related to the order of medication prioritization, while the latter 5 attributes are related to the timing and characteristics of initiation and titration. Additional details and examples of these attributes are elaborated further in Table B2 (Appendix B). In the âRationalizationâ section, we gathered rationales and supporting evidence, in form of direct quotes from the articles, for 2 primary categories of attributes: the order of medication prioritization and the timing and characteristics of initiation and titration. 2.2.8 Data synthesis The extracted data were summarized using descriptive statistics. For articles, we presented the number and percentage of articles for each characteristic from the 'Identification' section. For sequencing strategies, we reported the number and percentage of strategies associated with each attribute, as well as the range and median where applicable, from the âCategorizationâ section. The extracted rationales from the 'Rationalization' section were classified into the same 2 categories as described in the inclusion criteria and 'Categorization' section. These categories included rationales that explained and justified the choice of attributes related to the order of medication prioritization, as well as rationales that explained and justified the choice of attributes related to the timing and characteristics of initiation and titration. A narrative approach was employed to provide a concise summary of these rationales. 14 Following the data summarization process, a framework was proposed to categorize the sequencing strategies into different strategy types based on the dominant attributes of the order of medication prioritization and the timing and characteristics of initiation and titration. This was done with the aim of capturing all possible sequencing strategies while emphasizing their distinctiveness, particularly for strategies belonging to different strategy types. For each strategy type, 2 representative profiles were developed. These profiles were derived from the strategies identified in the scoping review, and standardizations were applied based on the common trends observed among the identified strategies in terms of their attributes. One example of this standardization was in the case of profiles extracted from sequencing strategies that did not provide details of the titration process. As a recurrent trend in terms of sequencing characteristics discussed in later section was that 2 or more medications were adjusted during the same visit with the goal of maximizing the speed to achieve the quadruple therapy, we applied this trend to these representative profiles. This approach enabled the representation of missing attributes that were not explicitly discussed by the authors, facilitating further comparisons between the strategies. 2.3 Results 2.3.1 Selection of sources of evidence After conducting a databases search, a total of 3,960 articles were identified. Duplicate removal using Covidence resulted in 3,439 articles that were independently screened. Out of these, 25 articles were selected for full-text review based on the eligibility criteria, resulting in 15 articles that described 17 unique sequencing strategies. In parallel, 527 results were obtained from other non-database sources, excluding 13 articles that were also identified through databases, as well as 498 irrelevant articles. This resulted in 16 articles being retrieved for full-text review, out of 15 which 2 articles describing 2 potential sequencing strategies were retained. Finally, the articles from both sources were combined, resulting in 8 articles that described 18 unique sequencing strategies. To elaborate further, 5 identified articles from the database source, all describing the "rapid" strategy, were merged into a single article. Similarly, 2 articles from the database and 1 from the non-database source, all detailing the "cluster" strategy, were combined into 1 article. Finally, 4 articles from the database source, each discussing the "simultaneous" strategy, were combined into a single article that described this strategy. Consequently, we now had 3 articles, each representing a distinct strategy. The list of articles retrieved for full text review, the reason for exclusion (if article was excluded), and the combination into the same article (if article was included) is provided in Table B3 (Appendix B). 16 Identification of articles via databases Identification of articles via other methods Identification Screening Included Articles* identified from: Medline (n = 1021) Embase (n = 2939) Articles removed before screening: Articles removed for duplication by software (n = 521) Articles screened. (n = 3439) Articles excluded. (n = 3414) Articles sought for retrieval. (n = 25) Articles not retrieved. (n = 0) Full-text articles assessed for eligibility. (n = 25) Articles excluded: Did not provide detailed sequencing strategy (n = 6) Did not include all quadruple therapy (n = 3) Require inpatient initiation of 1 or multiple medication classes (n = 1) Articles* identified from: Federated searches (n = 273) Google/Google scholars (n = 120) Web of science forward Citation searching (n = 134) Full-text articles assessed for eligibility. (n = 16) Articles excluded: Did not provide detailed sequencing strategy (n = 12) Did not include all quadruple therapy (n = 1) Require inpatient initiation of 1 or multiple medication classes (n = 1) 15 articles describe 17 unique sequencing strategies. Articles sought for retrieval. (n = 16) Articles not retrieved. (n = 0) Articles removed for duplication with articles from databases (n = 13) Articles excluded (n = 498) 2 articles describe 2 unique sequencing strategies. 8 Articles described 18 unique sequencing strategies. Combine 2 strategies into 1 strategy. Combine 12 articles into 3 articles. Figure 2.1 PRISMA flow diagram for the scoping review 17 2.3.2 Characteristics of sources of evidence The characteristics of included articles are summarized in Table 2.1. With the exception of a modeling study done by Shen et al.,53 all other articles were viewpoints/commentaries. 63% of the articles were published in 2021. Most articles described 1 sequencing strategy, however, exceptions existed where a single article described multiple sequencing strategies (13%), or multiple articles described the same strategy and were combined into 1 article (38%). From Shen et al., we extracted 11 different sequences, after excluding the traditional strategy.53 The full list of the included articles could be found in Table B4 (Appendix B). Table 2.1 Characteristics of included articles Characteristics Number of 8 articles (%) Article type â¢ Primary research â¢ Viewpoint/commentaries 1 (12) 7 (88) Year of first publication â¢ 2020 â¢ 2021 â¢ 2022 1 (12) 5 (63) 2 (26) Number of eligible strategies described in 1 article. â¢ 1 â¢ >2 7 (87) 1 (13) Number of individual articles described the same strategy. â¢ 1 â¢ 3 â¢ 4 5 (63) 1 (12) 2 (26) 2.3.3 Synthesis of results and results of individual sources of evidence 2.3.3.1 Attributes of proposed sequencing strategies We reported the overview of proposed sequencing strategiesâ attributes in Table 2.2. Due to the large number of sequencing strategies extracted from the modeling study by Shen et al.,53 which 18 may impact the interpretation of the results, we presented the results of this study separately from other sources. It was common for multiple medication classes to be initiated during the first patient visit. A median of 2 medications were initiated in these strategies. The most common combinations of medications initiated during the initial visit were ARNI and BB (17%), and SGLT2I alone (17%). When considering the exact order of medication initiation, there was little overlap between unique sequencing strategies, with the exception of where ARNI, BB, and SGLT2I are initiated together in the first visit (ARNI=BB=SGLT2I>MRA), which occurred in 2 strategies. In terms of the timing of starting titration (relative to completing initiation), most strategies involved starting medications titration after all medicationsâ initiation was completed, with the exception of sequencing strategies by Shen et al. in which each medication was titrated to the target dose before initiating the next medication in the sequence. The majority of strategies (56%) involved simultaneous medications titration of more than 2 medications during the same visit. 14 strategies (77%) involved adjusting medications every 2 weeks or more quickly, but slower frequencies of every 2-4 weeks were also reported in 3 strategies (17%) (3 or 43% excluding Shen et al.). Based on the observed frequencies, the minimum time required to initiate all medications ranged from 0 weeks (for strategies that simultaneously started all 4 medications) to 11 weeks, with a median of 6 weeks (2 weeks when excluding Shen et al.). Furthermore, the minimum expected time to complete the titration/adjustment of all medications ranged from 8 to 14 weeks, with a median of 12 weeks (regardless of whether Shen et al. is included or excluded). The full detailed attributes for each of the included sequencing strategies can be found in Table B5 (Appendix B). 19 Table 2.2 Summary of proposed sequencing strategy attributes Attributes All strategies (n=18) Strategies from Shen et al. (n=11) Others (n=7) Number of medications initiated during the first visit, n (%) 1 5 (28) 5 (45) 2 10 (56) 6 (55) 4 (57) 3 2 (11) 2 (29) 4 1 (6) 1 (14) Identity of medications initiated during the first visit, n (%) ARNI 1 (6) 1 (9) BB MRA 1 (6) 1 (9) SGLT2I 3 (17) 3 (27) ARNI & BB 3 (17) 1 (9) 2 (29) ARNI & SGLT2I 1 (6) 1 (14) ARNI & MRA 1 (6) 1 (9) BB & SGLT2I 2 (11) 1 (9) 1 (14) BB & MRA 1 (6) 1 (9) SGLT2I & MRA 2 (11) 2 (18) ARNI, BB & SGLT2I 1 (6) 1 (14) ARNI, BB & MRA 1 (6) 1 (14) ARNI, SGLT2I & MRA BB, SGLT2I & MRA ARNI, BB, SGLT2I & MRA 1 (6) 1 (14) Order of initiation*, n (%) ARNI>BB>MRA>SGLT2I 1 (6) 1 (9) ARNI=BB>SGLT2I>MRA 1 (6) 1 (9) ARNI=BB>SGLT2I=MRA 1 (6) 1 (9) ARNI=BB>MRA>SGLT2I 1 (6) 1 (9) ARNI=MRA>SGLT2I>BB 1 (6) 1 (9) ARNI=BB=SGLT2I>MRA 2 (11) 2 (18) ARNI=BB=SGLT2I=MRA 1 (6) 1 (9) BB=SGLT2I>MRA>ARNI 1 (6) 1 (9) BB=SGLT2I>ARNI>MRA 1 (6) 1 (9) BB=MRA>SGLT2I>ARNI 1 (6) 1 (9) MRA>SGLT2I>BB>ARNI 1 (6) 1 (9) SGLT2I>MRA>ARNI>BB 1 (6) 1 (9) SGLT2I>MRA>BB>ARNI 1 (6) 1 (9) SGLT2I>BB>MRA>ARNI 1 (6) 1 (9) SGLT2I=ARNI>BB=MRA 1 (6) 1 (9) SGLT2I=MRA>BB>ARNI 1 (6) 1 (9) SGLT2I=MRA>ARNI>BB 1 (6) 1 (9) 20 Attributes All strategies (n=18) Strategies from Shen et al. (n=11) Others (n=7) Timing of starting titration (relative to completing initiation), n (%) Before initiating all 4 medications 11 (61) 11 (100) After initiating all 4 medications 7 (39) 7 (100) Not reported 0 0 Characteristics of medication adjustments, n (%) Sequential 6 (33) 5 (45) 1 (14) Simultaneous 10 (56) 6 (55) 4 (57) Not reported 2 (11) 2 (28) Average frequency of medication adjustment visits, n (%) Every â¤2 weeks 14 (77) 11 (100) 3 (43) Every >2 weeks 3 (17) 3 (43) Not reported 1 (6) 1 (14) Minimum time to complete all medication initiations, weeks Min 0 6 0 Max 11 11 8 Minimum time to complete all medication titrations, weeks Min 8 8 8 Max 14 12 14 * X>Y: Initiate X before Y, X=Y: Initiate X at the same time at Y Regarding the order of medication introduction, we implemented an additional step to facilitate a more effective comparison of the relative prioritization of each medication class across various sequencing strategies. This step pertains to the third attribute related to the order of medication introduction. Apart from extracting the precise sequence of medication introductions for each strategy, we categorized each medication into one of four ordered positions based on the visit when it was introduced. In cases where multiple medications were initiated during the same visit, they were grouped within the same position, and subsequent positions were adjusted accordingly. For instance, if a sequencing strategy encompassed the initial introduction of ARNI, BB, and 21 SGLT2I, followed by the subsequent introduction of MRA, we classified ARNI, BB, and SGLT2I as the first-position medications, and MRA as the fourth-position medication. By aggregating the positions of each medication class across all strategies, we determined the medication classes that were more likely to be prioritized among the various sequencing strategies. The outcome of this approach is presented in Table 2.3. It is evident that SGLT2I emerged as the most frequently prioritized medication, being initiated first in 11 out of 18 strategies. In close succession, both BB and ARNI were initiated first in 9 out of 18 strategies. Lastly, MRA was initiated first in 5 out of 18 strategies. Excluding the 11 strategies from Shen et al., among the remaining strategies, ARNI and BB equally shared the title of the most commonly initiated first medication class in 6 strategies. SGLT2I closely followed in 5 strategies, while MRA was the first medication initiated in 1 strategy. Table 2.3 The relative order of medication initiation across strategies Order of initiation All strategies (n=18) Excluding Shen et al. (n=7) ARNI BB MRA SGLT2I ARNI BB MRA SGLT2I 1st 9 9 5 11 6 6 1 5 2nd 0 2 3 1 0 0 0 0 3rd 3 4 6 4 1 1 3 1 4th 6 3 4 2 0 0 3 1 2.3.3.2 Rationales for proposed sequencing strategies The 11 strategies derived from Shen et al. were based on the authorsâ argument that maximizing the benefits of the quadruple therapy required initiating as many medication classes as possible in a timely manner.53 According to the authors, each therapy provided early benefits shortly after initiation, typically within less than 30 days. Regarding the factors to consider for specific choice of attributes related to the order of medication prioritization, the authors highlighted the significance of considering the number of titration steps and the time required to achieve the 22 evidence-based dose. The authors gave examples of BB required up to 4 titration steps over a span of 6-12 weeks, while SGLT2I were used in a single fixed dose for all patients. However, the author did not provide any specific rationales for choice of attributes related the timing and characteristics of initiation and titration.53 Packer et al., McMurray et al., Docherty et al., and Lorke et al. described a ârapidâ sequencing strategy across related 5 articles.24,25,32,34,54 The authors discussed several rationales for specific choice of attributes related to the order of medication prioritization. They stated that proper sequencing of medications classes could enhance safety and tolerability.25 The authors proposed a stepwise approach, with step 1 involving simultaneous initiation of a BB and an SGLT2I since they considered BB the most effective in reducing sudden death, while SGLT2Iâs diuretic effect mitigated the short-term risk of worsening HF due to BB.25 Furthermore, the authors highlighted BBâs favorable effects on left ventricular remodeling.24 They also emphasized that treatment with BB and SGLT2I did not require specialized safety monitoring or laboratory testing, allowing patients to establish tolerance to this combination within 2 weeks of ambulatory treatment initiation.24 Regarding ARNI, the authors noted its effect on lowering biomarkers of cardiac wall stress, minimizing the risk of renal function decline compared to ARB alone, preventing excessive hyperkalemia associated with MRA.24 The authors noted that MRA has the unique benefit of once-daily dosing, minimal up-titration, and a modest impact on blood pressure.24 However, they cautioned that MRA could potentially worsen renal function and cause hyperkalemia, again stressing the ARNI and SGLT2I helped counteract the adverse renal and potassium effects of MRA, thus increasing the likelihood of long-term treatment with MRA.24 Regarding the rationales for specific choice of attributes related to the timing and characteristics of initiation and titration, the authors provided several reasons to support the initiation of 23 medications rather than titration, along with advocating for a fast titration approach. Firstly, they highlighted that starting with low doses of foundational medications had shown effectiveness in reducing both morbidity and mortality.25 Secondly, they emphasized that the introduction of a new medication class provided greater benefits compared to increasing the dosage of existing medication classes.25 Furthermore, the authors emphasized the importance of achieving quadruple therapy with all 4 medication classes within 4 weeks.25 They pointed out that many of the benefits associated with quadruple therapy were observed within the first 30 days of initiating treatment.25 Therefore, the recommended algorithm aimed to ensure that patients receive quadruple therapy within this time frame.25 The authors believed their sequencing approach maximized the likelihood of rapidly preventing deaths and hospitalizations and enhanced the tolerability of concurrently or subsequently administered treatments.25 Sharma et al. described a titration strategy for de novo non-ischemic HFrEF.33 In terms of rationales for specific choice of attributes related to the order of medication prioritization, the authors discussed the potential benefits of initiating multiple therapies upfront, particularly ARNI and SGLT2I. According to the authors, this simultaneous initiation of ARNI and SGLT2I may help stabilize potassium levels and kidney function, which could enable the initiation of MRA in the future. The authors highlighted the rationales for specific choice of attributes related to the timing and characteristics of initiation and titration. They emphasized that these therapies have a rapid impact on reducing morbidity and mortality shortly after initiation. Therefore, they advocated for the need to add multiple medication classes in quick succession. The authors also noted that each therapy's effectiveness was independent of the dose or prior initiation of other therapies. Additionally, they emphasized the additive therapeutic efficacy of low doses of each medication class within the quadruple therapy. Thus, they suggested prioritizing the initiation of 24 low doses of all 4 medication classes over strict sequencing and dose escalation, as traditionally recommended. Finally, the authors pointed out that most recommendations for rapid therapy sequencing suggested initiating all medication classes, unless contraindicated, within 4 weeks of identifying heart failure with reduced ejection fraction.33 Silva-Cardoso et al. described a three-step sequence for the initiation of the 4 foundational medications for non-diabetic patients.26 The authors provided rationales for specific choice of attributes related to the order of medication prioritization, stating that their proposal builds upon several influential papers and guidelines in the field, including the papers by McMurray et al., the 2021 updates to the American College of Cardiology HF Expert Consensus, Canadian Cardiovascular Society/ Canadian HF Society HF Guidelines, and European Society of Cardiology/HF Association HF Guidelines preview. They highlighted the benefits of SGLT2I in reducing the risk of HFH and cardiovascular mortality, regardless of the presence of type 2 diabetes, when added to optimized HFrEF therapy consisting of ACEI/ARB/ARNI, BB, and MRA. For HFrEF patients without type 2 diabetes, the authors recommended a three-step disease-modifying medication initiation approach that includes adding SGLT2I to the existing therapy of ARNI, BB, and MRA. The authors stated that this recommendation aligned with the 2021 guidelines of the American Diabetes Association, which emphasized the timely use of SGLT2I therapy for patients with both type 2 diabetes and heart failure. The authors provided the rationales for specific choice of attributes related to the timing and characteristics of initiation and titration. They emphasized that quadruple therapy had shown positive prognostic impacts within a few weeks of initiating therapy. They also highlighted that the combined action of 2 disease-modifying medications at low doses has a greater prognostic impact than a high dose of a single medication. To optimize outcomes for HFrEF patients, the authors recommended a change 25 from the traditional "start low and go slow" approach to a "start low and add fast" strategy, with the goal of initiating all 4 foundational HF disease-modifying medication classes within a 4 to 6-week interval, followed by up-titration during an 8-week period. To minimize complications, they suggested up-titrating one medication at a time, with up-titration steps for each medication occurring every 2 weeks during an in-person visit. By following this approach, the authors believed that most HFrEF patients can initiate and fully up-titrate all 4 medications within a 12 to 14 weeks period.26 Straw et al. described a sequencing strategy in 1 article.35 Regarding the rationales for specific choice of attributes related to the order of medication prioritization, they emphasized that initiating ARNI at the time of diagnosis would address the risk of inertia, ensuring that patients received a more effective treatment during the period of highest risk. They considered SGLT2I as the obvious first choice for medication initiation due to its favorable characteristics, such as the lack of dosing considerations, their early beneficial effects, and reduced concerns about renal function impairment that could arise from up-titrating ARNI and MRA. Regarding the rationales for the specific choice of attributes related to the timing and characteristics of initiation and titration, the authors emphasized the limitations of the traditional approach. They highlighted that attempting to avoid "unnecessary" treatments in patients who "respond" has significant drawbacks: guidelines did not provide a specific time interval for altering therapy, leading to delays in initiating additional agents and incurring additional costs for follow-up; in clinical practice, it often took several months for patients to receive optimized doses of these medications, and many patients never achieve optimal dosing. The authors also noted that even with optimal doses of the quadruple therapy, very few patients become asymptomatic. Thus, they 26 suggested that a slow up-titration approach, followed by a decision to proceed to the next step based solely on symptoms, was not ideal.35 Di Lenarda et al. described 1 sequencing strategy in 1 article.37 The authors provided rationales for specific choice of attributes related to the order of medication prioritization, emphasizing the impact on medication safety and tolerability. The authors suggested their approach allowed patients to have some form of quadruple treatment in the first month. They emphasized that medication tolerability was influenced by the order of initiation, with early initiation of low-dose ARNI and/or SGLT2I reducing the risk of hyperkalemia or worsening renal insufficiency associated with MRA, while initiating ARNI in patients with advanced HF could enhance the hemodynamic tolerability of BB, but titrating ARNI alone to maximum dose may impede the initiation of other medications due to the risk of hypotension. The authors put forth several rationales for specific choice of attributes related to the timing and characteristics of initiation and titration. They highlighted that the incremental benefits of dose escalation from low to high were less apparent compared to the additive effects observed at low doses when multiple medications were initiated simultaneously or in rapid succession. Additionally, the authors argued that their stepwise approach of initiating quadruple therapy at low doses, as opposed to the traditional sequential initiation and dose titration, maximized therapeutic efficacy and accelerated the achievement of clinical benefits. Howlett et al., Miller et al., and El Hussein et al. presented a âclusterâ sequencing strategy from which the specific choices of attributes related to both the order of medication prioritization and the timing and characteristics of initiation and titration could be devised.27,29,36 The scheme divided medications into 3 cluster, and proposed initiating or titrating a medication from each cluster at every clinical interaction, resulting in approximately 3 medication adjustments per 27 visit. The authors proposed specific choices for the order of medication prioritization based on the rationale of grouping medications with similar effects or adverse events. They categorized medications into 3 groups: Cluster 1 consisting of medications with diuretic effects such as loop diuretics and SGLT2I, Cluster 2 comprising medications that directly affect renal and potassium metabolism like ARNI and MRA, and Cluster 3 including medications that directly influence blood pressure or heart rate such as BB and sinus node inhibitors. During each visit, the authors recommend selecting the medication that is easiest and safest to modify as the preferred option. In Cluster 1, SGLT2 inhibitors are favored unless diuretic was necessary due to congestion symptoms or evidence of volume depletion. In Cluster 2, ARNI is the preferred option, except in cases of hypotension. Lastly, in Cluster 3, titration of BB to the target dose is preferred before considering the use of ivabradine. The authors provided several rationales for specific choice of attributes related to the timing and characteristics of initiation and titration. Firstly, they highlighted that utilizing a cluster approach adjusting medications with different neurohormonal effects within the same visit enabling more efficient titration and optimization of multiple medications. In terms of timing, the authors suggested that titration within each medication class should occur no more frequently than every 1 to 2 weeks, which limited the occurrence of adverse events while still ensuring that full titration was achieved within 12 weeks.27 They also referenced titration protocols from landmark trials, which emphasized the completion of titration within 2 to 3 months.27,29,36 The authors emphasized the importance of avoiding a slow optimization of HF medications, as it could result in delays in initiating other life-prolonging medical therapies and device therapies, thus exposing patients to unnecessary risks. They argued against strategies that relied solely on patient response or symptom status, as they may lead to the exclusion of potentially beneficial therapies and delays in medication titration. Furthermore, 28 the authors acknowledged that the rationale for sequential initiation of medical therapy was often related to cost considerations associated with newer therapies. However, they noted that this perceived cost-saving could be mitigated by increasing the number of clinic visits and testing.27 In several articles, Brownell et al., Khan et al., Greene et al., and Tomasoni et al. discussed the strategy of simultaneously initiating all 4 medications in the first visit.28,30,31,38 The authors provided several general rationales for this approach involved both the order of medication prioritization and the timing and characteristics of initiation and titration, including the aim to overcome clinical inertia and treat HFrEF with the necessary urgency. They emphasized that simultaneous initiation and titration leverage the early clinical benefits of each individual therapy, ensuring that HFrEF is addressed promptly. Additionally, the authors suggested that initiating and continuing all medications simultaneously may improve tolerance, adherence, and persistence to the quadruple therapy. They further highlighted that immediate initiation of comprehensive quadruple therapy, followed by prompt titration, took advantage of the significant risk reduction for death and hospitalization associated with each therapy and their fully additive effects. Specifically, regarding rationales for specific choice of attributes related to the order of medication prioritization, the authors stated that delaying the initiation of SGLT2I and the switch from ACEI to ARNI could expose patients to unnecessary risks of hyperkalemia and MRA discontinuation, apart from the increased risk of death and hospitalization. The authors also emphasized that SGLT2I encompassed most of the desirable characteristics for an HFrEF medication, such as once-daily administration, no need for titration, early beneficial effects on clinical events and quality of life as reported by patients, and a favorable safety and tolerability profile. In regards to rationales for specific choice of attributes related to the timing and characteristics of initiation and titration, the authors emphasized the importance of immediate 29 initiation of medication therapy for HFrEF and highlighted the risks associated with delaying treatment. They addressed concerns about simultaneous initiation of multiple therapies, stating that the worsening of HFrEF disease itself was more likely to occur if any of the medications were delayed. They argued that delaying initiation exposed patients to unnecessary risks of clinical deterioration and even the possibility of never receiving the prescribed medications. The authors advocated for providing eligible patients without withholding medications unnecessarily. They emphasized that there was no evidence to support the traditional sequential approach to titration, as it did not offer any proven benefits or improve medication tolerance. While some clinicians may be hesitant about rapidly initiating multiple medications for HFrEF, the authors pointed out that there was no evidence suggesting adverse events associated with this approach. On the contrary, they argued that delaying treatment would result in unnecessary clinical deterioration and an increased risk of cardiovascular death.30,31 2.3.3.3 Classifying sequencing strategies type and profiles During the process of data charting and analysis, we observed that among the attributes linked to the order of medication prioritization, the most prevalent one is the number of medications initiated during the first visit. Meanwhile, regarding the attributes concerning the timing and characteristics of initiation and titration, the dominant attribute is whether to prioritize initiation or titration (i.e., the timing of starting titration relative to completing initiation). These two attributes often shape the specific decisions made for other attributes and were frequently the main focus of attention for most authors due to their clear definability and extensive discussion. Moreover, they play a crucial role in influencing the duration needed to establish patients on quadruple therapy. By classifying strategy types based on these 2 attributes, it is possible to 30 create a framework to account for all possible permutations of sequencing strategies while ensuring distinctiveness among strategies within each type. The identified sequencing strategies exhibited several trends: (1) Most strategies suggested the initiation of 2 or more of the quadruple therapy medications during the first visit; (2) The relative order of medication initiation across strategies were SGLT2I, followed closely by ARNI, BB and lastly MRA; (3) The complete initiation of all medications was often prioritized over titration (i.e., titration was often only started after completion of all initiations); (4) Simultaneous adjustment of 2 or more medications was more common than sequential adjustment. These trends underscore a focus on the speed of alternative sequencing strategies in comparison to traditional sequencing strategies. We took these trends into consideration while proposing the framework for classifying sequencing strategies into types and devising representative profiles for each type, a process discussed below and summarized in Table 2.4, which provides greater detail about the operationalization of these profiles. "Types" are broad categories that can be used to classify various potential strategies, while "Profiles" are sequencing strategies represent these types and identified in the scoping review, with standardization aimed at addressing any gaps in information. Type 1 â Initiation of fewer than 3 medications in the first visit, prioritizing titration over initiation: Strategies falling under this type involved completing titration before starting another medication and sequential adjustment of 1 medication at a time, were found to be less common in our scoping review. This approach closely aligns with the traditional sequencing strategy, where only 1 medication class is initiated during the first visit and subsequently titrated to the target dose before initiating the next medication class. 31 Within this strategy type, there are various potential approaches to the order of medication initiation. A modeling study conducted by Shen et al. indicated that the most favorable theoretical sequence for reducing the composite of HFH or cardiovascular death within this type involved prioritizing medication classes in an order that required the fewest titration steps.53 Specifically, the optimal sequence suggested by the study was the initiation of SGLT2I followed by MRA, then ARNI, and finally BB. To represent this type, we have Profile 1, which aligns with the traditional sequencing strategy. On the other hand, the sequencing strategies described in Shen et al. are represented by Profile 2.53 Type 2 â Initiation of fewer than 3 medications in the first visit, prioritizing initiation over titration: In strategies where initiation is prioritized over titration, 2 medications may be initiated during the first visit, as titration is not required to be done prior to new medication initiation. Most strategies within this type also opt for simultaneous rather than a sequential medication adjustment. Similar to type 1, there are multiple possible approaches to the order of medication initiation with this type. However, a trend observed among the identified strategies in the scoping review reveals two commonly discussed approaches in terms of the order of medication initiation. The first approach gives priority to the initiation of SGLT2I due to its capacity to enhance the tolerability of other medications and its ease of implementation, as it does not require titration. The second approach prioritizes the initiation of ARNI and BB based on their well-established clinical benefits and their traditional position in treatment guidelines. To represent this type with profiles, we have the ârapidâ sequencing strategy proposed by Packer et al., McMurray et al., Docherty et al., and Lorke et al. which align with the first approach and 32 are represented by Profile 3.24,25,32,34,54 On the other hand, the sequencing strategies described in Sharma et al. and Silva-Cardoso et al. align with the second approach and are represented by Profile 4.26,33 Type 3 â Initiation of 3 or more medications in the first visit: In approaches where more than 3 medications are initiated in the first visit, the order of medication prioritization and the consideration of whether to prioritize initiation or titration become irrelevant as all (or almost all) medications are essentially initiated at the same time before titration can occur. In this type, the focus on the characteristics of the titration process becomes more important. Titrating 3 medications simultaneously, after an already more intense initiation scheme compared to type 2, may be limited by a perceived higher risk of adverse events. Among the strategies identified in our scoping review, the use of a âclusterâ approach emerged as the most well-rationalized and described titration strategy. In this approach, the 4 medication classes are divided into 3 clusters based on their hemodynamic effects: cluster 1 consists of medications with diuretic effects (loop diuretics, SGLT2I), cluster 2 includes medications directly affecting renal/potassium metabolism (ARNI and MRA), and cluster 3 comprises medications directly affecting blood pressure or heart rate (BB, sinus node inhibitors). Medications within the same cluster are not adjusted simultaneously to minimize the potential for adverse events. Type 3 include Profile 5 represents the âclusterâ sequencing strategy described by Howlett et al., Miller et al., and El Hussein et al. 27,29,36 and Profile 6, which combines the simultaneous initiation approach advocated Brownell et al., Khan et al., Greene et al., and Tomasoni et al. with the âclusterâ titration approach.28,30,31,38 33 Table 2.4 Sequencing strategy types and representative profiles Strategy type Sequencing strategy profile Description Justification/Rationale Related sequencing strategies from scoping review Type 1 â Initiation of fewer than 3 medications in the first visit, prioritize titration over initiation Profile 1 â One-medication (ACEI/ARB) initiation âtraditionalâ sequencing strategy Step 1: Initiate ACEI/ARB Step 2: Titrate ACEI/ARB Step 3: Initiate BB Step 4: Titrate BB Step 5: Initiate MRA Step 6 Titrate MRA Step 7: Initiate ARNI (Stop ACEI/ARNI) Step 8: Titrate ARNI Step 9: Initiate SGLT2I â¢ Traditional approach to sequencing the HFrEF quadruple therapy. Shen et al.53 (Sequence 1 & 1a); Packer et al.24 (conventional sequencing); Khan et al.31 (traditional strategy). Profile 2 â One-medication (SGLT2I) initiation sequencing strategy Step 1: Initiate SGLT2I Step 2: Initiate MRA Step 3: Titrate MRA Step 4: Initiate ARNI Step 5: Titrate ARNI Step 6: Initiate BB Step 7: Titrate BB â¢ Prioritize initiation of medication classes based on ease of titration, to minimize time to complete initiation of all medications. Shen et al.53 (Sequence 1b). Type 2 â Initiation of fewer than 3 medications in the first visit, prioritize initiation over titration Profile 3 â Two-medication (SGLT2I & BB) initiation ârapidâ sequencing strategy Step 1: Initiate SGLT2I & BB Step 2: Initiate ARNI Step 3: Initiate MRA Step 4: Titrate ARNI, BB, MRA Step 5: Titrate ARNI, BB Step 6: Titrate BB â¢ Maximize the benefits of synergic effects. â¢ Strategy related to rapid sequencing strategy. Docherty et al.32; McMurray et al.25,34; Packer et al.24; Lorke et al.54 (Rapid sequencing) 34 Strategy type Sequencing strategy profile Description Justification/Rationale Related sequencing strategies from scoping review Profile 4 â Two-medication (ARNI & BB) initiation sequencing strategy Step 1: Initiate ARNI & BB Step 2: Initiate MRA Step 3: Initiate SGLT2I Step 4: Titrate ARNI, BB, MRA Step 5: Titrate ARNI, BB Step 6: Titrate BB â¢ Strategy is consistent with the âhistorical approachâ in term of order of medications introduction.55 Sharma et al..33; Silva-Cardoso et al.26 Type 3 â Initiation of 3 or more medications initiation in the first visit Profile 5 â Three-medication initiation âclusterâ sequencing strategy Step 1: Initiate ARNI, BB & SGLT2I Step 2: Initiate MRA, Titrate BB Step 3: Titrate ARNI, BB Step 4: Titrate MRA, BB Step 5: Titrate ARNI â¢ Strategy related to cluster sequencing strategy. â¢ Attempt to balance between the speed of initiation (2 starting medications) with tolerability (4 starting medications). Howlett et al.29; Miller et al.27; El Hussein et al.36 (Cluster Titration Scheme); Di Lenarda et al.37 Profile 6 â Four-medication initiation âsimultaneousâ sequencing strategy Step 1: Initiate ARNI, BB, MRA & SGLT2I Step 2: Titrate ARNI, BB Step 3: Titrate MRA, BB Step 4: Titrate ARNI, BB â¢ Strategy combined simultaneous initiation with cluster up-titration. â¢ Minimize time to complete initiation. Brownell et al.28; Khan et al.31; Greene, et al.30; Tomasoni et al.38 (Simultaneous sequencing) 35 Figure 2.2 provided a visual representation of each profile with the following standardizations and assumptions: (1) The number of up-titration visits required to achieve the target dose for each medication as shown in table A1: ACEI/ARB/ARNI (3 visits); BB (4 visits); MRA (2 visits); SGLT2I (1 visit). (2) All medications were titrated simultaneously, unless there were specific strategies we wanted to mimic (i.e., cluster titration rule); (3) Frequency of medication adjustment is every 1 week. 36 Figure 2.2 Visual representation of sequencing strategy profiles Type 1 â Initiation of fewer than 3 medications in the first visit, prioritize titration over initiation Profile 1 â One-medication (ACEI/ARB) initiation âtraditionalâ sequencing strategy STEP 1 2 3 4 5 6 7 8 9 ACEI/ ARB 25% Target 50% Target Target ARNI 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 2 â One-medication (SGLT2I) initiation sequencing strategy STEP 1 2 3 4 5 6 7 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Type 2 â Initiation of fewer than 3 medications in the first visit, prioritize initiation over titration Profile 3 â Two-medication (SGLT2I & BB) initiation ârapidâ sequencing strategy STEP 1 2 3 4 5 6 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target 37 Profile 4 â Two-medication (ARNI & BB) initiation sequencing strategy STEP 1 2 3 4 5 6 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Type 3â Initiation of 3 or more medications initiation in the first visit Profile 5 â Three-medication initiation âclusterâ sequencing strategy STEP 1 2 3 4 5 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 6 â Four-medication initiation âsimultaneousâ sequencing strategy STEP 1 2 3 4 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target *Diagnosed dashed line indicates the completion of the sequencing process. 38 2.4 Discussion 2.4.1 Summary of evidence In this scoping review, we identified 8 articles describing 18 alternative approaches to sequence medications making up the quadruple therapy in patients with de novo HFrEF in the ambulatory care setting. The majority of articles were commentaries, and one was a modeling study.53 The majority of strategies identified in this scoping review involved the initiation of 2 or more medications during the first visit. Among these strategies, the relative order of medication initiation across various strategies was SGLT2I, followed by ARNI, BB, and finally MRA. It was observed that all medications were typically initiated before the start of titration for any individual medication. Simultaneous adjustment of multiple medications during the same visit was more frequently described than sequential adjustment of 1 medication at a time. Additionally, the average frequency of medication adjustment reported across the strategies was typically every 2 weeks or less. When considering the rationales for specific choice of attributes related to the order of medication prioritization, several common factors were repeatedly cited, including how different medications interacted with each other,24,25,32,34,35,54 the practicality of implementing the chosen strategy in clinical practice (i.e., steps take to titrate medications, requirement of additional monitoring),24,25,32,34,53,54 and finally, alignment with previously established guidelines.56 When it comes to specific choice of attributes related to the timing and characteristics of initiation and titration, the decision to prioritize completing initiation before starting titration was frequently supported by studies demonstrating the early onset of treatment benefits, the comparison between high and low medication doses, and the advantages of adding additional medications versus titrating existing medications to higher doses.24,25,27,29â38,54 These rationales were also 39 often used to support the decision to simultaneously adjust multiple medications during the same visit.24,25,27,29â38,54 In the 1 strategy that employed sequential adjustment of 1 medication at a time, the authors noted that the reason behind this approach was to minimize the potential risk of complications that may arise from simultaneous adjustments.26 Shen et al. whose strategies that involved implementing titration before completing initiation did not provide specific rationales for this approach.53 When considering the specific order of medication introduction, given the availability of 4 medication classes, there is a vast number of possible combinations, potentially resulting in dozens of different sequencing strategies. Consequently, it is not surprising that there was minimal overlap among the unique sequencing strategies identified in this scoping review. It is also important to note that some strategies used in practice may not have been identified if they were not discussed in the articles or relevant literature, preventing their retrieval. However, it is not necessary to identify every single possible strategy. Through analyzing the existing proposed strategies in the literature, valuable insights were gained into the key factors considered by experts when sequencing therapy for HFrEF. Overall, the analysis confirmed the initial impression that proponents of alternative sequencing strategies aim to address perceived issues with traditional sequencing strategy by reducing the time required to establish patients on quadruple therapy. Among the various attributes considered, the number of medications initiated during the first visit and whether to prioritize initiation or titration (i.e., the timing of starting titration relative to completing initiation) emerged as the most dominant attributes contributing to this theme of emphasizing on speed, and also played a significant role in shaping decisions for other attributes. 40 Based on the specific choices of these 2 attributes, we have provided a framework to categorize the sequencing strategies into 3 distinct strategy types. For each type, 2 sequencing profiles had been developed as representative examples. These profiles drew inspiration from the identified strategies in the scoping review and capture common trends, allowing for a more comprehensive understanding of the range of sequencing approaches within each type. They provided a meaningful overview of the essential characteristics and nuances of the identified strategies while maintaining distinctiveness among the profiles. 2.4.1.1 Number of medications initiated during the first visit The choice of the number of medications initiated during the first visit stood out as one of the most frequently reported, readily identifiable, and easily extracted attributes in the literature. This attribute provided valuable insights into the authors' preferred approaches when sequencing HFrEF quadruple therapy. It served as a crucial indicator of the initial treatment intensity and set the foundation for subsequent medication adjustments and titrations. For instance, in strategies involving the initiation of 3 or more medications during the first visit, (represented by our Type 3), the specific choices of attributes related to the identity and order of medications initiated in the first visit, as well as the timing of starting titration relative to completing initiation, were inherent in the choice of this approach by default. This choice revealed the authors' emphasis on completing medication initiation before starting titration, ensuring that all necessary medications were initiated and established before adjusting their dosages. With this approach, the focus of attention shifted to the process of medication titration, which was frequently underreported, despite simultaneous titration (defined as multiple (â¥2) medications titrated, adjusted in the same visit in at least 1 step) being commonly chosen in most strategies. Notably, the âclusterâ sequencing strategy described by Howlett et al., Miller et al., 41 and El Hussein et al. provided explicit details and rationales for medication titration,27,29,36 while the âsimultaneousâ sequencing strategy advocated in Brownell et al., Khan et al., Greene et al., and Tomasoni et al. also offered some information on the titration process but lacked specific rationales.28,30,31,38 In more conservative approaches where fewer than 3 medications were initiated during the first visit (represented by Type 1 and Type 2), there was flexibility in choosing the order of medication initiation, timing of initiation/titration, and other attributes shaping the sequencing strategy. In general, for strategies identified in our scoping review, most authors did not provide a reason why a certain number of initial medications were chosen, even when such number was provided. Indeed, many authors indicated that the number and the identity of initial medications could be flexible, though rarely fewer than 2.35,37,56 2.4.1.2 Order of medication initiation and prioritization When comparing the relative order of medication initiation across different sequencing strategies, ARNI and BB emerged as the most commonly prioritized classes, closely followed by SGLT2I and MRA. However, if we include the sequences proposed by Shen et al., SGLT2I becomes the most prioritized medication, followed by BB, ARNI, and finally MRA. The stated rationales for ARNI over ACEI/ARB were the improvements in efficacy observed in the PARADIGM-HF trial,57 and the ability to skip the washout period versus starting with an ACEI and needing to switch to ARNI afterwards, simplifying the treatment process and reducing the potential for inertia.35 Furthermore, authors asserted that the addition of a neprilysin inhibitor may improve renal outcomes and reduce the risk of hyperkalemia compared to ARB alone.58,59 Most importantly, authors stressed the ability of an ARNI to reduce sudden cardiac deaths was not reported, or at least measured with ACEI/ARB.60 Speaking of BB, some authors preferred to 42 prioritize BB for initiation and titration because of its ability to reduce sudden cardiac deaths,61,62 and to exert positive influence on left ventricular modeling.63,64 Factors that favored early initiation of SGLT2I listed by authors included their favorable tolerability profile, glucose-lowering effect in patients with concomitant type 2 diabetes, ease of administration, lack of need for titration, as well as their synergetic impact on other medicationsâ tolerability. Particularly, some authors stated that the mild diuretic effect of SGLT2I could mitigate fluid retention and potential for acute worsening of HF from BB, and their impact on potassium handling minimized the risk of hyperkalemia and renal impairment with ARNI and MRA.12,65â70 MRA was often positioned as the last medication in most sequences and received relatively less attention in the articles. The focus seemed to be more on the potential disadvantages of MRA, such as the risk of hyperkalemia and renal impairment, without giving due consideration to their advantages.71,72 Theoretically, one advantage of MRA was their minimal impact on diuresis and blood pressure, making them easy to add on at target-range doses to most regimens. Surprisingly, none of the articles highlighted this benefit, rather articles were more likely to focus on how to manage risk of hypotension with ARNI and BB, alone or as a combination.24,25,33 Additionally, similar to SGLT2I, MRA required few titrations to reach target doses, which translated to fewer titration steps compared to ARNI and BB, which hypothetically allowed it to reach the maximum clinical benefit earlier, and facilitated faster initiation of other medications.53 Finally, cliniciansâ comfort and familiarity may also play a role in these recommendations, with strategies prioritizing ARNI and BB before MRA and SGLT2I possibly taking advantage of their similarity to the traditional approach of starting with ACEI/ARB and BB, following by newer medications as recommended in older guidelines.26 43 When it came to medication prioritization for the strategies identified through this scoping review, the process was conceptualized as having 2 main approaches. The "ease of medication administration" approach focused on the ease of initiating and titrating medications. In this context, SGLT2I and MRA were often prioritized due to their fewer titration steps, making them more straightforward to incorporate into treatment regimens. SGLT2I, in particular, offered the advantage of reducing adverse events when used in combination with other medication classes (represented by Profile 2 - Type 1 and Profile 3 - Type 2). The "clinical benefits and guideline alignment" approach prioritized the initiation of ARNI and BB, given their well-established clinical benefits and alignment with existing guidelines. These medications had demonstrated efficacy in improving patient outcomes, especially in reducing sudden cardiac deaths and positively influencing left ventricular remodeling (represented by Profile 4 - Type 2). 2.4.1.3 The timing of starting titration relative to completing initiation We used the timing of titration relative to completing initiation as a surrogate for determining whether a strategy prioritized initiation or titration. This attribute was crucial and could be argued to serve as one of the primary distinguishing features between most alternative sequencing strategies (represented by Type 2 and Type 3) and the traditional approach and its similarity (represented by Type 1). Our review found that most alternative sequencing strategies favored initiating all medications before starting titration. One rationale for prioritizing the initiation of all medications before starting titration was the belief that the benefits and risks of adding additional medications outweighed the benefits and risks associated with titration. Authors supported this rationale by citing evidence of the quick onset of treatment benefits and argued that earlier initiation allowed patients to experience therapeutic effects sooner.71,73â80 Based on the analysis of registry data, 44 some authors argued that medication titration and adjustment could be challenging and time-consuming to implement, and advocated for starting all medications at low-to-moderate doses initially to ensure a smoother transition to the titration phase and facilitate the management of medication adjustments in clinical practice.20â22,81â87 In contrast to the traditional sequencing strategy, some authors argued that a strict sequential order may not be necessary, as each medication class provided independent or additive clinical benefits.24,25,27â34,36â38,53,54,56 Some also suggested initiating multiple low-dose medications upfront and reserving up-titration for later stages as a strategy to potentially reduce the occurrence of adverse events.73,88â91 Overall, these findings reinforced our observation that the primary focus among the identified strategies was the speed of establishing patients on quadruple therapy, with titration considered of lesser importance in optimizing treatment outcomes. Given the prevailing trend of prioritizing initiation over titration, it is noteworthy to mention an exception observed in the study conducted by Shen et al., where a strategy was identified that involved immediate titration following medication initiation. It is important to clarify that this study did not propose or recommend any sequencing strategies; rather, it presents them as modeling options.53 However, if we were to consider this approach for specific reasons, this study showed that focusing on medications with the fewest titration steps, such as SGLT2I and MRA (represented by Profile 2 - Type 1), could potentially offer significant clinical benefits and align with the overarching theme of expediting the establishment of patients on quadruple therapy observed in other approaches.53 2.4.1.4 Approaches to medication adjustment There was a lack of consensus and limited elaboration among the identified strategies regarding the characteristics of the medication adjustment process, in contrast to the more agreed-upon 45 timing of titration. While two strategies did not provide sufficient information to determine whether they supported a simultaneous or sequential approach to medication adjustments,24,25,32,34,37 the remaining strategies were divided on this issue, with a slight preference for simultaneous adjustment. Specifically, 10 strategies (56%) favored simultaneous adjustment, where 2 or more medication classes were initiated or titrated during the same visit, compared to 6 strategies (33%) that employed sequential up-titration, where medication classes were initiated or titrated 1 at a time.26,53 Among strategies choosing sequential adjustment, Silva-Cardoso et al. cited concerns about safety and the need to monitor and assess the benefits of each treatment individually as reasons for this recommendation, while no rationale were provided Shen et al.26,53 Among strategies suggested simultaneous adjustment of 2 or more medications during the same visit, Brownell et al., Khan et al., Greene et al., and Tomasoni et al. suggest a staggered approach to titration following âsimultaneousâ initiation of all 4 medication classes. In the first 1-2 weeks, only BB is titrated, followed by the titration of ARNI, BB, and MRA in weeks 2-4, and finally the titration of ARNI and BB in weeks 4-6.28,30,31,38 Compared to Howlett et al., Miller et al., and El Hussein et al. âclusterâ sequencing strategy, where according to the rule, since ARNI and MRA are in the same cluster they should not be initiated or titrated together, instead ARNI was initiated along with BB, and MRA was initiated in the following visit within the first 1-2 weeks alongside with BB titration.27,29,36 With the âsimultaneousâ sequencing strategy, it was unclear the exact reasons as to why the authors proposed this exact titration scheme. In contrast, âclusterâ sequencing strategy provided well-defined rules for dividing medications into clusters based on their hemodynamic and pharmacologic effects.27,29,36 The aim of this clustering was to reduce adverse events and improved tolerability by ensuring that medications from the same cluster were not 46 adjusted together.27,29,36 This resulted in a well-established sequencing strategy where both the choice for medication initiation and titration were clearly defined and supported (represented by Profile 5 â Type 3). Taking a step further, by combining the âclusterâ titration scheme with âsimultaneousâ initiation, we can potentially create a sequencing strategy that not only establishes quadruple therapy quickly but also provides a structured and well-rationalized approach to medication titration (represented by Profile 6 â Type 3). Apart from the âclusterâ and the âsimultaneousâ sequencing strategy, most other strategies lacked detailed recommendations on how to approach titration. Instead, they commonly provided generic comments such as "uptitrate as tolerated" or "pursue up-titration", 24,25,33 or focused on addressing common adverse events,26,33 with limited guidance on medication class prioritization or combinations for titration. The lack of consensus and clear guidance on how to titrate quadruple therapy may reflect the current perception that titration was of secondary importance compared to medication initiation. The perceived complexity of titration may have also contributed to the scarcity of detailed recommendations in this area. 2.4.1.5 Other factors impacting the intensity and speed of sequencing strategies The frequency of medication adjustments was an often-overlooked factor that could influence the intensity and speed of establishing patients on quadruple therapy. The suggestions regarding the appropriate frequency of visits varied among authors, with many lacking detailed explanations. Some authors assumed standard frequencies and durations of follow-up based on what they believed to be the best or most tolerable for the patient, taking into account the specific choices of attributes discussed in other sections. In our review, the estimated time to start and fully titrate all 4 medications ranged from 0 to 11 weeks and 8 to 14 weeks, respectively. This variability was influenced by the number of initial 47 medications, the characteristics of medication adjustment, and the frequency of medication adjustments. Most strategies (77%) involved adjusting medications every â¤2 weeks, while a smaller proportion (17%) involved slower frequencies of 2-4 weeks. Notably, all strategies highlighted the significance of initiating all 4 medication classes within the first few weeks. Strategies with longer medication adjustment frequencies were often characterized by fewer steps to achieve this goal, allowing patients to complete initiation within the same period. For instance, aiming to complete initiation within 4 to 6 weeks, authors suggested strategies with 3 steps typically had 2 weeks between visits, while strategies with 2 steps had 3 weeks between visits.26,33 Explicit rationales for these frequencies were often lacking. One possible reason for this was that these decisions may be based on authorsâ interpretation of primary literature that was presented in the general rationales section, particularly regarding the speed and onset of treatment benefits. Many authors agreed that all 4 medication classes exerted their efficacy within a few weeks of initiation, citing the same landmark trials.92â97 However, the application of this evidence into specific steps resulted in wide variability. In cases where strategy-specific rationales were available, shorter frequencies of medications adjustments (1-2 weeks) had been linked to adverse events and following pre-existing guidelines.10,26,27 Completing titration within 3 months allowed for earlier re-evaluation for defibrillator implantation,37 or aligned with titration protocols of landmark trials.27,93,98 Lastly, the expected time to complete medication titration/adjustment also depended on assumptions about the number of steps required to achieve up-titration for each medication class. Authors commonly suggested that ARNI requires 1-2 titration steps, BB requires 2-4 steps, and 48 MRA requires 1 step, often correlating with the number of steps required to double the dose from the starting dose to the target or maximum dose.26,35,99 2.4.2 Limitations Our scoping review had several limitations that should be acknowledged. Firstly, we found that many authors did not provide sufficient detailed explanations about the attributes of sequencing strategies, resulting in a lack of clarity and specificity. While general rationales against the traditional sequencing strategy were commonly discussed, strategy-specific rationales were often lacking. This made it challenging to fully understand the rationale behind certain choices within the strategies. Additionally, rationales that were provided were often broad and could be applied to support various approaches, leading to ambiguity in strategy interpretation. Additionally, it is important to acknowledge the limited availability of data or evidence regarding certain aspects of sequencing strategies. Due to this lack of clear evidence, authors may have relied on their own preferences, assumptions about the risks and benefits of medications, and considerations of resource availability when formulating their strategies. The inclusion of Shen et al. 's modeling study provided valuable insights into additional sequencing strategies, particularly those prioritizing the titration over initiation approach. However, it stood apart from the other proposed strategies we examined due to its qualitative nature. To accurately represent its distinctive nature, we made a clear distinction within our analysis, highlighting that Shen et al.'s study does not propose or endorse any of the sequencing strategies discussed. Instead, it offered a contrasting perspective to the other proposed strategies. 2.5 Conclusion Our scoping review identified 8 articles that described 18 alternative sequencing strategies aimed at replacing the traditional sequencing strategy to establishing quadruple therapy for HFrEF 49 patients. We observed several key trends in the choice of attributes of sequencing strategies that contribute to the overarching theme of prioritizing the speed of establishing the quadruple therapy. Among the attributes, âthe number of medications initiated during the first visitâ and âthe timing of starting titration relative to completing initiationâ, as a surrogate for determining whether to prioritize initiation or titration, emerged as the 2 dominant attributes that were extensively discussed within this theme. Based on these 2 attributes, we developed a framework to classify all possible sequencing strategies into 3 distinct strategy types. Additionally, within each type, we proposed 2 sequencing strategy profiles by drawing inspiration from the strategies identified in the scoping review and incorporating established trends to address any gaps in assumptions. The insights obtained from this review are valuable for informing the development of a model that can assess the relative efficacy, harm, utility, and costs associated with these sequencing strategy profiles. 50 Chapter 3: Microsimulation model 3.1 Introduction In the previous chapter, we conducted a scoping review to explore the various proposed HFrEF quadruple therapy sequencing strategies. From this review, we developed 3 types of sequencing strategies characterized by the number medications initiated in the first visit (fewer than 3 versus 3 or more during the first visit) and the timing of starting titration relative to initation. For each type, 2 profiles based on existing strategies identified in the scoping review were chosen to represent each type. Since there is a lack of evidence from RCTs and observational studies comparing the various sequencing strategies, decision-makers currently have limited data to guide their actions. Shen et al. conducted a modeling study of several sequencing approaches for HFrEF and found that optimizing the order of treatment could potentially reduce deaths and the number of patients experiencing adverse outcomes.53 However, their study had several limitations, as our scoping review revealed that the sequences they explored did not fully align with those proposed in the literature, and they did not consider costs or account for uncertainties in the medication adjustment process. To address these limitations, a benefit-harm and cost-utility analysis can provide a valuable framework for evaluating the economic efficiency and clinical effectiveness of different sequencing strategies, while microsimulation can help incorporate variability in the medication adjustment process, offering a more comprehensive assessment of the strategies' outcomes. By conducting this analysis, our aim is to provide insights that will assist healthcare providers, policymakers, and other stakeholders in making informed decisions regarding the allocation of healthcare resources and optimizing patient outcomes in the management of HFrEF. 51 The objective of this chapter is to compare the benefit-harm and cost-utility of proposed HFrEF quadruple therapy sequencing strategies using a microsimulation model. 3.2 Methods 3.2.1 Model design We used an individual-based state-transition microsimulation model to compare 6 HFrEF quadruple therapy sequencing strategy profiles identified from the Chapter 2 scoping review. The design and reporting followed the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement.100 All stages of the work were informed by discussions with clinicians, who provided feedback on the model structure, data inputs, and assumptions. A microsimulation model of 10,000 trials, where each trial represented a simulated patient, was selected instead of a Markov cohort model due to its ability to track individual patient histories. This allowed for the modeling of medications adjustment based on adverse events during each cycle, which is essential for emulating sequencing strategy profiles. The microsimulations incorporated data from the literature on the cost of treatment,101 medication adjustments,102 and HFH,103 and utilities associated with outcomes.104â108 We used a 1-week cycle length, corresponding to the minimum proposed frequency between therapy adjustments, and to the median length of hospital stay for HF in Canada.103 We modeled over a lifetime horizon with a half-cycle correction, which is a method to account for the fact that events can occur at any point during the cycle. It involves subtracting and adding half of the outcome in the initial and final cycles of the discrete-time model. The microsimulation model was constructed with TreeAge Pro 2022 (TreeAge Software, Williamstown, MA). 52 3.2.2 Model structure A state-transition diagram of the model is presented in Figures 3.1. All patients started in the stable HF state (S) and could remain in this state, be hospitalized for heart failure (HFH), or die (M). Hospitalized patients could die or return to the stable HF state. While patients were in the stable state and still undergoing medication adjustment, they had a probability of transiently experiencing one of the following adverse events: bradycardia, hypotension, hyperkalemia, and renal impairment. These adverse events could be either dose-limiting or non-dose-limiting. The probabilities of HFH (S -> HFH), dying (S -> M), or experiencing any of the adverse events depended on each individual patientsâ combination of medications and dose-levels (i.e., sub-target or target dose) in the current cycle. Figure 3.1 State transition diagram 53 3.2.3 Sequencing strategy profile representation and therapy adjustment algorithm In the model, sequencing strategy profiles are represented by a sequence of steps and corresponding walks. A sequencing step refers to a unique combination of medications and dose-levels defined within a sequencing profile, while a walk is a breakdown of each sequencing step in weekly cycles. The added granularity provided by walks allows for the precise determination of a patient's current position within the sequencing process, which cannot be achieved by steps alone. Furthermore, as cycles represent the passage of time and are bound to increase, patients can also regress or progress through the sequencing strategy; hence, relying solely on the concept of cycles is inadequate for accurately depicting the dynamics we aim to capture with walks. Figure 3.2 illustrates how each strategy profile identified from the scoping review is visualized through sequencing steps and walks. Patients begin in the first walk and can transition through the sequencing profiles by moving to the next walk, staying in the same walk, or moving back to the walk corresponding to a previous step, following a medication adjustment algorithm depicted in Figure 3.3. The algorithm simulates a simplified medication adjustment decision tree made in clinical practice. If the patient did not experience an adverse event in the previous cycle, they can continue with adjustment (i.e., move to the next walk); If the patient experienced adverse events, the clinician may consider slowing or delaying the adjustment process (i.e., stay at the same walk). If these adverse events are considered severe and dose-limiting, treatment may be de-escalated (i.e., move back one step). 54 Figure 3.2 Visual representation of sequencing strategy profiles Profile 1a Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 8 9 10 ACEI/ ARB 25% Target 50% Target Target ARNI 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 1b Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 8 9 10 ACEI/ ARB 25% Target 50% Target Target ARNI 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 2a Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 8 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 2b Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 8 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target 55 Profile 3a Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 3b Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 4a Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 4b Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 7 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target 56 Profile 5a Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 5b Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 6 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 6a Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target Profile 6b Walk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 STEP 1 2 3 4 5 ACEI/ ARB ARNI 25% Target 50% Target Target BB 12.5% Target 25% Target 50% Target Target MRA 50% Target Target SGLT2I Target *Diagnosed dashed line indicates the completion of the sequencing process. 57 Figure 3.3 Medication adjustment algorithm Non-dose limiting HF hospitalization (HFH) All-cause mortality (M) HF stable (S) Have an adverse event? Type of adverse event? Continue adjustment (Move forward 1 Walk) De-escalation/ Delay adjustment (Move back 1 Step) Delay adjustment (Stay at the same Walk) Yes No Serious/ Dose limiting 58 3.2.4 Base case The base case analysis used a hypothetical 10,000 trials cohort of 60-year-old patients newly diagnosed with HFrEF with New York Heart Association class 2 who were treatment-naïve and had no contraindications to the standard therapies. This emulated the placebo arm of the Studies of Left Ventricular Dysfunction (SOLVD) trial from which the baseline event rates for HFH and mortality were derived for an untreated individual.109,110 For the base scenario, we assumed that patients would receive follow-up and undergo medications adjustment, and thus experience adverse events and costs associated with medications adjustments during the first year. After that, they would be established on whichever combination of medications (i.e., representing by step/walk) they were on at the end of the first year. At that point, we assumed patients would no longer experience adverse events or incur medication adjustments costs, but they would continue to derive consistent transition probabilities for death or HFH until death, as well as incur costs associated with treatments itself and HF hospitalization. All model inputs are listed in Table 3.1. Table 3.1 Model input Parameter/Variable Value Range Distribution Source Base case for clinical outcomes (1 Cycle or 1 Week) HF hospitalization (HFH) incidence rate (S -> HFH)* 0.006768 NA SOLVD109 All-cause mortality incidence rate (S -> M)* In-trial (0-4 year) 0.003265156 NA SOLVD110 Follow-up (4-12 year & longer) 0.002715964 NA SOLVD110 Correction factor for all-cause mortality 0.8 NA SOLVD109 In-hospital mortality incidence rate* (HFH -> M) 0.089925 NA Poon et al.4 Age-related risk ratio per year HF hospitalization 1.0385 NA CHARM111 In-hospital mortality 1.029 NA Fonarow et al.112 59 Parameter/Variable Value Range Distribution Source Base case for adverse events (1 Cycle or 1 Week) Adverse event rate Hypotension* 0.000463 NA SOLVD113 Bradycardia* 0.000177 NA US Carvedilol HF Study114 Hyperkalemia* 0.000026 NA SOLVD113 Renal impairment* 0.001168 NA SOLVD115 Proportion of adverse events that are dose-limiting Hypotension 39.3% 0.8%-77.8% Beta SOLVD113 Bradycardia 7.8% 0.2%-15.4% Beta US Carvedilol HF Study114 Hyperkalemia 14.3% 0.3%-28.3% Beta SOLVD113 Renal impairment 14.6% 0.3%-28.9% Beta EMPHASIS-HF72 Risk ratio for treatments versus placebo ACEI (Target Dose) HF hospitalization 0.71 0.65-0.77 Log-normal BÅuf-Gibot et al,116 Flather et al.117 All-cause mortality 0.85 0.80â0.90 Log-normal BÅuf-Gibot et al.116 Hypotension 1.49 1.29â1.71 Log-normal BÅuf-Gibot et al.116 Bradycardia 1 Known pharmacology Hyperkalemia 2.23 1.65â3.00 Log-normal BÅuf-Gibot et al.116 Renal impairment 1.33 1.12â1.57 Log-normal BÅuf-Gibot S.116 ACEI (Sub dose) HF hospitalization 0.82 0.72-0.92 Log-normal Turgeon et al.75 All-cause mortality 0.896 0.82â0.98 Log-normal Turgeon et al.75 Hypotension 1.49 1.29â1.71 Log-normal Assumption Bradycardia 1 Known pharmacology Hyperkalemia 2.23 1.65â3.00 Log-normal Assumption Renal impairment 1.33 1.12â1.57 Log-normal Assumption ARNI (Target Dose) HF hospitalization 0.56 0.49â0.64 Log-normal BÅuf-Gibot et al,116 PARADIGM-HF57 All-cause mortality 0.72 0.64â0.81 Log-normal BÅuf-Gibot et al,116 PARADIGM-HF57 Hypotension 2.32 1.91â2.80 Log-normal BÅuf-Gibot et al.,116 Gao et al.118 Bradycardia 1 Known pharmacology 60 Parameter/Variable Value Range Distribution Source Hyperkalemia 2.43 1.74â3.40 Log-normal BÅuf-Gibot et al.,116 Gao et al.118 Renal impairment 1.24 0.97â1.58 Log-normal BÅuf-Gibot et al.,116 Gao et al.118 ARNI (Sub Dose) HF hospitalization 0.56 0.49â0.64 Log-normal Vardeny et al.,76 PROVE-HF119 All-cause mortality 0.72 0.64â0.81 Log-normal Vardeny et al.,76 PROVE-HF.119 Hypotension 2.32 1.91â2.80 Log-normal Assumption Bradycardia 1 Known pharmacology Hyperkalemia 2.43 1.74â3.40 Log-normal Assumption Renal impairment 1.24 0.97â1.58 Log-normal Assumption BB (Target Dose) HF hospitalization 0.63 0.56â0.71 Log-normal Shibata et al.120 All-cause mortality 0.65 0.57â0.74 Log-normal Shibata et al,120 McAlister et al.77 Hypotension 1.24 0.92â1.64 Log-normal Barron et al.121. Bradycardia 3.54 2.19â5.42 Log-normal Barron et al.121. Hyperkalemia 1 Known pharmacology Renal impairment 1 Known pharmacology BB (Sub Dose) HF hospitalization 0.63 0.56â0.71 Log-normal Turgeon et al.75 All-cause mortality 0.65 0.57â0.74 Log-normal Turgeon et al.,75 McAlister et al..77 Hypotension 1.24 0.92â1.64 Log-normal Turgeon et al..75 Bradycardia 3.45 2.19â5.42 Log-normal Wikstrand et al.78 Bristow et al.122 Simon et al..123 Hyperkalemia 1 Known pharmacology Renal impairment 1 Known pharmacology MRA (Target Dose) HF hospitalization 0.80 0.70â0.92 Log-normal Berbenetz et al.124 All-cause mortality 0.83 0.77â0.88 Log-normal Berbenetz et al.124 Hypotension 1 Serenelli et al.125 Bradycardia 1 Known pharmacology Hyperkalemia 2.03 1.78â2.31 Log-normal Berbenetz et al.124 61 Parameter/Variable Value Range Distribution Source Renal impairment 1 Ferreira et al.71 MRA (Sub Dose) HF hospitalization 0.80 0.70â0.92 Log-normal Ferreira et al.71 All-cause mortality 0.83 0.78â0.88 Log-normal Ferreira et al.71 Hypotension 1 Known pharmacology Bradycardia 1 Known pharmacology Hyperkalemia 2.03 1.78â2.31 Log-normal Ferreira et al.71 Renal impairment 1 Ferreira et al.71 SGLT2I HF hospitalization 0.69 0.61â0.78 Log-normal Zannad et al..12 All-cause mortality 0.87 0.77â0.98 Log-normal Zannad et al..12 Hypotension 1 Butler, et al.126 Bradycardia 1 Known pharmacology Hyperkalemia 0.82 0.71â0.95 Log-normal Ferreira et al..127 Renal impairment 0.63 0.59â0.67 Log-normal Butler et al..126 Utility/Disutility Clinical Outcomes â Utility (52 Cycle or 1 Year) Stable HF 0.657 0.591 â 0.723 Beta Armoiry et al.104 HF hospitalization 0.551 0.496 â 0.606 Beta Armoiry et al.104 All-cause mortality 0 Assumption Adverse events - Disutility (1 Cycle or 1 Week) Hypotension 0.029 0.017 â 0.042 Beta Ademi et al.105 Bradycardia 0.025 0.014 â 0.035 Beta Sullivan et al.106 Hyperkalemia 0.010 0.009 â 0.011 Beta Widen et al.107 Renal Impairment 0.054 0.052 â 0.057 Beta Salcedo et al.108 Cost (1 Cycle or 1 Week) Reimbursement for encounter for medication adjustment (in-office visit age 60-69) $36.47 $9.4-$79.94 Gamma British Columbia Medical Services Commission Payment Schedule.102 62 Parameter/Variable Value Range Distribution Source HF hospitalization $14,194 $3,867-$31,111 Gamma Canadian Institute for Health Information103 ACEI $0.78 + $1 Dispensing fee $0.49-$3.9 Gamma Pacific Blue Cross Pharmacy Compass.101 ARNI $56 + $1 Dispensing fee $15.53-$124.93 Gamma Pacific Blue Cross Pharmacy Compass.101 BB $1.56 + $1 Dispensing fee $0.69-$5.61 Gamma Pacific Blue Cross Pharmacy Compass.101 MRA $0.7 + $1 Dispensing fee $0.46-$3.72 Gamma Pacific Blue Cross Pharmacy Compass.101 SGLT2I $20.57 + $1 Dispensing fee $5.87-$47.28 Gamma Pacific Blue Cross Pharmacy Compass.101 *After calculation, all rates converting to probabilities for the transition probability matrix. 3.2.5 Comparators To compare the different sequencing profiles, the model included 2 versions, with the use of fortnightly medications adjustment being designated as âVersion aâ and weekly medications adjustment as âVersion bâ of all 6 profiles suggested in Chapter 2, along with an âuntreatedâ group, resulting in a total of 13 comparators. In addition, the number of medications initiated in the first visit generally increased from Profile 1 (1-medication âTraditionalâ initiation sequencing strategy) to Profile 6 (4-medication âSimultaneousâ initiation sequencing strategy). As a result, profiles with higher numbers and version b would be considered more intensive in terms of medications adjustment. 63 3.2.6 Model inputs and assumptions 3.2.6.1 Transition probabilities Transition probabilities for each cycle, which tied to the step/walk of the sequencing profiles, were estimated based on therapies and dose-levels, using data from landmark RCTs or meta-analyses of RCTs. Our model made the following assumptions: First, HFH, all-cause mortality, and adverse events were modeled to follow an exponential survival distribution, characterized by a constant hazard rate over time. Second, beneficial treatment effects and adverse events of each medication itself were independent of the sequencing order and background combination of medications. We applied relative treatment effect measures (i.e., risk ratios) to the âuntreatedâ event rates to obtain absolute event rates for the different sequencing step/walk. Third, during titration, we assume that patients derived the effects of sub-target dose, and they only derived the effects of target dose once titration is completed. Furthermore, the effect was the same at all sub-target dose-levels. In other words, we assumed that both the 12.5% and 75% sub-target doses had the same effects, but these effects may differ from the 100% target dose. Fourth, we used a correction factor of 0.8 for mortality rate (S -> M) to avoid double-counting in-hospital mortality, since these were already account for by in-hospital mortality rate (HFH -> M). This factor was determined by the observation that 20% of all deaths in SOLVD (102 out of 510) occurred within 7 days of hospitalization for HF, which we assumed to be a reasonable approximation of in-hospital mortality rate in our model.109 Fifth, we applied relative risk increases by age for both the HFH rate (S -> HFH) and in-hospital mortality rate (HFH -> M) to adjust for the increased risk of these outcomes with advancing age.111,112 Since the mortality rate had already been estimated using 12-year follow-up data, we deemed it unnecessary to further adjust for age-related risks.110 Sixth, we assumed that adverse events were transient and occurred 64 only within 1 cycle. We assume these adverse events would resolve without intervention, thus incurred no cost, and would not impact the future risk of adverse events or other outcomes, except for the potential of delaying or deescalating medication adjustments and the associated disutility if the adverse event was dose-limiting. 3.2.6.2 Costs The model included costs of medication acquisition, medication adjustment visits, and HFH from published sources.101â103 In most instances, the cost of medication remained the same across different dose levels. All costs were calculated from the perspective of a single public payer (i.e., British Columbia Ministry of Health). Costs were adjusted using the Canadian Consumer Price Index for Health and are expressed in 2022 Canadian dollars ($).128 3.2.6.3 Utilities The same baseline utility for chronic HF was applied to the stable state (S) regardless of the patientâs current therapy step/walk. The utilities associated with stable HFrEF, hospitalized patients with HF and disutility due to an adverse event were taken from previous economic evaluations and studies that derived these values from patients with the relevant adverse events.104â108,129 For each health state, disutility was subtracted from the baseline utility. Utilities over different periods (i.e., 1-year) were converted to a 1-week period. 3.2.7 Analysis 3.2.7.1 Compare the benefit-harm outcomes We quantified and compared the following outcomes of interest for each comparator: Quality adjusted life years (QALYs), life years gained, number of HFH and number of events for each adverse event. A discount rate for QALYs was applied at 1.5% per annum in line with guideline recommendations.130 65 3.2.7.2 Compare the cost-utility outcomes The cost-utility outcomes included the incremental cost-effectiveness ratio (ICER) and the net monetary benefit (NMB). For multiple comparators, we conducted a sequential analysis of cost-effectiveness following the principle of extended dominance.131 A publicly-funded health care payer perspective (i.e., the British Columbia Ministry of Health) was used over a lifetime horizon with a half-cycle correction. This perspective is recommended by Canadian Agency for Drugs and Technologies in Health (CADTH) guidelines, and therefore only direct costs incurred by the public payer were considered, assuming all therapies were covered without restriction or copay.130 CADTH does not formally state a willingness-to-pay (WTP) threshold, thus a WTP of $50,000/QALY was chosen for this project.132 Similarly, a discount rate for cost of 1.5% per annum was applied.130 3.2.7.3 Variability and uncertainty A probabilistic sensitivity analysis (PSA) using a 2nd order Monte Carlo simulation of 1,000 samples, on top of the existing 10,000 microsimulation trials, was used to emulate the uncertainty in individual model parameters and generate a distribution of expected costs and QALYs. Log-normal distributions were used for all ratios, beta distributions for probabilities and utilities, and gamma distributions for all costs. The PSA results were presented as a cost-effectiveness acceptability curve (CEAC). The x-axis indicated the WTP range ($0 to $100,000/QALY), while the y-axis represented the proportion (%) of samples where a profile having the highest NMB, indicating the most cost-effective strategy (i.e., being the most optimal choice) at that particular WTP. The profile that was most likely to be cost-effective at a certain WTP would have its curve on top of the others. 66 For one-way sensitivity analyses, we varied a single input parameter at a time and recorded the change in incremental cost per QALY. Variables for which 95% confidence intervals were not available were modelled with wide distributions (± 50% of the point estimate), while discount rate was varied from 0% to 3%.130 For both the probabilistic and one-way sensitivity analysis, the most cost-effective profile was directly compared to the second most cost-effective profile, and the profile representing the traditional sequencing strategy (Profile 1a). Two scenario analyses were done: the one scenario assumed that medications adjustment ended after 3 months (13 cycles; Scenario 1), and the second scenario assumed that a medication was not effective until the target dose was achieved (i.e., sub-target doses were ineffective; Scenario 2). Table C1 (Appendix C) presents the variables and their uncertainty ranges considered for one-way sensitivity analysis. Table C2 (Appendix C) shows the differences between scenarios. 3.2.7.4 Model validation We consulted with clinicians to review the model's structure, data sources, assumptions, and results for face validity. We also conducted internal validity checks by performing trace analysis, which tracked individual events and their timing, and running tests to ensure that the model produced expected outputs. Furthermore, to ensure the accuracy of our model's simulations, we incorporated an "untreated" group to replicate the placebo group from the SOLVD trial. By comparing the results of our model to those of the trial, we validated the model's ability to accurately simulate the study conditions and outcomes. Finally, we conducted external validation by narratively comparing and discussing the model's results with those of other models and estimation studies. 67 3.3 Results 3.3.1 Benefit-harm comparison of proposed sequencing strategies Table C3 provides a comprehensive summary of the benefit and harm outcomes for the simulated patient across all sequencing strategy profiles. The visualization of these outcomes can be observed in Figure 3.4 to Figure 3.10. The results were averaged over a sample size of 10,000 simulated patients (i.e., trials of microsimulation). Compared to the âuntreatedâ group, the sequencing strategies (Profiles 1a [1-medication âTraditionalâ initiation] to Profile 6b [4-medication âSimultaneousâ initiation]) increased QALYs (5.370-5.541 QALYs), increased life expectancy (10.495-10.812 years), and reduced HFH (0.394-0.401 events) on average per patient over their lifetime. However, these strategies also resulted in additional adverse events, including bradycardia (0.026-0.029 events), hypotension (0.057-0.068 events), hyperkalemia (0.0046-0.0051 events), and renal impairment (0.0594-0.0467 events) on average per patient over the 1-year adjustment period. Of the sequencing strategies, Profile 6b provided the greatest QALYs (9.055) and life years (16.597 years), followed by Profiles 6a, Profile 5b (3-medication âClusterâ initiation), and Profile 3b (2-medication [SGLT2I & BB] âRapidâ initiation). These 4 strategies had similar numbers of adverse events except for Profile 3b, which had fewer hypotension events (0.675 events per patient, versus range 0.680-0.682 with others). Profiles 2a (1-medication [SGLT2I] initiation) and 2b had the lowest HFH (2.118 events and 2.126 events per patient respectively, versus range 2.129 â 2.137 with others), and Profile 2a resulted in the fewest number of adverse events related to bradycardia (0.232 events per patient) and renal impairment (0.447 events per patient). Profile 1a had the fewest events of hypotension and hyperkalemia, but also had the lowest QALYs and life years, as well as the highest number of HFH (2.137 events per patient) and renal impairment (0.594 events per patient). 68 Figure 3.4 Benefit-harm analysis - QALYs Figure 3.5 Benefit-harm analysis - Life years 012345678910"Untreated" Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6QALYsVersion a Version b024681012141618"Untreated" Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6Life yearsVersion a Version b69 Figure 3.6 Benefit-harm analysis - HFH Figure 3.7 Benefit-harm analysis â Bradycardia (1-year medication adjustment period) 1.922.12.22.32.42.52.6"Untreated" Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6HFH eventsVersion a Version b00.0050.010.0150.020.0250.030.035Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6Bradycardia eventsVersion a Version b70 Figure 3.8 Benefit-harm analysis â Hypotension (1-year medication adjustment period) Figure 3.9 Benefit-harm analysis â Hyperkalemia (1-year medication adjustment period) 00.010.020.030.040.050.060.070.08Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6Hypotension eventsVersion a Version b00.0010.0020.0030.0040.0050.006Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6Hyperkalemia events Version a Version b71 Figure 3.10 Benefit-harm analysis â Renal Impairment (1-year medication adjustment period) 3.3.2 Cost-utility comparison of proposed sequencing strategies Table 3.2 displays the results of a cost-utility analysis based on microsimulations of 10,000 patients at a WTP of $50,000/QALY. Compared to Profile 1a, all other sequencing profiles resulted in a greater incremental NMB ($1,557-$6,099). Profile 6a provided the highest NMB ($369,277), followed by Profile 4a ($369,135) and Profile 5a ($369,083), whereas Profile 1a had the lowest NMB ($363,178). Notably, profile versions with more frequent medication adjustments (i.e., Version b) often exhibited higher cost, attributed to their more frequent clinician reimbursement, and higher QALYs compared to Version a. Although the more intensive profiles may offer potential benefits in terms of clinical outcomes, their higher costs offset some of their advantages, resulting in a slightly lower incremental NMB. It should be noted that the magnitudes of the variations in costs, QALYs, and 00.010.020.030.040.050.060.07Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6Renal impairment eventsVersion a Version b72 as a result NMB, were relatively small, and there were considerable overlaps among all the sequencing profiles 95% confidence interval. Taking Profile 1a, which represents the traditional sequencing strategy, as the base, we observed that the 95% confidence intervals for both QALYs, costs, as well as NMB overlapped with those of all other profiles, including Profile 6a and Profile 6b. Table 3.3 shows the cost-effectiveness ranking of the âuntreatedâ group and all sequencing strategy profiles, following the extended dominance principle, with a visual representation in Figure 3.11. Profiles 1a, 3a, 6a and 6b were undominated strategies with sequential ICERs of $8,992, $13,742, $23,118, and $753,530 respectively. With a WTP of $50,000/QALY, Profile 6a was the most cost-effective since it is the strategy with the highest sequential ICER while below the WTP, which aligned with the NMB results. 73 Table 3.2 Cost-utility analysis â Base scenario Base Scenario (Deterministic) Mean values per 10,000 patients/trials NMB 95% Lower Bound 95% Upper Bound Incremental NMB* Cost 95% Lower Bound 95% Upper Bound QALYs 95% Lower Bound 95% Upper Bound Profile 1a 363,177.99 358,100.11 368,255.87 - 81,008.36 79,772.39 82,244.32 8.88 8.76 9.01 Profile 1b 365,293.42 360,238.79 370,348.06 2,115.44 83,077.24 81,843.33 84,311.14 8.97 8.84 9.09 Profile 2a 364,735.07 359,680.31 369,789.82 1,557.08 82,211.71 80,979.50 83,443.92 8.94 8.81 9.06 Profile 2b 366,487.49 361,443.92 371,531.05 3,309.50 83,829.22 82,597.03 85,061.42 9.01 8.88 9.13 Profile 3a 369,072.24 364,039.23 374,105.25 5,894.25 83,242.41 82,013.14 84,471.68 9.05 8.92 9.17 Profile 3b 368,322.93 363,290.93 373,354.93 5,144.94 84,275.25 83,045.50 85,505.00 9.05 8.93 9.18 Profile 4a 369,134.84 364,099.36 374,170.33 5,956.85 83,332.21 82,102.36 84,562.06 9.05 8.93 9.17 Profile 4b 368,183.74 363,151.04 373,216.44 5,005.75 84,293.95 83,064.11 85,523.79 9.05 8.93 9.17 Profile 5a 369,082.78 364,049.36 374,116.20 5,904.79 83,382.09 82,152.84 84,611.33 9.05 8.93 9.17 Profile 5b 368,263.95 363,232.26 373,295.64 5,085.96 84,348.77 83,119.11 85,578.43 9.05 8.93 9.18 Profile 6a 369,277.36 364,244.49 374,310.22 6,099.37 83,418.82 82,189.53 84,648.11 9.05 8.93 9.18 Profile 6b 368,383.86 363,352.12 373,415.59 5,205.87 84,375.82 83,145.98 85,605.66 9.06 8.93 9.18 *Compare to profile 1a 74 Table 3.3 Cost-effectiveness ranking â Base scenario Category Dominance Strategy Cost ÎCost QALYs ÎQALYs ICER NMB Excluding dominated undominated âUntreatedâ 32,726.92 3.51 142,994.49 Excluding dominated undominated Profile 1a 81,008.36 48,281.44 8.88 5.37 8,992.13 363,177.99 Excluding dominated undominated Profile 3a 83,242.41 2,234.06 9.05 0.16 13,742.45 369,072.24 Excluding dominated undominated Profile 6a 83,418.82 176.41 9.05 0.01 23,118.47 369,277.36 Excluding dominated undominated Profile 6b 84,375.82 957.00 9.06 0.00 753,529.90 368,383.86 All undominated âUntreatedâ 32,726.92 3.51 142,994.49 All undominated Profile 1a 81,008.36 48,281.44 8.88 5.37 8,992.13 363,177.99 All ext. dominated Profile 2a 82,211.71 1,203.36 8.94 0.06 21,796.51 364,735.07 All ext. dominated Profile 1b 83,077.24 865.53 8.97 0.03 30,393.11 365,293.42 All undominated Profile 3a 83,242.41 2,234.06 9.05 0.16 13,742.45 369,072.24 All ext. dominated Profile 4a 83,332.21 89.80 9.05 0.00 29,460.02 369,134.84 All abs. dominated Profile 5a 83,382.09 49.88 9.05 0.00 -1,141,187.54 369,082.78 All undominated Profile 6a 83,418.82 176.41 9.05 0.01 23,118.47 369,277.36 All abs. dominated Profile 2b 83,829.22 410.41 9.01 -0.05 -8,623.91 366,487.49 All abs. dominated Profile 3b 84,275.25 856.43 9.05 0.00 -436,975.61 368,322.93 All abs. dominated Profile 4b 84,293.95 875.13 9.05 0.00 -200,273.79 368,183.74 All abs. dominated Profile 5b 84,348.77 929.95 9.05 0.00 -557,153.42 368,263.95 All undominated Profile 6b 84,375.82 957.00 9.06 0.00 753,529.90 368,383.86 75 Figure 3.11 Cost-effectiveness plane This graph shows the cost-effectiveness plane. Following the principle of extended dominance, excluding the âuntreatedâ group, there are 4 additional undominated profiles. The line connecting the undominated profiles forms the efficiency frontier. All dominated profiles have appeared above the efficiency frontier and have been removed for clarity purposes. To choose the best options within our WTP, we start with the least expensive strategies (at the bottom) and upgrade to the next expensive strategies, as long as the ICER between the two is less than the WTP. Here, to upgrade from Profile 6a to 6b, we need to pay more than our WTP, thus Profile 6a was the most cost-effective.ICER=$23,118 per QALY ICER=$753,259 per QALY ICER=$13,742 per QALY 76 3.3.3 Sensitivity analyses 3.3.3.1 Probabilistic sensitivity analysis (PSA) With a WTP of $50,000/QALY, Profiles 6a, 4a, and 5a, had the highest NMB in 87.90%, 5.40%, and 5.30% of samples, respectively (Table 3.4). Analyses of CEAC for all profiles except the âuntreatedâ group, across different WTP values, showed that Profile 1a was the most likely optimal strategy for a WTP <$14,000/QALY, while Profile 6a was the most likely optimal strategy for a WTP â¥$14,000/QALY, including $50,000/QALY (Figure 3.12). To further explore this observation, we compared Profile 6a versus Profile 1a, Profile 4a and Profile 6b through incremental cost-effectiveness (ICE) scatterplots. The comparison in terms of ICER clearly showed that 6a was more likely to be cost-effective than both Profiles 1a, 4a, and 6b (Figure 3.13, 3.14 and 3.15). 77 Table 3.4 Probabilistic sensitivity analysis â Base Scenario Base Scenario (Probabilistic) Mean values per 1,000 samples & 10,000 patients/trials NMB 95% Lower Bound 95% Upper Bound Cost 95% Lower Bound 95% Upper Bound QALY 95% Lower Bound 95% Upper Bound % Optimal* âUntreatedâ 143,457 142,229 144,684 35,479 34,365 36,593 3.579 3.567 3.590 0.00% Profile 1a 368,965 366,449 371,481 81,604 80,050 83,157 9.011 8.968 9.055 0.10% Profile 1b 370,978 368,426 373,530 83,680 82,102 85,259 9.093 9.049 9.137 0.00% Profile 2a 370,883 368,327 373,439 82,940 81,358 84,522 9.076 9.033 9.120 0.00% Profile 2b 372,027 369,453 374,601 84,365 82,771 85,958 9.128 9.084 9.172 0.00% Profile 3a 374,447 371,862 377,031 83,722 82,124 85,321 9.163 9.119 9.208 1.30% Profile 3b 373,839 371,251 376,427 84,768 83,166 86,370 9.172 9.128 9.217 0.00% Profile 4a 374,664 372,078 377,251 83,817 82,215 85,419 9.170 9.125 9.214 5.40% Profile 4b 373,938 371,348 376,528 84,824 83,220 86,427 9.175 9.131 9.220 0.00% Profile 5a 374,912 372,322 377,501 83,938 82,335 85,542 9.177 9.133 9.221 5.30% Profile 5b 374,062 371,471 376,654 84,891 83,287 86,496 9.179 9.135 9.224 0.00% Profile 6a 375,067 372,476 377,657 83,966 82,362 85,570 9.181 9.136 9.225 87.9% Profile 6b 374,195 371,603 376,787 84,919 83,314 86,524 9.182 9.138 9.227 0.00% * % Optimal at WTP $50,000/QALY 78 Figure 3.12 Cost-effectiveness acceptability curve â Base scenario PSA A cost-effectiveness acceptability curve was generated to visualize the results of the 1,000 samples conducted in the probabilistic sensitivity analysis. The x-axis indicates the WTP range ($0-$100,000/QALY), while the y-axis represents the proportion (%) of samples a profile has the highest NMB, indicating the probability of one profile being the most cost-effective strategy at that particular WTP. The profile that is most likely to be cost-effective at a certain WTP will have its curve on top of the others. 79 Figure 3.13 Incremental effectiveness scatterplot, Profile 6a v. Profile 1a A scatterplot was generated to visualize the 1,000 samples conducted in the probabilistic sensitivity analysis. Each dot on the diagram corresponds to one of the samples, with the dashed line representing the WTP threshold. The x-axis indicates the incremental effectiveness of Profile 6a compared to Profile 1a, while the y-axis represents the incremental cost of Profile 6a relative to Profile 1a. The green dots that lie below the WTP line represent simulations where Profile 6a was more cost-effective (99.9% of samples) or dominant (0% of samples) to Profile 1a. Conversely, the red dots correspond to simulations where Profile 1a was more cost-effective (0.01% of samples) or dominant (0% of samples) to Profile 6a. 80 Figure 3.14 Incremental effectiveness scatterplot, Profile 6a v. Profile 4a A scatterplot was generated to visualize the 1,000 samples conducted in the probabilistic sensitivity analysis. Each dot on the diagram corresponds to one of the samples, with the dashed line representing the WTP threshold. The x-axis indicates the incremental effectiveness of Profile 6a compared to Profile 1a, while the y-axis represents the incremental cost of Profile 6a relative to Profile 4a. The green dots that lie below the WTP line represent simulations where Profile 6a was more cost-effective (91.8% of samples) or dominant (2% of samples) to Profile 4a. Conversely, the red dots correspond to simulations where Profile 4a was more cost-effective (3.9% of samples) or dominant (2.3% of samples) to Profile 6a. 81 Figure 3.15 Incremental effectiveness scatterplot, Profile 6a v. Profile 6b A scatterplot was generated to visualize the 1,000 samples conducted in the probabilistic sensitivity analysis. Each dot on the diagram corresponds to one of the samples, with the dashed line representing the WTP threshold. The x-axis indicates the incremental effectiveness of Profile 6a compared to Profile 1a, while the y-axis represents the incremental cost of Profile 6a relative to Profile 6b. The green dots that lie below the WTP line represent simulations where Profile 6a was more cost-effective (79.6% of samples) or dominant (20.4% of samples) to Profile 6b. Conversely, the red dots correspond to simulations where Profile 6b was more cost-effective (0% of samples) or dominant (0% of samples) to Profile 6a. 82 3.3.3.2 One-way sensitivity analysis The tornado diagrams of the NMB revealed that the discount rate and incidence rate of clinical outcomes, such as mortality and hospitalization, had their greatest impact on NMB, whereas adverse events and costs had minimal impact (Figure 3.16). However, none of the input parameters led to a negative NMB, indicating that analyses were robust at a WTP of $50,000/QALY. The ICER tornado diagram comparing Profile 6a to Profile 1a revealed the HFH rate, HFH cost, mortality rate (follow-up), and discount rate to be the most influential variables on the ICER (Figure 3.17). Conversely, the ICER tornado diagram comparing Profile 6a to Profile 4a (the next best comparators) identified mortality rate (follow-up), HFH cost, HFH rate, and rate of renal impairment as the most influential variables on the ICER (Figure 3.18). Finally, the ICER tornado diagram comparing Profile 6a to Profile 6b identified HFH rate and cost, discount rate, and all-cause-mortality (in-trial) as the most influential variables on the ICER (Figure 3.19). Notably, none of the input parameters led to an ICER that crossed either the WTP of $50,000/QALY or 0, demonstrating the robustness of the base case analysis. 83 Figure 3.16 Tornado diagram â Net monetary benefit A tornado diagram was generated to show the results of a one-way sensitivity analysis of the NMB for a WTP of $50,000/QALY. Variables tested in one-way sensitivity analysis are displayed on the y-axis while the x-axis represents the net monetary benefit, with variables having the widest range for the result with a wider line at the top. Variables are followed by the values of their range considered in the analysis. The most relevant variables in the model were the discount rate, the mortality rate during follow-up and in-trial periods, and HFH rate. The expected NMB of the best comparator (Profile 6a) at the base value is represented by EV. 84 Figure 3.17 Tornado diagram â ICER, Profile 1a vs. Profile 6a A tornado diagram of the incremental cost-effectiveness of Profile 1a (baseline) compared to Profile 6a (comparator). The horizontal bars represent the range of variation for each parameter and indicate its impact on the model calculation. When the blue bar is on the left and the red bar is on the right, an increase in the parameter's value results in an increase in ICER, and vice versa. The expected value of ICER of profile 6b versus profile 1a at the base value is represented by EV. 85 Figure 3.18 Tornado diagram â ICER, Profile 4a vs. Profile 6a A tornado diagram of the incremental cost-effectiveness of Profile 4a (baseline) compared to Profile 6a (comparator). The horizontal bars represent the range of variation for each parameter and indicate its impact on the model calculation. When the blue bar is on the left and the red bar is on the right, an increase in the parameter's value results in an increase in ICER, and vice versa. The expected value of ICER of Profile 6b versus Profile 4a at the base value is represented by EV. 86 Figure 3.19 Tornado diagram â ICER, Profile 6a vs. Profile 6b A tornado diagram of the incremental cost-effectiveness of Profile 6a (baseline) compared to Profile 6b (comparator). The horizontal bars represent the range of variation for each parameter and indicate its impact on the model calculation. When the blue bar is on the left and the red bar is on the right, an increase in the parameter's value results in an increase in ICER, and vice versa. The expected value of ICER of Profile 6b versus Profile 6a at the base value is represented by EV. 87 3.3.3.3 Scenario analyses Tables C4, C5, C6 (Appendix C) provide the benefit-harm analysis, the cost-effectiveness ranking, and probabilistic sensitivity analysis for scenario 1 (i.e., the one assumed that medications adjustment ended after 3 months or 13 cycles). Overall, scenario 1 did not differ significantly from the base scenario, with the exception of Profile 1a. Profile 1a involved a longer sequencing strategy that extended beyond 3 months, resulting in participants only being able to establish a stable regimen for ARNI and BB by the end of the adjustment period, at best. As a result, profile 1a yielded notably fewer benefits and incurred lower costs compared to other profiles, positioning it between the other profiles and the âuntreatedâ group. Additionally, it was worth noting a slight increase in the number of samples where Version b of Profiles 3, 5, and 6 were optimal (cumulative to approximately 8% of samples compared to 0% in the base scenario), accompanied by a corresponding decrease in the preference for Version a. This observation could be attributed to the successful achievement of the target dose of quadruple therapy by most profiles at this stage. The shorter adjustment duration in scenario 1 helped to save additional costs, rendering these profiles more cost-effective in this specific instance. This observation was further supported when comparing the CEAC between the base scenario and scenario 1, as shown in Figure C1 (Appendix C), which demonstrated a gradual increase in the proportion of samples where Profile 6b was deemed optimal as the WTP threshold increased. Table C7, C8, C9 (Appendix C) provide the benefit-harm analysis, the cost-effectiveness ranking, and probabilistic sensitivity analysis for scenario 2 (i.e., the one assumed that a medication was not effective until the target dose was achieved). Given the assumptions made in this scenario, all sequencing profiles were less effective across the board, resulting in a decrease in QALYs due to the increased risk of deaths and HFHs in the first few weeks of treatment when 88 sub-target doses were used. This was particularly noticeable when comparing profiles that involve more frequent medication adjustments (Version b) with those involving less frequent adjustments that resulted in delays to achieving target doses (Version a). The profiles with more frequent adjustments were less impacted by the reduced efficacy of sub-doses, thereby demonstrating higher QALYs and NMB. Analyzing the CEAC for scenario 2, as shown in Figure C2 (Appendix C), Profile 6a was optimal at a WTP range of $15,000-$25,000, whereas Profile 6b emerged as the most cost-effective strategy for a WTP â¥$25,000/QALY, including a WTP of $50,000/QALY. 3.3.3.4 Model validation The âuntreatedâ group yielded a mean and median survival of 5.8 years and 4 years (Inter quartile range: 1.7â8.3), respectively, which is consistent with the median survival of 4.8 years (Inter quartile range: 1.8â10.4) in the placebo arm of SOLVD.110 Regarding external validity, a study by Vaduganathan et al. estimated the treatment effects of comprehensive standard quadruple therapy and found that it increased the projected mean overall survival of a 55-year-old patient by 17.7 years (14.9-20.5) and a 65-year-old patient by 15 years (13.1-16.8).133 In our model, most patients who survived through the medication adjustment periods (achieving an average sequencing walk 50 of at the end of 1 year medications adjustment duration) were on the target dose of standard quadruple therapy. Our model shows that for 60-year-old patients on treatment profiles, the mean survival ranged from 16.3 to 16.6 years, which is consistent with the results from Vaduganathan et al.133 89 3.4 Discussion 3.4.1 Summary of evidence In this microsimulation modeling study of 12 proposed HFrEF quadruple therapy sequencing strategies, we observed that sequencing profiles involving more intensive and more frequent medications adjustment resulted in greater QALYs and life years. While there was a decrease in mean HFH, the results were inconsistent with Profile 2 (1-medication [SGLT2I] initiation strategy) associated with fewest HFH. The trade-offs for better clinical outcomes were higher numbers of adverse events, except for renal impairment where the highest number of events was seen with Profile 1 (1-medication âTraditionalâ initiation strategy). When comparing sequencing profiles with the same frequency of medication adjustments, we found that profiles involving more intense medication adjustments often demonstrated greater cost-effectiveness compared to less intensive medication adjustment profiles. When considering the same sequencing profiles, we found that fortnightly medication adjustments (Version a) were more cost-effective than weekly medication adjustments (Version b). However, it is worth mentioning that in scenario where the medication adjustments were shortened (scenario 1) or when the sub-target dose was less effective (scenario 2), weekly adjustment became more likely to be cost-effective. 3.4.1.1 Benefit-harm outcomes Our study findings indicate that more intensive sequencing profiles with greater frequency of medication adjustments led to an increase in mean life years and QALYs. However, additional gains in QALYs and life years become incremental beyond Profile 3a, with Profile 3 (2-medication [SGLT2I & BB] âRapidâ initiation strategy), Profile 4 (2-medication initiation [ARNI & BB] strategy), Profile 5 (3-medication âClusterâ initiation strategy) and Profile 6 (4-medication âSimultaneousâ initiation strategy) achieved around 9.05 QALYs and 16.59 life 90 years. The differences between the most intensive profile (Profile 6b - A sequencing strategy initiating all medications simultaneously on first visit followed by weekly titrations) and the least intensive profile (Profile 1a â A traditional sequencing strategy initiated and titrated each medication sequentially every fortnight) were found to be only 0.18 QALYs and 0.22 years, which are relatively minor compared to the increase observed from the âuntreatedâ group to Profile 1a, which showed an average gain of 5.37 QALYs and 10.5 life years. The effectiveness of more intensive strategies and frequent medication adjustments in reducing HFH was less consistent. This inconsistency may be attributed to the fact that as patients lived longer due to these strategies, they also had a longer period at risk of HFH. In terms of absolute numbers, Profile 2 demonstrated the greatest reduction in HFH. However, it is important to note that the differences in HFH reduction between profiles were relatively insignificant compared to the mean reduction of 0.24 HFH when comparing profile 1a to the âuntreatedâ group. The more intensive sequencing profiles were found to be associated with a higher total incidence of adverse events, including hypotension, bradycardia, and hyperkalemia, across 10,000 simulated patients. However, similar to the findings for life years and QALYs, the differences in the number of adverse events between the profiles, particularly between Profile 3, Profile 4, Profile 5, and Profile 6, were relatively small. It is worth noting that there was an increase in the number of renal impairment events in profiles that delayed the initiation of SGLT2I (Profiles 1 and 4). This was attributed to the assumptions in our model, where we considered SGLT2I to provide renal protective effects, as supported by the results of systematic reviews.126 However, it was important to note that the majority of the studies included in the systematic reviews had follow-up periods spanning multiple years and, it should be acknowledged that the renal 91 protective effect of SGLT2I was not immediate and typically became apparent after a duration of more than one year. 3.4.1.2 Cost-utility outcomes The more intensive sequencing strategies generally led to higher NMB due to their positive impact on increasing QALYs, although there are some nuances to consider. Specifically, when comparing sequencing profiles with the same frequency of medication adjustments, we observed that profiles involving more intense medication adjustments tended to be more cost-effective compared to less intensive medication adjustment profiles. However, within the same sequencing profiles, we found that fortnightly medication adjustments (Version a) were more cost-effective than weekly medication adjustments (Version b) as the additional costs associated with more frequent medication adjustments partially offset the incremental benefits gained. Consequently, Profile 6a exhibited the highest NMB, followed by Profiles 4a, 5a, and 3a, with Profile 6b trailing behind in terms of NMB, although the incremental benefits were minimal. 3.4.1.3 Sensitivity and scenario analyses Our one-way sensitivity analysis revealed that the results remained robust across a wide range of uncertainty values. Among the factors examined, clinical outcomes rates had the greatest impact on the outcomes, followed by the discount rate, costs, and adverse event rates. In the base scenario, our findings of the probabilistic analysis were consistent with the deterministic analysis. For the same sequencing profiles, medication adjustment every 2 weeks (Version a) were more likely to be cost-effective as they provide the best balance between the benefits and costs. In the scenario analysis, we examined 2 potential scenarios that explore important assumptions and factors affecting the value and conclusions of the study. Scenario 1 aimed to examine the 92 impact of a shorter medication adjustment duration on outcomes, reflecting real-life situations where patients may face challenges in completing the full duration of medication adjustments or be lost to follow-up due to various reasons. This scenario also accounts for resource limitations or the need to reduce follow-up duration for practical considerations. Our findings in this scenario revealed that the outcomes did not change significantly compared to the base scenario. However, we did observe improved cost-effectiveness for the weekly medication adjustment (Version b) compared to fortnightly adjustment (Version a). This improvement in cost-effectiveness could be mainly attributed to the cost savings associated with shorter adjustment times. A significant finding emerged from the traditional strategy involving a fortnightly adjustment period (Profile 1a). Due to the limited time available, patients could only reach the target dose of ARNI and BB, resulting in fewer benefits compared to other strategies. On the other hand, when comparing Profile 1a with the same sequencing strategy but with a weekly medication adjustment (Profile 1b), patients had a better chance of reaching the target dose of all therapies within the allocated time frame. This highlighted the importance of establishing patients on all quadruple therapy to maximize the potential long-term benefits. Additionally, this scenario analysis further supported the advantages of more intensive sequencing profiles. These profiles allowed for a buffer period in case patients are lost to follow-up or experience interruptions in their treatment. By initiating and titrating medications more rapidly, these profiles increased the likelihood of patients reaching the target dose of all therapies, even in the presence of interruptions or delays during the treatment course. In Scenario 2, we conducted an analysis focusing on a critical assumption related to the effect of sub-target doses in our model inputs. To test this assumption, we explored the impact of assuming that patients would not derive any benefits or experience any harm from the treatments 93 until the titration process was fully completed. Essentially, we considered the effect of the target dose to be equivalent to that of a placebo. In this scenario, the results revealed interesting findings. While Profile 6a remained the most likely optimal option within a WTP range of $15,000/QALY-$25,000/QALY, Profile 6b emerged as the most likely optimal option for a WTP above $25,000/QALY. Notably, at a WTP of $50,000/QALY, Profile 6b was found to be optimal in 93.7% of the samples. Furthermore, we noticed that profiles involving faster medication adjustments (Version b) were more likely to be optimal. This finding could be attributed to the assumption that the beneficial impact of medications only becomes apparent once the titration process was completed. As a result, profiles with more frequent adjustments (Version b) were less impacted by this assumption, making them more favorable in terms of cost-effectiveness. This indicated that the more intensive sequencing strategy involving faster medication adjustments also had a higher likelihood of being the most cost-effective option in this scenario. 3.4.2 Strengths Our study's results align with previous modeling studies, while also enhancing them in several key aspects.53,133 Shen et al. modeled different approaches to sequencing the HFrEF standard therapies and provided an estimated number of deaths and hospitalization admissions which could be prevented over 12 months for each strategy.53 Our study improves upon Shen et al. 's study in several ways. Firstly, we model over the patient's entire lifetime, allowing us to capture relevant benefits and harms. Secondly, in addition to clinical outcomes, we incorporate other critical factors into our model, such as adverse events and costs. By utilizing these factors and a medication adjustment algorithm, our model emulates clinical practice where we account for probabilities that some patients might not be able to tolerate a strict dose sequencing strategy. Finally, by quantifying both benefits and harms into utility measures, in combination with the 94 associated monetary costs, our model allowed for a more comprehensive comparison of strategies that are relevant to patients, clinicians, and policymakers. 3.4.3 Limitations The model had some limitations. One of our key assumptions pertained to the connection between sub-target doses and target doses on outcomes. Given the limited data available, which did not indicate no statistically significant differences between various doses commonly used in clinical settings, we adopted the assumption that sub-target doses would produce comparable results to target doses across most therapies and endpoints in our base scenario.71,75,76,78,119,125 To account for the uncertainty of this assumption, we conducted a scenario analysis in which we assumed the effect of sub-target doses to be the same as placebo, in which case the results were even more in favor of more intensive sequencing profiles. Second, we derived adverse event rates from RCTs,113â115 which may have been underestimates because RCTs tend to retain patients who tolerate therapies fairly well by excluding those who do not during run-in phases. Additionally, we recognized that if most of the adverse events were front-loaded during the initiation of therapy, then using the entire trial duration to calculate the rate may have led to an underestimation of the true rates. However, our sensitivity analysis showed that variations in adverse event rates generally had minimal impact on the results. Furthermore, we did not consider the cost of adverse events and assumed that adverse events only lasted for one cycle, given our hypothesis that these events would resolve naturally without requiring intervention. Due to the relatively small number of adverse events, resulting in a limited number of dose-limiting adverse events, we believe that these factors have a minimal impact on the final results. Finally, our model assumed that the effects of each therapy were independent of one another. 95 Previous articles have suggested that certain combinations of therapies may increase or decrease the risk of specific adverse events,24,37 and we did not explicitly attempt to model these effects. 3.5 Conclusion Our study conducted a comprehensive analysis of various profiles representing a broad spectrum of sequencing strategies for HFrEF quadruple therapy. The analysis revealed that more intensive strategies, involving multiple therapy initiations/up-titrations and more frequent medication adjustments, led to a slight rise in QALYs, factoring in benefits such as extended life years, reduced HFH occurrences, and harms such as increased adverse events. However, these differences were clinically insignificant. In terms of cost-effectiveness, under the base scenario, the benefits of more frequent adjustments in medication did not justify the additional expenses for the same profiles. Nonetheless, under the second scenario, where we assume that sub-target doses have no effect, within the same strategy, medication adjustments every week proved to be more cost-effective compared to adjustments every two weeks. Furthermore, under the first scenario, where we shortened the medication adjustment duration to 3 months, we found that longer sequencing strategies, resembling the traditional approach with medication adjustments every two weeks (Profile 1a), led to patients failing to achieve quadruple therapy, resulting in significantly fewer benefits. This emphasizes the importance of prioritizing patients' attainment of quadruple therapy, as it leads to improved outcomes. 96 Chapter 4: Conclusion 4.1 Summary of thesis findings 4.1.1 Identify sequencing strategies for the quadruple therapy The scoping review conducted in Chapter 2 focused on exploring the sequencing strategies for initiating and titrating the 4 medication classes forming the quadruple therapy for HFrEF. Eight articles described 18 alternative sequencing strategies that aim to replace the traditional approach to sequence the HFrEF quadruple therapy. These strategies were analyzed and extracted based on 8 attributes from 2 main categories: attributes related to the prioritization and introduction of medications, and attributes related to the timing and nature of medication adjustments. The scoping review yielded several findings. Firstly, many of the suggested strategies involved initiating two or more medications during the first visit. Secondly, ARNI, BB, and SGLT2I were frequently prioritized by authors of included articles for earlier initiation over MRA, as these medications offer specific advantages that make them favorable choices for early introduction. Thirdly, most strategies emphasized completing the initiation of all medications before focusing on up-titration of existing medications. Lastly, simultaneous adjustment, whether it be initiation or titration, of 2 or more medications during the same visit was a common recommendation. 4.1.2 Categorize sequencing strategies for the quadruple therapy Based on the identified common trends and their underlying rationales of sequencing strategies identified in Chapter 2, âthe number of medications initiated during the first visitâ was the dominant attribute discussed related to the order of medication prioritization, and âthe timing of starting titration relative to completing initiationâ was the dominant attribute related to the timing and characteristics of medication initiation and titration. 97 From these 2 dominant attributes, we proposed a framework of 3 strategy types illustrated using 6 profiles that can be used to classify all sequencing approaches: For strategies involved fewer than 3 medications initiated on the first visit, Type 1 encompasses the traditional approach to sequencing strategies (Profile 1 â One-medication [ACEI/ARB] initiation âtraditionalâ sequencing strategy) and other strategies that strictly prioritize titration over initiation. This feature can be considered the distinctive and prominent factor that sets the traditional approach apart from alternative sequencing strategies. For those seeking a sequencing strategy that deviates minimally from the traditional sequential approach, the strategy described by Shen et al. (Profile 2 â One-medication [SGLT2I] initiation sequencing strategy) could be considered. In this approach, medications are prioritized based on the theoretical completion time of titration.53 The overwhelming popular choice among the identified strategies is to prioritize completing initiation over titration, placing them within Type 2. Two main approaches fitting Type 2 have been suggested in the literature regarding the order of medication prioritization. The first approach gives priority to SGLT2I, with MRA being considered to a lesser extent. The rationale behind this approach lies in the ease of titration, as these medications require one or two steps to reach the target dose. Additionally, SGLT2I can improve tolerability of other medications by providing diuretic effects for BB, reducing hyperkalemia, and improving renal function for MRA and ARNI. This approach is exemplified by the "rapid sequencing" strategy described by Packer et al.,24 McMurray et al.,25,34 Docherty et al.,32 and Lorke et al.54 (Profile 3 â Two-medication [SGLT2I & BB] initiation ârapidâ sequencing strategy). The second approach prioritizes ARNI and BB, primarily due to their established roles as the two medication classes approved for HFrEF, and both medications have demonstrated superior clinical benefits in reducing sudden deaths. This approach is seen in the sequencing strategies described by Sharma et al.33; 98 Silva-Cardoso et al.26 (Profile 4 â Two-medication [ARNI & BB] initiation sequencing strategy). Type 3 comprises strategies where 3 or more medications are initiated on the first visit. In Type 3, initiation takes precedence over titration, and the order of medication introduction becomes irrelevant as all medications are started immediately, or within the first two patient visits. However, the focus shifts to the characteristics of titration for these medications, although detailed descriptions are lacking in the literature. Two examples of sequencing strategies belongs to Type 3 include the âclusterâ sequencing strategy suggested by Howlett et al.29; Miller et al.27; El Hussein et al.36 (Profile 5 â Three-medication initiation âclusterâ sequencing strategy) and âsimultaneousâ sequencing strategy described by Brownell et al.28, Khan et al.31, Greene et al.30, and Tomasoni et al.38 (Profile 6 â Four-medication initiation âsimultaneousâ sequencing strategy). 4.1.3 Modeling study overview In Chapter 3, we conducted a microsimulation model to compare the profiles which represents different approaches to sequence HFrEF quadruple therapy, in terms of benefit-harm and cost-utility. We also examined potential factors that could impact the outcomes of different sequencing profiles. To begin, we created 2 versions of each profile: Version a, which involved medication adjustments every 2 weeks, and Version b, which involved adjustments every 1 week. Thus, we can observe that the level of intensity increased as we progressed from Profile 1 to Profile 6. 4.1.4 Benefit-harm of sequencing strategies In terms of benefits, the results aligned with our expectations. The more intensive sequencing strategies, which initiated and titrated more medications simultaneously within shorter time intervals, led to a reduction in mortality risk and an increase in patient life years. However, the 99 results were less consistent for HFH. Although more intensive strategies reduced the time patients spent at greater risk for HFH, the absolute number of HFH events did not improve significantly. This was due to the fact that as patients lived longer, the duration of time at risk also increased, offsetting the reduction in HFH events. Nevertheless, it was important to note that the absolute differences between profiles were relatively small compared to the improvement achieved by implementing any treatment. Turning to harms, we observed an increased number of adverse events during the medication adjustment periods with the more intensive sequencing profiles. The most common adverse event was hypotension, followed by renal impairment, bradycardia, and hyperkalemia. We noted a higher rate of renal impairment adverse events in profiles that delayed the initiation of SGLT2I. However, overall, the number of adverse events was low, with an average expectation of encountering approximately 1 transient adverse event over the entire adjustment period. 4.1.5 Cost-utility of sequencing strategies We observed a minor improvement in QALYs and NMB for more intensive sequencing strategies, at least given the same adjustment frequency; however, differences were small and did not reach clinical significance. This trend held true across a range of parameters during one-way sensitivity analysis and scenario analyses. Regarding the duration of medication adjustments, we found that profiles involving fortnightly adjustments were more cost-effective compared to those with weekly adjustments. However, it was important to consider specific scenarios where the effectiveness of sub-target doses or the duration of medication adjustment was shortened. In such scenarios, more frequent medication adjustments were likely to become the more optimal option for the same profile. 100 4.2 Contribution and implications Our studies fill gaps in the literature by identifying and categorizing different approaches to sequencing quadruple therapy for HFrEF and modeling their impact on important outcomes such as mortality and HFH. While previous modeling studies have explored clinical outcomes for HF sequences, our study incorporated key factors relevant to clinical decision-making that have been neglected in prior models, such as costs and adverse events. The microsimulation approach allowed us to leverage patient history within the model and enable medication adjustments based on previous adverse events, making it more closely aligned with clinical practice. In terms of results, we found that the most important factor is to successfully establish patients on quadruple therapy, and the specific ordering of pharmacotherapy may not significantly impact long-term outcomes as long as patients are established on the quadruple therapy within a reasonable timeframe. Compared to the "untreated" group, successfully establishing patients on quadruple therapy with the traditional sequencing strategy and fortnightly adjustments (represented by Profile 1a) provided a minimum of 10.495 additional life years and 5.370 QALYs. This benefit increased up to a maximum of 10.812 additional life years and 5.541 QALYs with simultaneous medication initiation and weekly adjustment (represented by Profile 6b). This finding provides data to support prior commentaries based only on expert opinion,24,25,34 and adds further evidence to the existing knowledge on this topic. Our study also examined the cost of medication adjustments and found that it did not change the overall conclusions. While a weekly adjustment interval was not more optimal than a fortnightly interval in the base scenario, there are several assumptions or settings that could impact this conclusion. For example, if the sub-target dose is less effective, or if the duration of medication adjustments can be reduced after patients are established on quadruple therapy, especially when utilizing 101 faster sequencing strategies, it could help offset the cost implications. Therefore, the focus should be on strategies to titrate medications faster, improve tolerability, and enhance acceptability. 4.3 Strengths and limitations 4.3.1 Strengths of the scoping review A strength of this scoping review is that it examined the actual recommendations found within the literature, shedding light on the sequencing strategies that practitioners might opt to implement in practice. To our knowledge, this is the first scoping review that specifically focuses on this topic. Moreover, we utilized a systematic approach to identify and categorize sequencing strategies relevant to the HFrEF quadruple therapy. We extracted insights and recurring trends from the identified strategies using 2 separate categories, comprising 8 distinct attributes. By discerning these trends, we introduced a comprehensive framework to classify strategies into 3 distinct types that encompasses all potential approaches to sequencing quadruple therapy. 4.3.2 Limitations of the scoping review The potential to generalize and interpret the results of this review is constrained by the quality of the input data. A notable limitation of the scoping review pertains to the absence of standardized data and a uniform format across the included articles. This lack of standardization poses challenges in consolidating and comparing information across the articles, hindering the assessment of the strengths and weaknesses of different sequencing strategies. Additionally, the inclusion of older articles introduces the risk of overlooking the latest evidence or relying on outdated information, potentially leading to biased conclusions. Throughout our analysis of the identified sequencing strategies, we observed a lack of detailed explanations for the chosen attributes. Many articles presented general justifications for deviating 102 from the traditional sequencing strategy without providing specific reasoning behind their choices of specific attributes. They often relied on broader evidence of treatment benefits or interactions between medication classes to support their chosen approaches, which itself could potentially justify variations in other attributes or multiple approaches. The absence of explicit recommendations may also stem from a lack of available data, leading authors to rely on their own expertise, preferences, and assumptions regarding risks, benefits, and resource constraints. The lack of standardized format as well as detailed rationales for the choice of specific attributes requires us to exercise some of our own judgment in extracting, synthesizing, and interpreting the findings. We acknowledge that this could potentially introduce bias and impact the outcomes. To mitigate this risk, alongside our systematic approach to identifying and categorizing sequencing strategies as previously mentioned, we have taken steps to enhance transparency through thorough documentation and clear justifications for our interpretations. 4.3.3 Strengths of modeling study Our modeling study improved upon previous studies by Shen et al. and Vaduganathan et al. in a number of ways.53,133 One key improvement was that we modeled across the patient's entire lifetime, enabling us to evaluate the long-term impact of different sequencing profiles on their health outcomes. Furthermore, we took into account not only treatment effectiveness but also incorporated additional factors such as adverse events and costs, rendering our comparison of sequencing profiles more comprehensive and reflective of real-world clinical decision-making. Additionally, our modeling study integrated a medication adjustment algorithm that considers adverse events, thereby emulating clinical practices where the speed and intensity of a sequencing process can be adjusted based on a patient's tolerability. This added realism enhances the applicability of our findings to real-world scenarios. 103 4.3.4 Limitations of modeling study Our study also has limitations inherent in modeling studies. Firstly, our analysis relied on different data sources, and the validity of the results is contingent upon the availability and accuracy of the data used. Additionally, the modeling process involved simplifications and assumptions to simulate real-world scenarios, which may not fully reflect the complexity and variability of clinical practice. Furthermore, the generalizability of the findings to specific patient populations may be limited, as the model is based on aggregated data and may not fully capture individual patient characteristics and variations. 4.4 Future research directions While our scoping review and modeling study provide important insights, there is still much to explore in this field. The current iteration of our model is relatively straightforward and offers ample room for expansion and refinement. Firstly, there's a valuable opportunity to increase the model's accuracy and reliability by conducting studies to obtain higher quality input and refine our assumptions. For instance, one avenue could involve conducting research to evaluate patient preferences. By doing so, we can obtain a more accurate assessment of patient preferences and utilities, ultimately enhancing the model's predictive capabilities. Secondly, the current model lacks consideration for individual patient characteristics. We can broaden its scope by factoring in patient-specific attributes, such as age, gender, NYHA classes, and other subgroup characteristics, and their influence on outcomes. This expanded representation would lend greater relevance to our simulations. Thirdly, we can enhance the model's applicability by incorporating additional decision factors, such as blood pressure and laboratory values, into the medication adjustment algorithm. This expanded approach will enable a broader range of actions to be considered, resulting in a closer alignment of the model with real-world clinical practice. 104 Through this adjustment, we aim to accurately mirror the intricate decision-making process that healthcare professionals encounter in their actual clinical settings. Our sensitivity analyses have demonstrated the robustness of our study results, effectively addressing a wide range of uncertainties, including potential variations in the cost of medication adjustment. While the efficacy and associated risks are well-established, there's a clear opportunity to adjust the cost aspect. A promising avenue for future investigations includes assessing the cost-effectiveness and practicality of supplementary clinical services, with a pronounced emphasis on monitoring programs managed by pharmacists or nurses. These programs could serve as a pivotal component in both managing potential adverse events and facilitating more frequent therapy adjustments for HFrEF patients. This exploration extends beyond the immediate practitioners involved; it encompasses the mode of delivery as well. The essential elements encompass identifying the optimal approach for implementing these sequencing strategies, determining the most suitable individuals to oversee them, and devising strategies to minimize implementation costs, leveraging innovative solutions, such as the use of online platforms. 4.5 Conclusion The findings from the scoping review revealed a notable trend in the selection of attributes from the identified strategies, with a primary emphasis on expediting the initiation of quadruple therapy. Two key attributes played a significant role in influencing this trend: the number of medications initiated during the first visit and the decision to prioritize initiation or titration. Utilizing these attributes, we developed a comprehensive framework to categorize sequencing strategies into 3 distinct types, and for each type, we proposed 2 strategy profiles to effectively represent the approaches. 105 Utilizing microsimulation, this study compares various profiles to shed light on the clinical and economic implications of different sequencing strategies for quadruple therapy. The analysis reveals that more intensive strategies offer additional benefits, such as increased survival rates and reduced hospitalizations, accompanied by an increase in adverse events and costs. Combining all factors, the incremental cost-effectiveness among the different strategies is minimal, making it challenging to identify a single dominant sequencing strategy, though slightly favor the more intensive strategies. This uncertainty emphasizes the significance of considering various assumptions that could influence the selection of the optimal strategy. In the base scenario, the "simultaneous" initiation strategy with fortnightly adjustment (Profile 6a) appears to be the most cost-effective. However, under scenario 2, which assumes sub-target doses are ineffective, strategies involving weekly adjustments become more promising compared to fortnightly adjustments. Consequently, the "simultaneous" initiation strategy with weekly adjustment (Profile 6b) emerges as having the highest probability of being the most cost-effective. Further analysis under scenario 1, where medication adjustment ceases after three months, indicates that the "traditional" strategy with fortnightly adjustment (Profile 1a) fails to achieve complete initiation, resulting in significantly fewer benefits. This underscores the importance of prioritizing patients to achieve quadruple therapy, as it leads to better outcomes. Ultimately, successfully establishing patients on quadruple therapy remains the critical factor for optimal long-term results. In conclusion, the literature suggests a wide range of approaches to sequencing quadruple therapy for HFrEF patients, with a notable preference for prioritizing the rapid sequencing of HFrEF quadruple therapy. However, the analysis revealed that the incremental cost-effectiveness among the different strategies was minimal, despite being presented. The crucial factor 106 determining optimal outcomes was the successful establishment of patients on quadruple therapy within a reasonable timeframe. 107 References 1. Bozkurt B, Coats AJ, Tsutsui H, et al. Universal Definition and Classification of Heart Failure: A Report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure. Journal of Cardiac Failure. 2021;27(4):387-413. doi:10.1016/j.cardfail.2021.01.022 2. Public Health Agency of Canada. Canadian Chronic Disease Surveillance System (CCDSS). Accessed May 1, 2022. https://health-infobase.canada.ca/ccdss/data-tool/ 3. Hospital Stays in Canada | CIHI. Accessed April 15, 2022. https://www.cihi.ca/en/hospital-stays-in-canada 4. Poon S, Leis B, Lambert L, et al. The State of Heart Failure Care in Canada: Minimal Improvement in Readmissions Over Time Despite an Increased Number of Evidence-Based Therapies. CJC Open. 2022;4(8):667-675. doi:10.1016/j.cjco.2022.04.011 5. Ottawa: Heart & Stroke Foundation; 2017. 2016 Report on the Health of Canadians: The Burden of Heart Failure. Accessed November 24, 2021. https://www.heartandstroke.ca/-/media/pdf-files/canada/2017-heart-month/heartandstroke-reportonhealth-2016.ashx?la=en 6. Ezekowitz JA, OâMeara E, McDonald MA, et al. 2017 Comprehensive Update of the Canadian Cardiovascular Society Guidelines for the Management of Heart Failure. Canadian Journal of Cardiology. 2017;33(11):1342-1433. doi:10.1016/j.cjca.2017.08.022 7. McDonald M, Virani S, Chan M, et al. CCS/CHFS Heart Failure Guidelines Update: Defining a New Pharmacologic Standard of Care for Heart Failure With Reduced Ejection Fraction. Canadian Journal of Cardiology. 2021;37(4):531-546. doi:10.1016/j.cjca.2021.01.017 8. McDonagh TA, Metra M, Adamo M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failureDeveloped by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) With the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J. 2021;42(36):3599-3726. doi:10.1093/eurheartj/ehab368 9. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. doi:10.1161/CIR.0000000000001063 10. Maddox TM, Januzzi JL, Allen LA, et al. 2021 Update to the 2017 ACC Expert Consensus Decision Pathway for Optimization of Heart Failure Treatment: Answers to 10 Pivotal Issues About Heart Failure With Reduced Ejection Fraction: A Report of the American College of Cardiology Solution Set Oversight Committee. Journal of the American College of Cardiology. 2021;77(6):772-810. doi:10.1016/j.jacc.2020.11.022 108 11. Yancy CW, Jessup M, Bozkurt B, et al. 2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Failure Society of America. Circulation. 2017;136(6):e137-e161. doi:10.1161/CIR.0000000000000509 12. Zannad F, Ferreira JP, Pocock SJ, et al. SGLT2 inhibitors in patients with heart failure with reduced ejection fraction: a meta-analysis of the EMPEROR-Reduced and DAPA-HF trials. Lancet. 2020;396(10254):819-829. doi:10.1016/S0140-6736(20)31824-9 13. Bhatt AS, Vaduganathan M, Claggett BL, et al. Effect of sacubitril/valsartan vs. enalapril on changes in heart failure therapies over time: the PARADIGM-HF trial. Eur J Heart Fail. 2021;23(9):1518-1524. doi:10.1002/ejhf.2259 14. Gracia E, Hamid A, Butler J. Timely Management of New-Onset Heart Failure. Circulation. 2019;140(8):621-623. doi:10.1161/CIRCULATIONAHA.118.035452 15. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. European Heart Journal. 2016;37(27):2129-2200. doi:10.1093/eurheartj/ehw128 16. Allen LA, Fang JC. Goldilocks Dilemma of Dose Titration in Heart Failure With Reduced Ejection Fraction. Circulation: Heart Failure. 2017;10(8):e004406. doi:10.1161/CIRCHEARTFAILURE.117.004406 17. Lonn E. Dose response of ACE inhibitors: implications of the SECURE trial. Curr Control Trials Cardiovasc Med. 2001;2(4):155-159. doi:10.1186/cvm-2-4-155 18. Bhatt AS, DeVore AD, DeWald TA, Swedberg K, Mentz RJ. Achieving a Maximally Tolerated β-Blocker Dose in Heart Failure Patients: Is There Room for Improvement? Journal of the American College of Cardiology. 2017;69(20):2542-2550. doi:10.1016/j.jacc.2017.03.563 19. Basile JN. Titration of beta-blockers in heart failure. How to maximize benefit while minimizing adverse events. Postgrad Med. 2003;113(3):63-70; quiz 3. doi:10.3810/pgm.2003.03.1389 20. Ouwerkerk W, Voors AA, Anker SD, et al. Determinants and clinical outcome of uptitration of ACE-inhibitors and beta-blockers in patients with heart failure: a prospective European study. European Heart Journal. 2017;38(24):1883-1890. doi:10.1093/eurheartj/ehx026 21. Greene SJ, Fonarow GC, DeVore AD, et al. Titration of Medical Therapy for Heart Failure With Reduced Ejection Fraction. Journal of the American College of Cardiology. 2019;73(19):2365-2383. doi:10.1016/j.jacc.2019.02.015 109 22. Fiuzat M, Ezekowitz J, Alemayehu W, et al. Assessment of Limitations to Optimization of Guideline-Directed Medical Therapy in Heart Failure From the GUIDE-IT Trial: A Secondary Analysis of a Randomized Clinical Trial. JAMA Cardiology. 2020;5(7):757-764. doi:10.1001/jamacardio.2020.0640 23. Miller RJH, Howlett JG, Exner DV, Campbell PM, Grant ADM, Wilton SB. Baseline Functional Class and Therapeutic Efficacy of Common Heart Failure Interventions: A Systematic Review and Meta-analysis. Canadian Journal of Cardiology. 2015;31(6):792-799. doi:10.1016/j.cjca.2014.12.031 24. Packer M, McMurray JJV. Rapid evidence-based sequencing of foundational drugs for heart failure and a reduced ejection fraction. European Journal of Heart Failure. 2021;23(6):882-894. doi:10.1002/ejhf.2149 25. McMurray JJV, Packer M. How Should We Sequence the Treatments for Heart Failure and a Reduced Ejection Fraction? Circulation. 2020;(143):875-877. doi:10.1161/CIRCULATIONAHA.120.052926. 26. Silva-Cardoso J, Fonseca C, Franco F, Morais J, Ferreira J, Brito D. Optimization of heart failure with reduced ejection fraction prognosis-modifying drugs: A 2021 heart failure expert consensus paper. Revista Portuguesa de Cardiologia. 2021;40(12):975-983. doi:10.1016/j.repc.2021.07.009 27. Miller RJH, Howlett JG, Fine N. A Novel Approach to Medical Management of Heart Failure With Reduced Ejection Fraction. Canadian Journal of Cardiology. 2021;37(4):632-643. doi:10.1016/j.cjca.2020.12.028 28. Brownell NK, Ziaeian B, Fonarow GC. The Gap to Fill: Rationale for Rapid Initiation and Optimal Titration of Comprehensive Disease-modifying Medical Therapy for Heart Failure with Reduced Ejection Fraction. Card Fail Rev . 2021;7(e18). doi:10.15420/cfr.2021.18. 29. Howlett JG. The time has finally come to prioritize drug initiation before dose titration for patients with heart failure and reduced ejection fraction. European Journal of Heart Failure. 2020;22(8):1483-1485. doi:10.1002/ejhf.1936 30. Greene SJ, Butler J, Fonarow GC. Simultaneous or Rapid Sequence Initiation of Quadruple Medical Therapy for Heart FailureâOptimizing Therapy With the Need for Speed. JAMA Cardiology. 2021;6(7):743-744. doi:10.1001/jamacardio.2021.0496 31. Khan MS, Butler J, Greene SJ. Simultaneous or rapid sequence initiation of medical therapies for heart failure: seeking to avoid the case of âtoo little, too late.â European Journal of Heart Failure. 2021;23(9):1514-1517. doi:10.1002/ejhf.2311 32. Docherty KF, McMurray JJV. Foundational drugs for HFrEF: the growing evidence for a rapid sequencing strategy. Br J Cardiol. 2022;29:12-15. doi:10.5837/bjc.2022.002 110 33. Sharma A, Verma S, Bhatt DL, et al. Optimizing Foundational Therapies in Patients With HFrEF: How Do We Translate These Findings Into Clinical Care? JACC: Basic to Translational Science. Published online March 2, 2022. doi:10.1016/j.jacbts.2021.10.018 34. McMurray JJV, Docherty KF. Insights into foundational therapies for heart failure with reduced ejection fraction. Clin Cardiol. 2022;45 Suppl 1:S26-S30. doi:10.1002/clc.23847 35. Straw S, McGinlay M, Witte KK. Four pillars of heart failure: contemporary pharmacological therapy for heart failure with reduced ejection fraction. Open Heart. 2021;8(1):e001585. doi:10.1136/openhrt-2021-001585 36. Hussein MTE, Negash S. Cluster Scheme Approach to Foundational Heart Failure With Reduced Ejection Fraction Therapy. The Journal for Nurse Practitioners. 2022;18(6):628-635. doi:10.1016/j.nurpra.2022.02.009 37. Di Lenarda A, Di Tano G, Cipriani M, et al. [ANMCO Position paper: Double, triple or quadruple therapy for heart failure with reduced ejection fraction. Current evidence and new strategies]. G Ital Cardiol (Rome). 2021;22(10):861-868. doi:10.1714/3666.36518 38. Tomasoni D, Fonarow GC, Adamo M, et al. Sodium-glucose co-transporter 2 inhibitors as an early, first-line therapy in patients with heart failure and reduced ejection fraction. Eur J Heart Fail. 2022;24(3):431-441. doi:10.1002/ejhf.2397 39. Mebazaa A, Davison B, Chioncel O, et al. Safety, tolerability and efficacy of up-titration of guideline-directed medical therapies for acute heart failure (STRONG-HF): a multinational, open-label, randomised, trial. The Lancet. 2022;400(10367):1938-1952. doi:10.1016/S0140-6736(22)02076-1 40. Cao VFS, Cowley E, Koshman SL, MacGillivray J, Sidsworth M, Turgeon RD. Pharmacist-led optimization of heart failure medications: A systematic review. JACCP: JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY. 2021;4(7):862-870. doi:10.1002/jac5.1450 41. Gandhi S, Mosleh W, Sharma UC, Demers C, Farkouh ME, Schwalm JD. Multidisciplinary Heart Failure Clinics Are Associated With Lower Heart Failure Hospitalization and Mortality: Systematic Review and Meta-analysis. Can J Cardiol. 2017;33(10):1237-1244. doi:10.1016/j.cjca.2017.05.011 42. Savarese G, Bodegard J, Norhammar A, et al. Heart failure drug titration, discontinuation, mortality and heart failure hospitalization risk: a multinational observational study (US, UK and Sweden). Eur J Heart Fail. 2021;23(9):1499-1511. doi:10.1002/ejhf.2271 43. Savarese G, Kishi T, Vardeny O, et al. Heart Failure Drug TreatmentâInertia, Titration, and Discontinuation. JACC: Heart Failure. 0(0). doi:10.1016/j.jchf.2022.08.009 111 44. Khan MS, Butler J, Greene SJ. The real world of de novo heart failure: the next frontier for heart failure clinical trials? European Journal of Heart Failure. 2020;22(10):1786-1789. doi:10.1002/ejhf.1844 45. Yeung DF, Boom NK, Guo H, Lee DS, Schultz SE, Tu JV. Trends in the incidence and outcomes of heart failure in Ontario, Canada: 1997 to 2007. CMAJ. 2012;184(14):E765-E773. doi:10.1503/cmaj.111958 46. Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology. 2018;18(1):143. doi:10.1186/s12874-018-0611-x 47. Chapter 11: Scoping reviews - JBI Manual for Evidence Synthesis - JBI Global Wiki. Accessed April 26, 2022. https://jbi-global-wiki.refined.site/space/MANUAL/4687342/Chapter+11%3A+Scoping+reviews 48. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation | Annals of Internal Medicine. Accessed April 26, 2022. https://www.acpjournals.org/doi/10.7326/M18-0850 49. Scambler G. Sociology as Applied to Medicine E-Book. Elsevier Health Sciences; 2008. 50. McMurray JJV, Solomon SD, Inzucchi SE, et al. Dapagliflozin in Patients with Heart Failure and Reduced Ejection Fraction. N Engl J Med. 2019;381(21):1995-2008. doi:10.1056/NEJMoa1911303 51. Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org. 52. Chapter 5: Collecting data. Accessed October 20, 2022. https://training.cochrane.org/handbook/current/chapter-05 53. Shen L, Jhund PS, Docherty KF, et al. Accelerated and personalized therapy for heart failure with reduced ejection fraction. European Heart Journal. Published online April 25, 2022:ehac210. doi:10.1093/eurheartj/ehac210 54. Lokre A, Vala DR. Therapy of heart failure (heart failure with reduced ejection fraction): New sequencing (drug therapy). JOURNAL OF INDIAN COLLEGE OF CARDIOLOGY. 2021;11(2):44. doi:10.4103/jicc.jicc_8_21 55. Fauvel C, Bonnet G, Mullens W, et al. Sequencing and titrating approach of therapy in heart failure with reduced ejection fraction following the 2021 European Society of Cardiology guidelines: an international cardiology survey. European Journal of Heart Failure. n/a(n/a). doi:10.1002/ejhf.2743 112 56. Sinagra G, Pagura L, Stolfo D, et al. Combining New Classes of Drugs for HFrEF: from Trials to Clinical Practice. Eur J Intern Med. 2021;90:10-15. doi:10.1016/j.ejim.2021.05.017 57. McMurray JJV, Packer M, Desai AS, et al. AngiotensinâNeprilysin Inhibition versus Enalapril in Heart Failure. New England Journal of Medicine. 2014;371(11):993-1004. doi:10.1056/NEJMoa1409077 58. Desai AS, Vardeny O, Claggett B, et al. Reduced Risk of Hyperkalemia During Treatment of Heart Failure With Mineralocorticoid Receptor Antagonists by Use of Sacubitril/Valsartan Compared With Enalapril: A Secondary Analysis of the PARADIGM-HF Trial. JAMA Cardiol. 2017;2(1):79-85. doi:10.1001/jamacardio.2016.4733 59. Feng Y, Yin Y, Deng R, Li H. Renal safety and efficacy of angiotensin receptor-neprilysin inhibitor: A meta-analysis of randomized controlled trials. Journal of Clinical Pharmacy and Therapeutics. 2020;45(6):1235-1243. doi:10.1111/jcpt.13243 60. Rohde LE, Chatterjee NA, Vaduganathan M, et al. Sacubitril/Valsartan and Sudden Cardiac Death According to Implantable Cardioverter-Defibrillator Use and Heart Failure Cause: A PARADIGM-HF Analysis. JACC Heart Fail. 2020;8(10):844-855. doi:10.1016/j.jchf.2020.06.015 61. The Cardiac Insufficiency Bisoprolol Study II (CIBIS-II): a randomised trial. The Lancet. 1999;353(9146):9-13. doi:10.1016/S0140-6736(98)11181-9 62. Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in-Congestive Heart Failure (MERIT-HF). The Lancet. 1999;353(9169):2001-2007. doi:10.1016/S0140-6736(99)04440-2 63. Packer M, Antonopoulos GV, Berlin JA, Chittams J, Konstam MA, Udelson JE. Comparative effects of carvedilol and metoprolol on left ventricular ejection fraction in heart failure: results of a meta-analysis. Am Heart J. 2001;141(6):899-907. doi:10.1067/mhj.2001.115584 64. Park CS, Park JJ, Mebazaa A, et al. Characteristics, Outcomes, and Treatment of Heart Failure With Improved Ejection Fraction. J Am Heart Assoc. 2019;8(6):e011077. doi:10.1161/JAHA.118.011077 65. Packer M, Anker SD, Butler J, et al. Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure. N Engl J Med. 2020;383(15):1413-1424. doi:10.1056/NEJMoa2022190 66. Jhund PS, Solomon SD, Docherty KF, et al. Efficacy of Dapagliflozin on Renal Function and Outcomes in Patients With Heart Failure With Reduced Ejection Fraction. Circulation. 2021;143(4):298-309. doi:10.1161/CIRCULATIONAHA.120.050391 67. Zannad F, Ferreira JP, Pocock SJ, et al. Cardiac and Kidney Benefits of Empagliflozin in Heart Failure Across the Spectrum of Kidney Function: Insights From EMPEROR-Reduced. Circulation. 2021;143(4):310-321. doi:10.1161/CIRCULATIONAHA.120.051685 113 68. Kristensen SL, Docherty KF, Jhund PS, et al. Dapagliflozin reduces the risk of hyperkalaemia in patients with heart failure and reduced ejection fraction: a secondary analysis DAPA-HF. European Heart Journal. 2020;41(Supplement_2):ehaa946.0939. doi:10.1093/ehjci/ehaa946.0939 69. Scholtes RA, Muskiet MHA, van Baar MJB, et al. Natriuretic Effect of Two Weeks of Dapagliflozin Treatment in Patients With Type 2 Diabetes and Preserved Kidney Function During Standardized Sodium Intake: Results of the DAPASALT Trial. Diabetes Care. 2021;44(2):440-447. doi:10.2337/dc20-2604 70. Boorsma EM, Beusekamp JC, Ter Maaten JM, et al. Effects of empagliflozin on renal sodium and glucose handling in patients with acute heart failure. Eur J Heart Fail. 2021;23(1):68-78. doi:10.1002/ejhf.2066 71. Ferreira JP, Abreu P, McMurray JJV, et al. Renal function stratified dose comparisons of eplerenone versus placebo in the EMPHASIS-HF trial. European Journal of Heart Failure. 2019;21(3):345-351. doi:10.1002/ejhf.1400 72. Zannad F, McMurray JJV, Krum H, et al. Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms. New England Journal of Medicine. 2011;364(1):11-21. doi:10.1056/NEJMoa1009492 73. Konstam MA, Neaton JD, Dickstein K, et al. Effects of high-dose versus low-dose losartan on clinical outcomes in patients with heart failure (HEAAL study): a randomised, double-blind trial. Lancet. 2009;374(9704):1840-1848. doi:10.1016/S0140-6736(09)61913-9 74. Packer M, Poole-Wilson PA, Armstrong PW, et al. Comparative Effects of Low and High Doses of the Angiotensin-Converting Enzyme Inhibitor, Lisinopril, on Morbidity and Mortality in Chronic Heart Failure. Circulation. 1999;100(23):2312-2318. doi:10.1161/01.CIR.100.23.2312 75. Turgeon RD, Kolber MR, Loewen P, Ellis U, McCormack JP. Higher versus lower doses of ACE inhibitors, angiotensin-2 receptor blockers and beta-blockers in heart failure with reduced ejection fraction: Systematic review and meta-analysis. PLoS One. 2019;14(2):e0212907. doi:10.1371/journal.pone.0212907 76. Vardeny O, Claggett B, Packer M, et al. Efficacy of sacubitril/valsartan vs. enalapril at lower than target doses in heart failure with reduced ejection fraction: the PARADIGM-HF trial. European Journal of Heart Failure. 2016;18(10):1228-1234. doi:10.1002/ejhf.580 77. McAlister FA, Wiebe N, Ezekowitz JA, Leung AA, Armstrong PW. Meta-analysis: beta-blocker dose, heart rate reduction, and death in patients with heart failure. Ann Intern Med. 2009;150(11):784-794. doi:10.7326/0003-4819-150-11-200906020-00006 78. Wikstrand J, Hjalmarson A, Waagstein F, et al. Dose of metoprolol CR/XL and clinical outcomes in patients with heart failure: analysis of the experience in metoprolol CR/XL 114 randomized intervention trial in chronic heart failure (MERIT-HF). J Am Coll Cardiol. 2002;40(3):491-498. doi:10.1016/s0735-1097(02)01970-8 79. Düngen HD, Apostolovic S, Inkrot S, et al. Titration to target dose of bisoprolol vs. carvedilol in elderly patients with heart failure: the CIBIS-ELD trial. Eur J Heart Fail. 2011;13(6):670-680. doi:10.1093/eurjhf/hfr020 80. Ouwerkerk W, Teng THK, Tromp J, et al. Effects of combined reninâangiotensinâaldosterone system inhibitor and beta-blocker treatment on outcomes in heart failure with reduced ejection fraction: insights from BIOSTAT-CHF and ASIAN-HF registries. European Journal of Heart Failure. 2020;22(8):1472-1482. doi:10.1002/ejhf.1869 81. Greene SJ, Butler J, Albert NM, et al. Medical Therapy for Heart Failure With Reduced Ejection Fraction: The CHAMP-HF Registry. J Am Coll Cardiol. 2018;72(4):351-366. doi:10.1016/j.jacc.2018.04.070 82. Teng THK, Tromp J, Tay WT, et al. Prescribing patterns of evidence-based heart failure pharmacotherapy and outcomes in the ASIAN-HF registry: a cohort study. Lancet Glob Health. 2018;6(9):e1008-e1018. doi:10.1016/S2214-109X(18)30306-1 83. Ferreira JP, Rossignol P, Machu JL, et al. Mineralocorticoid receptor antagonist pattern of use in heart failure with reduced ejection fraction: findings from BIOSTAT-CHF. Eur J Heart Fail. 2017;19(10):1284-1293. doi:10.1002/ejhf.900 84. Cowie MR, Schöpe J, Wagenpfeil S, et al. Patient factors associated with titration of medical therapy in patients with heart failure with reduced ejection fraction: data from the QUALIFY international registry. ESC Heart Fail. 2021;8(2):861-871. doi:10.1002/ehf2.13237 85. Komajda M, Anker SD, Cowie MR, et al. Physiciansâ adherence to guideline-recommended medications in heart failure with reduced ejection fraction: data from the QUALIFY global survey. Eur J Heart Fail. 2016;18(5):514-522. doi:10.1002/ejhf.510 86. Vaduganathan M, Greene SJ, Zhang S, et al. Applicability of US Food and Drug Administration Labeling for Dapagliflozin to Patients With Heart Failure With Reduced Ejection Fraction in US Clinical Practice: The Get With the Guidelines-Heart Failure (GWTG-HF) Registry. JAMA Cardiol. 2020;6(3):1-10. doi:10.1001/jamacardio.2020.5864 87. Felker GM, Anstrom KJ, Adams KF, et al. Effect of Natriuretic Peptide-Guided Therapy on Hospitalization or Cardiovascular Mortality in High-Risk Patients With Heart Failure and Reduced Ejection Fraction: A Randomized Clinical Trial. JAMA. 2017;318(8):713-720. doi:10.1001/jama.2017.10565 88. Packer M, Lee WH, Medina N, Yushak M, Kessler PD. Functional renal insufficiency during long-term therapy with captopril and enalapril in severe chronic heart failure. Ann Intern Med. 1987;106(3):346-354. doi:10.7326/0003-4819-106-3-346 115 89. Packer M, Kessler PD, Gottlieb SS. Adverse effects of converting-enzyme inhibition in patients with severe congestive heart failure: pathophysiology and management. Postgrad Med J. 1986;62 Suppl 1:179-182. 90. Sackner-Bernstein JD. Use of carvedilol in chronic heart failure: Challenges in therapeutic management. Progress in Cardiovascular Diseases. 1998;41(1, Supplement 1):53-58. doi:10.1016/S0033-0620(98)80031-5 91. Marti CN, Fonarow GC, Anker SD, et al. Medication dosing for heart failure with reduced ejection fraction - opportunities and challenges. Eur J Heart Fail. 2019;21(3):286-296. doi:10.1002/ejhf.1351 92. Lam PH, Packer M, Fonarow GC, et al. Early Effects of Starting Doses of Enalapril in Patients with Chronic Heart Failure in the SOLVD Treatment Trial. Am J Med. 2020;133(2):e25-e31. doi:10.1016/j.amjmed.2019.06.053 93. Krum H, Roecker EB, Mohacsi P, et al. Effects of initiating carvedilol in patients with severe chronic heart failure: results from the COPERNICUS Study. JAMA. 2003;289(6):712-718. doi:10.1001/jama.289.6.712 94. Pitt B, White H, Nicolau J, et al. Eplerenone reduces mortality 30 days after randomization following acute myocardial infarction in patients with left ventricular systolic dysfunction and heart failure. J Am Coll Cardiol. 2005;46(3):425-431. doi:10.1016/j.jacc.2005.04.038 95. Packer M, McMurray JJV, Desai AS, et al. Angiotensin receptor neprilysin inhibition compared with enalapril on the risk of clinical progression in surviving patients with heart failure. Circulation. 2015;131(1):54-61. doi:10.1161/CIRCULATIONAHA.114.013748 96. Morrow DA, Velazquez EJ, DeVore AD, et al. Clinical Outcomes in Patients With Acute Decompensated Heart Failure Randomly Assigned to Sacubitril/Valsartan or Enalapril in the PIONEER-HF Trial. Circulation. 2019;139(19):2285-2288. doi:10.1161/CIRCULATIONAHA.118.039331 97. Packer M, Anker SD, Butler J, et al. Effect of Empagliflozin on the Clinical Stability of Patients With Heart Failure and a Reduced Ejection Fraction: The EMPEROR-Reduced Trial. Circulation. 2021;143(4):326-336. doi:10.1161/CIRCULATIONAHA.120.051783 98. Poole-Wilson PA, Cleland JGF, Di Lenarda A, et al. Rationale and design of the carvedilol or metoprolol European trial in patients with chronic heart failure: COMET. Eur J Heart Fail. 2002;4(3):321-329. doi:10.1016/s1388-9842(02)00025-9 99. Borovac JA. Early in-hospital initiation and optimization of comprehensive disease-modifying pharmacotherapy in patients with heart failure with reduced ejection fraction: a time for the paradigm shift. Expert Review of Cardiovascular Therapy. 2022;20(2):91-94. doi:10.1080/14779072.2022.2039626 116 100. Husereau D, Drummond M, Petrou S, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMJ. 2013;346:f1049. doi:10.1136/bmj.f1049 101. Pharmacy Compass - Pharmacy Compass. Accessed March 26, 2023. https://www.pac.bluecross.ca/pharmacycompass 102. Health M of. MSC Payment Schedule - Province of British Columbia. Accessed March 26, 2023. https://www2.gov.bc.ca/gov/content/health/practitioner-professional-resources/msp/physicians/payment-schedules/msc-payment-schedule 103. Patient Cost Estimator | CIHI. Accessed April 30, 2022. https://www.cihi.ca/en/patient-cost-estimator 104. Armoiry X, Obadia JF, Auguste P, Connock M. Conflicting findings between the Mitra-Fr and the Coapt trials: Implications regarding the cost-effectiveness of percutaneous repair for heart failure patients with severe secondary mitral regurgitation. PLoS One. 2020;15(11):e0241361. doi:10.1371/journal.pone.0241361 105. Ademi Z, Pfeil AM, Hancock E, et al. Cost-effectiveness of sacubitril/valsartan in chronic heart-failure patients with reduced ejection fraction. Swiss Med Wkly. 2017;147:w14533. doi:10.4414/smw.2017.14533 106. Sullivan PW, Lawrence WF, Ghushchyan V. A National Catalog of Preference-Based Scores for Chronic Conditions in the United States. Medical Care. 2005;43(7):736-749. doi:10.1097/01.mlr.0000172050.67085.4f 107. Widén J, Ivarsson M, Schalin L, et al. Cost-Effectiveness Analysis of Patiromer in Combination with ReninâAngiotensinâAldosterone System Inhibitors for Chronic Kidney Disease in Sweden. PharmacoEconomics. 2020;38(7):747-764. doi:10.1007/s40273-020-00902-w 108. Salcedo J, Hay JW, Lam J. Cost-effectiveness of rivaroxaban versus warfarin for treatment of nonvalvular atrial fibrillation in patients with worsening renal function. International Journal of Cardiology. 2019;282:53-58. doi:10.1016/j.ijcard.2018.11.087 109. Effect of Enalapril on Survival in Patients with Reduced Left Ventricular Ejection Fractions and Congestive Heart Failure. New England Journal of Medicine. 1991;325(5):293-302. doi:10.1056/NEJM199108013250501 110. Jong P, Yusuf S, Rousseau MF, Ahn SA, Bangdiwala SI. Effect of enalapril on 12-year survival and life expectancy in patients with left ventricular systolic dysfunction: a follow-up study. The Lancet. 2003;361(9372):1843-1848. doi:10.1016/S0140-6736(03)13501-5 111. Pocock SJ, Wang D, Pfeffer MA, et al. Predictors of mortality and morbidity in patients with chronic heart failure. European Heart Journal. 2006;27(1):65-75. doi:10.1093/eurheartj/ehi555 117 112. Fonarow GC, Adams KF, Abraham WT, Yancy CW, Boscardin WJ, ADHERE Scientific Advisory Committee SG and Investigators, for the. Risk Stratification for In-Hospital Mortality in Acutely Decompensated Heart FailureClassification and Regression Tree Analysis. JAMA. 2005;293(5):572-580. doi:10.1001/jama.293.5.572 113. Kostis JB, Shelton B, Gosselin G, et al. Adverse effects of enalapril in the Studies of Left Ventricular Dysfunction (SOLVD). American Heart Journal. 1996;131(2):350-355. doi:10.1016/S0002-8703(96)90365-8 114. Packer M, Bristow MR, Cohn JN, et al. The effect of carvedilol on morbidity and mortality in patients with chronic heart failure. U.S. Carvedilol Heart Failure Study Group. N Engl J Med. 1996;334(21):1349-1355. doi:10.1056/NEJM199605233342101 115. Knight EL, Glynn RJ, McIntyre KM, Mogun H, Avorn J. Predictors of decreased renal function in patients with heart failure during angiotensin-converting enzyme inhibitor therapy: Results from the Studies of Left Ventricular Dysfunction (SOLVD). American Heart Journal. 1999;138(5):849-855. doi:10.1016/S0002-8703(99)70009-8 116. BÅuf-Gibot S, Pereira B, Imbert J, et al. Benefits and adverse effects of ACE inhibitors in patients with heart failure with reduced ejection fraction: a systematic review and meta-analysis. Eur J Clin Pharmacol. 2021;77(3):321-329. doi:10.1007/s00228-020-03018-4 117. Flather MD, Yusuf S, Køber L, et al. Long-term ACE-inhibitor therapy in patients with heart failure or left-ventricular dysfunction: a systematic overview of data from individual patients. The Lancet. 2000;355(9215):1575-1581. doi:10.1016/S0140-6736(00)02212-1 118. Gao J, Zhao C, Zhang WZ, Liu S, Xin H, Lian ZX. Efficacy and safety profile of angiotensin receptor neprilysin inhibitors in the management of heart failure: a systematic review and meta-analysis of randomized controlled trials. Heart Fail Rev. Published online October 3, 2022. doi:10.1007/s10741-022-10273-3 119. Mohebi R, Liu Y, Piña IL, et al. Dose-Response to Sacubitril/Valsartan in Patients With Heart Failure and Reduced Ejection Fraction. Journal of the American College of Cardiology. 2022;80(16):1529-1541. doi:10.1016/j.jacc.2022.08.737 120. Shibata MC, Flather MD, Wang D. Systematic review of the impact of beta blockers on mortality and hospital admissions in heart failure. European Journal of Heart Failure. 2001;3(3):351-357. doi:10.1016/S1388-9842(01)00144-1 121. Barron AJ, Zaman N, Cole GD, Wensel R, Okonko DO, Francis DP. Systematic review of genuine versus spurious side-effects of beta-blockers in heart failure using placebo control: Recommendations for patient information. Int J Cardiol. 2013;168(4):3572-3579. doi:10.1016/j.ijcard.2013.05.068 118 122. Bristow MR, Gilbert EM, Abraham WT, et al. Carvedilol Produces Dose-Related Improvements in Left Ventricular Function and Survival in Subjects With Chronic Heart Failure. Circulation. 1996;94(11):2807-2816. doi:10.1161/01.CIR.94.11.2807 123. Simon T, Mary-Krause M, Funck-Brentano C, Lechat Ph, Jaillon P, on behalf of CIBIS II investigators. Bisoprolol doseâresponse relationship in patients with congestive heart failure: a subgroup analysis in the cardiac insufficiency bisoprolol study (CIBIS II). European Heart Journal. 2003;24(6):552-559. doi:10.1016/S0195-668X(02)00743-1 124. Berbenetz NM, Mrkobrada M. Mineralocorticoid receptor antagonists for heart failure: systematic review and meta-analysis. BMC Cardiovasc Disord. 2016;16:246. doi:10.1186/s12872-016-0425-x 125. Serenelli M, Jackson A, Dewan P, et al. Mineralocorticoid Receptor Antagonists, Blood Pressure, and Outcomes in Heart Failure With Reduced Ejection Fraction. JACC Heart Fail. 2020;8(3):188-198. doi:10.1016/j.jchf.2019.09.011 126. Butler J, Usman MS, Khan MS, et al. Efficacy and safety of SGLT2 inhibitors in heart failure: systematic review and meta-analysis. ESC Heart Failure. 2020;7(6):3298-3309. doi:10.1002/ehf2.13169 127. Ferreira JP, Zannad F, Butler J, et al. Empagliflozin and serum potassium in heart failure: an analysis from EMPEROR-Pooled. European Heart Journal. 2022;43(31):2984-2993. doi:10.1093/eurheartj/ehac306 128. Statistics Canada. Table 18-10-0005-01 Consumer Price Index, annual average, not seasonally adjusted. Published July 31, 2023. Accessed July 31, 2023. https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810000501 129. Restelli U, Rizzardini G, Antinori A, et al. Cost-effectiveness analysis of dolutegravir plus backbone compared with raltegravir plus backbone, darunavir+ritonavir plus backbone and efavirenz/tenofovir/emtricitabine in treatment naïve and experienced HIV-positive patients. Ther Clin Risk Manag. 2017;13:787-797. doi:10.2147/TCRM.S135972 130. CADTH. Guidelines for the Economic Evaluation of Health Technologies: Canada (4th Edition). Published online March 2017. https://www.cadth.ca/guidelines-economic-evaluation-health-technologies-canada-4th-edition 131. Cantor SB. Cost - Effectiveness Analysis, Extended Dominance, and Ethics: A Quantitative Assessment. Med Decis Making. 1994;14(3):259-265. doi:10.1177/0272989X9401400308 132. Griffiths EA, Vadlamudi NK. Cadthâs $50,000 Cost-Effectiveness Threshold: Fact or Fiction? Value in Health. 2016;19(7):A488-A489. doi:10.1016/j.jval.2016.09.821 133. Vaduganathan M, Claggett BL, Jhund PS, et al. Estimating lifetime benefits of comprehensive disease-modifying pharmacological therapies in patients with heart failure 119 with reduced ejection fraction: a comparative analysis of three randomised controlled trials. Lancet. 2020;396(10244):121-128. doi:10.1016/S0140-6736(20)30748-0 134. Granger CB, McMurray JJ, Yusuf S, et al. Effects of candesartan in patients with chronic heart failure and reduced left-ventricular systolic function intolerant to angiotensin-converting-enzyme inhibitors: the CHARM-Alternative trial. The Lancet. 2003;362(9386):772-776. doi:10.1016/S0140-6736(03)14284-5 135. Cohn JN, Tognoni G. A Randomized Trial of the Angiotensin-Receptor Blocker Valsartan in Chronic Heart Failure. New England Journal of Medicine. 2001;345(23):1667-1675. doi:10.1056/NEJMoa010713 136. McMurray JJV, Packer M, Desai AS, et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med. 2014;371(11):993-1004. doi:10.1056/NEJMoa1409077 137. Packer M, Fowler MB, Roecker EB, et al. Effect of carvedilol on the morbidity of patients with severe chronic heart failure: results of the carvedilol prospective randomized cumulative survival (COPERNICUS) study. Circulation. 2002;106(17):2194-2199. doi:10.1161/01.cir.0000035653.72855.bf 138. Pitt B, Remme W, Zannad F, et al. Eplerenone, a Selective Aldosterone Blocker, in Patients with Left Ventricular Dysfunction after Myocardial Infarction. New England Journal of Medicine. 2003;348(14):1309-1321. doi:10.1056/NEJMoa030207 139. Pitt B, Zannad F, Remme WJ, et al. The Effect of Spironolactone on Morbidity and Mortality in Patients with Severe Heart Failure. New England Journal of Medicine. 1999;341(10):709-717. doi:10.1056/NEJM199909023411001 140. Packer M, Anker SD, Butler J, et al. Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure. N Engl J Med. 2020;383(15):1413-1424. doi:10.1056/NEJMoa2022190 120 Appendices Appendix A - Background A.1 Table A1: HFrEF Standard Therapies Medication class Agents in class Number of dose titrations to reach target dose* Common adverse events Trials ACEI or ARB Enalapril, Lisinopril, Ramipril, Trandolapril, Candesartan, Valsartan 2-3 hypotension, hyperkalemia, cough, dizziness SOLVD109, CHARM-Alt134, Val-HeFT135 ARNI Sacubitril/ valsartan 1-2 hypotension, hyperkalemia, cough, dizziness PARADIGM-HF136 BB Bisoprolol, Carvedilol, Metoprolol succinate 2-3 bradycardia, dizziness, hypotension CIBIS II61, COPERNICUS137, MERIT-HF62 MRA Eplerenone, Spironolactone 0-1 renal impairment, hyperkalemia, gynecomastia EPHESUS138, EMPHASIS-HF72, RALES139 SGLT2I Dapagliflozin, Empagliflozin 0 urinary tract infection, yeast infection DAPA-HF,50 EMPEROR-reduced140 *Number of cycles required to go from starting dose to target dose, assuming dose is double every cycle. SOLVD: Studies of Left Ventricular Dysfunction; CHARM: Candesartan in Heart Failure Assessment of Reduction in Mortality and morbidity; Val-HeFT: The Valsartan Heart Failure Trial; PARADIGM-HF: Prospective Comparison of ARNI with ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure; CIBIS: Cardiac Insufficiency Bisoprolol Study; COPERNICUS: Carvedilol Prospective Randomized Cumulative Survival; MERIT-HF: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure; EPHESUS: Eplerenone Post-AMI Heart Failure Efficacy and Survival Study; EMPHASIS-HF: Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure; RALES: Randomized Aldactone Evaluation Study; DAPA-HF: Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure; EMPEROR-reduced: EMPagliflozin outcomE tRial in Patients With chrOnic heaRt Failure With Reduced Ejection Fraction.121 Appendix B - Scoping review B.1 Table B1: Search strategy Database/ Non-database sources Search strategy # of items identified MEDLINE Date of search: 2022-09-18 1. exp Heart Failure/ 2. Cardiomyopathy, Dilated/ 3. (HF or heart failure or cardiac failure or cardiac insufficiency or cardiomyopathy*).tw. 4. ((cardi* or myocard*) adj2 (failure* or insufficien*)).tw. 5. OR/1-4 6. (angiotensin receptor-neprilysin inhibitor or ARNI).mp. 7. exp Angiotensin-Converting Enzyme Inhibitors/ 8. ((angiotensin converting enzyme) adj2 (antagonist$ or inhibitor$) or ACEI*).mp. 9. exp Angiotensin Receptor Antagonists/ 10. ((angiotensin Receptor) adj2 (antagonist$ or inhibitor$ or blocker$) or ARB*).mp. 11. exp Adrenergic beta-Antagonists/ 12. (beta blocker* OR BB*).mp 13. exp aldosterone antagonist/ 14. (aldosterone antagonist$ OR mineralocorticoid-receptor antagonist OR MRA*).mp. 15. exp Sodium-Glucose Transporter 2 Inhibitors/ 16. (sodium-glucose co-transporter 2 OR SGLT2 OR SGLT2 inhibitor* OR sodium glucose adj6 inhibitor* OR (SGLT2 inhibitor*) OR sodium-glucose adj6 inhibitor* OR Sodium-Glucose Transporter 2 OR sodium glucose-cotransporter 2 OR sodium-glucose co-transporter* OR sodium glucose-cotransporter*).mp. 17. OR/6-16 18. ((up-titrat* or titrat* or sequenc* or add* or modif* or adjust* or initiat*) adj2 (treatment* or therap* or medication* or medication* or medic* or regimen* or intervention* or dose* or strateg*)).mp. 19. Medication combinations/ or medication medication, combination/ 20. OR/18-19 21. 5 AND 17 AND 20 22. limit 21 to yr=â2019-Currentâ 1021 EMBASE Date of search: 2022-09-18 1. exp Heart Failure/ 2. congestive cardiomyopathy/ 2939 122 Database/ Non-database sources Search strategy # of items identified 3. (HF or heart failure or cardiac failure or cardiac insufficiency or cardiomyopathy*).tw. 4. ((cardi* or myocard*) adj2 (failure* or insufficien*)).tw. 5. OR/1-4 6. exp sacubitril plus valsartan/ 7. dipeptidyl carboxypeptidase inhibitor/ 8. ((angiotensin converting enzyme) adj2 (antagonist$ or inhibitor$) or ACEI*).mp. 9. exp angiotensin receptor antagonist/ 10. ((angiotensin Receptor) adj2 (antagonist$ or inhibitor$ or blocker$) or ARB*).mp. 11. exp beta adrenergic receptor blocking agent/ 12. (beta blocker* OR BB*).mp 13. exp aldosterone antagonist/ OR aldosterone antagonist/ 14. (aldosterone antagonist$ or mineralocorticoid-receptor antagonist or MRA*).mp. 15. exp sodium glucose cotransporter 2 inhibitor/ 16. (((((sodium-glucose co-transporter 2 or SGLT2 or SGLT2 inhibitor* or sodium glucose) adj6 inhibitor*) or SGLT2 inhibitor* or sodium-glucose) adj6 inhibitor*) or Sodium-Glucose Transporter 2 or sodium glucose-cotransporter 2 or sodium-glucose co-transporter* or sodium glucose-cotransporter*).mp. 17. OR/6-16 18. ((up-titrat* or titrat* or sequenc* or add* or modif* or adjust* or initiat*) adj2 (treatment* or therap* or medication* or medication* or medic* or regimen* or intervention* or dose* or strateg*)).mp. 19. medication combination/ or combination medication medication/ 20. OR/18-19 21. 5 AND 17 AND 20 22. limit 21 to yr=â2019-Currentâ ACCESSSS.org Date of search: 2022-10-21 Search term: heart failure AND (medication OR medication) AND (sequencing OR titration OR modifying OR switching) Discipline: Select All Categories: Treatment Population: Adults Article Type: Select All Medication Study: Medication studies 168 Trip Database Date of search: 2022-10-21 Population: Heart failure reduced ejection fraction Intervention: Treatment sequencing strategy 105 123 Database/ Non-database sources Search strategy # of items identified Comparison: None Outcome: N/A Since 2019 Google /Google Scholar Date of search: 2022-10-21 1. âHF treatment sequencing strategyâ 2. âHeart failure treatment sequencing strategyâ 3. âHeart failure titration strategyâ 4. âQuadruple medication sequencing strategyâ Limited to the first 30 results for each search term Jan 1, 2019 â Date of Search 120 Other sources (e.g., Web of science citation searching) Date of search: 2022-10-21 Forward citations search of all final Medline/Embase articles 134 124 B.2 Table B2: Data collection guide Overview Reference Extract text: â¢ Authors: last and first name of first author â¢ Year: Publication year â¢ References Article type Definition: â¢ Viewpoint/commentaries: A paper giving a broad oversight, opinion, perspective, or point of view of the author or authors on a particular topic. â¢ Primary research: Consists of a collection of original primary data collected from trials, observational studies or generated using simulation models. â¢ Systematic review: Collection and synthesis of available evidence on a topic, if a systematic approach was lacking, these studies were scored as narrative reviews. Year of first publication Extract number: â¢ For a group of articles, the year of the first article was published. Identification Strategy name Extract Text: â¢ Strategy ânameâ as referred by the original authors (if any) OR â¢ Not reported: Not enough details are provided to report. Strategy description Extract Text: â¢ Brief description of sequencing strategy breaking down into step, which include titration and/or initiation, including approximate duration in weeks Rationalization Rationales Extract Text, and include references: â¢ Specific rationale(s) for choice of attributes related to the order of medication prioritization can be extracted: The number and identity of medications initiated in the first visit, the order of medication initiation. For our study, a visit was defined as any physical or virtual contact between a patient and healthcare practitioner in which medication adjustments were performed. â¢ Specific rationale(s) for choice of attributes related to the timing and characteristics of initiation and titration could be extracted: When titration is started (relative to completing initiation), the characteristic of medication adjustments (Sequential vs. Simultaneous), the frequency of medication adjustments, the minimum expected time to complete all medication initiations and titrations. These attributes provide insights into the different 125 considerations and relationships between initiation and titration within the sequencing strategies OR â¢ Not reported: Not enough details are provided to report. Categorization - 8 Sequencing strategy attributes Number of medications initiated during the first visit Extract Number: â¢ Number of medications started in the first step Example: 2 (i.e., 2 medications are started during initial visit) Identity of medications initiated during the first visit Choose one or multiple of the following standard medication classes: â¢ ACEI/ARB â¢ ARNI â¢ BB â¢ MRA â¢ SGLT2I Order of initiation Extract Text: â¢ Ranking of medication from the one being initiated first to the one being initiated last. â¢ Notation: X>Y: Initiate X before Y, X=Y: Initiate X at the same time at Y, Xâ¥Y: Initiate X before OR at the same time at Y Example: BB>ARNI>SGLT2I>MRA Timing of starting titration (relative to completing initiation) Choose one of the following: â¢ Before completing all 4-medication initiations: Titration is started immediately after each medication initiation and before the initiation of all medications is completed. â¢ After completing all 4-medication initiations: After completing the initiation of all four medications, titration is started. This can occur either during a separate visit or during the final visit when all four medication initiations are completed. â¢ Not reported: Not enough details are provided to report. Characteristic of medication adjustments Choose one of the following: â¢ Sequential: No more than 1 medication is adjusted (i.e., initiated, titrated) in the same visit in all steps. â¢ Simultaneous: Multiple (â¥2) medications could be is adjusted (i.e., initiated, titrated) in the same visit in at least 1 step. â¢ Not reported: Not enough details are provided to report. Average frequency of medication adjustments Extract Number: â¢ Minimum weeks - maximum weeks OR â¢ Not reported: Not enough details are provided to report. Minimum time to complete all medication initiations Extract Number: â¢ Minimum weeks - maximum weeks OR â¢ Not reported: Not enough details are provided to report. 126 Minimum time to complete all medication titrations Extract Number: â¢ Minimum weeks - maximum weeks OR â¢ Not reported: Not enough details are provided to report. 127 B.3 Table B3: Full-text articles considered for eligibility and reason for exclusion # Citation Source (Database or Non-Database) Verdict (Included or excluded) Reasons for exclusion (If excluded) Combined into article (If included) 1 Bhatt AS, Abraham WT, Lindenfeld J, et al. Treatment of HF in an Era of Multiple Medications: Statement From the HF Collaboratory. JACC Heart Fail. 2021;9(1):1-12. doi:10.1016/j.jchf.2020.10.014 Non-Database Excluded Did not provide detailed sequencing strategy 2 Fucili A, Cimaglia P, Severi P, Giannini F, Boccadoro A, Micillo M, Rapezzi C, Tavazzi L, Ferrari R. Looking for a Tailored Medication for Heart Failure: Are We Capable of Treating the Patient Instead of the Disease? Journal of Clinical Medicine. 2021; 10(19):4325. https://doi.org/10.3390/jcm10194325 Non-Database Excluded Did not provide detailed sequencing strategy 3 McDonald M, Virani S, Chan M, et al. CCS/CHFS Heart Failure Guidelines Update: Defining a New Pharmacologic Standard of Care for Heart Failure With Reduced Ejection Fraction. Can J Cardiol. 2021;37(4):531-546. doi:10.1016/j.cjca.2021.01.017 Non-Database Excluded Did not provide detailed sequencing strategy 4 Tromp J, Voors AA. Heart failure medication: moving from evidence generation to implementation. Eur Heart J. 2022;43(27):2588-2590. doi:10.1093/eurheartj/ehac272 Non-Database Excluded Did not provide detailed sequencing strategy 5 Heidenreich PA, Bozkurt B, Aguilar D, et al. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines [published correction appears in Circulation. 2022 May 3;145(18):e1033] [published correction appears in Circulation. 2022 Sep 27;146(13):e185]. Circulation. 2022;145(18):e895-e1032. doi:10.1161/CIR.0000000000001063 Non-Database Excluded Did not provide detailed sequencing strategy 128 # Citation Source (Database or Non-Database) Verdict (Included or excluded) Reasons for exclusion (If excluded) Combined into article (If included) 6 Tsutsui H. Recent advances in the pharmacological medication of chronic heart failure: Evidence and guidelines. Pharmacol Ther. 2022;238:108185. doi:10.1016/j.pharmthera.2022.108185 Non-Database Excluded Did not provide detailed sequencing strategy 7 Escobar C, Luis-Bonilla J, Crespo-Leiro MG, et al. Individualizing the treatment of patients with heart failure with reduced ejection fraction: a journey from hospitalization to long-term outpatient care. Expert Opin Pharmacother. 2022;23(14):1589-1599. doi:10.1080/14656566.2022.2116275 Non-Database Excluded Did not provide detailed sequencing strategy 8 Manito N. New 2021 ESC/HFA heart failure guidelines. A practical comprehensive approach. Rev Esp Cardiol (Engl Ed). 2022;75(7):548-551. doi:10.1016/j.rec.2022.02.006 Non-Database Excluded Did not provide detailed sequencing strategy 9 Kalogeropoulos AP, Butler J. Uptitrating versus adding heart failure with reduced ejection fraction medications: bring more players to the game. Eur J Heart Fail. 2022;24(5):885-886. doi:10.1002/ejhf.2507 Non-Database Excluded Did not provide detailed sequencing strategy 10 Abdin A, Bauersachs J, Frey N, et al. Timely and individualized heart failure management: need for implementation into the new guidelines. Clin Res Cardiol. 2021;110(8):1150-1158. doi:10.1007/s00392-021-01867-2 Non-Database Excluded Did not provide detailed sequencing strategy 11 Mueller C, Bally K, Buser M, et al. Roadmap for the treatment of heart failure patients after hospital discharge: an interdisciplinary consensus paper. Swiss Med Wkly. 2020;150:w20159. Published 2020 Feb 6. doi:10.4414/smw.2020.20159 Non-Database Excluded Did not include all quadruple medication 12 Kondo T, Jhund PS, McMurray JJV. Medication medication for heart failure with reduced ejection fraction: what is the 'right' dose?. Eur J Heart Fail. 2022;24(3):421-430. doi:10.1002/ejhf.2447 Non-Database Excluded Did not provide detailed sequencing strategy 129 # Citation Source (Database or Non-Database) Verdict (Included or excluded) Reasons for exclusion (If excluded) Combined into article (If included) 13 Abdin A, Bauersachs J, Soltani S, Eden M, Frey N, Böhm M. A practical approach to the guideline-directed pharmacological treatment of heart failure with reduced ejection fraction [published online ahead of print, 2022 Oct 13]. ESC Heart Fail. 2022;10.1002/ehf2.14197. doi:10.1002/ehf2.14197 Non-Database Excluded Did not provide detailed sequencing strategy 14 Bhatt AS, Vaduganathan M, Butler J. Angiotensin-neprilysin inhibition in de novo heart failure - starting off strong. Eur J Heart Fail. 2020;22(2):313-314. doi:10.1002/ejhf.1675 Database Excluded Did not include all quadruple medication 15 Agarwal A, Yancy CW, Huffman MD. Improving Care for Heart Failure With Reduced Ejection Fraction-A Potential Polypill-Based Strategy. JAMA. 2020;324(22):2259-2260. doi:10.1001/jama.2020.21395 Database Excluded Did not provide detailed sequencing strategy 16 Shacham, Yacov. (2020). Medication Titration in Heart Failure: Too High or Too Complex?. The Israel Medical Association journal : IMAJ. 22. 519-520. Database Excluded Did not provide detailed sequencing strategy 17 Evans M, Morgan AR, Yousef Z, et al. Optimising the Heart Failure Treatment Pathway: The Role of SGLT2 Inhibitors. Medications. 2021;81(11):1243-1255. doi:10.1007/s40265-021-01538-6 Database Excluded Did not provide detailed sequencing strategy 18 Desai AS, Maclean T, Blood AJ, et al. Remote Optimization of Guideline-Directed Medical Medication in Patients With Heart Failure With Reduced Ejection Fraction [published correction appears in JAMA Cardiol. 2021 Apr 1;6(4):485]. JAMA Cardiol. 2020;5(12):1430-1434. doi:10.1001/jamacardio.2020.3757 Database Excluded Did not provide detailed sequencing strategy 19 Greene SJ, Butler J, Metra M. Another reason to embrace quadruple medical medication for heart failure: medications enabling tolerance of each other. Eur J Heart Fail. 2021;23(9):1525-1528. doi:10.1002/ejhf.2301 Database Excluded Did not provide detailed sequencing strategy 130 # Citation Source (Database or Non-Database) Verdict (Included or excluded) Reasons for exclusion (If excluded) Combined into article (If included) 20 Wilcox JE. Early Implementation of Sacubitril/Valsartan for Patients With Heart Failure. JAMA Cardiol. 2020;5(2):207-208. doi:10.1001/jamacardio.2019.4822 Database Excluded Did not include all quadruple medication 21 Fragasso G. Editorial Commentary: Medication dosing optimization in heart failure: Need of a multidimensional approach (and skilled heart failure specialists). Trends Cardiovasc Med. 2021;31(2):117-118. doi:10.1016/j.tcm.2020.01.007 Database Excluded Did not provide detailed sequencing strategy 22 Tanaka A, Node K. When and for Whom Should We Use SGLT2 Inhibitors in HFrEF?. JACC Heart Fail. 2020;8(12):1056. doi:10.1016/j.jchf.2020.07.009 Database Excluded Did not include all quadruple medication 23 Shen L, Jhund PS, Docherty KF, et al. Accelerated and personalized medication for heart failure with reduced ejection fraction. European Heart Journal. Published online April 25, 2022:ehac210. doi:10.1093/eurheartj/ehac210 Database Included 1 article describes 11 strategies 24 Packer M, McMurray JJV. Rapid evidence-based sequencing of foundational medications for heart failure and a reduced ejection fraction. European Journal of Heart Failure. 2021;23(6):882-894. doi:10.1002/ejhf.2149 Database Included 1 article describes 1 strategy 25 McMurray JJV, Packer M. How Should We Sequence the Treatments for Heart Failure and a Reduced Ejection Fraction? Circulation. 2020;(143):875-877. doi:10.1161/CIRCULATIONAHA.120.052926. Database Included 26 McMurray JJV, Docherty KF. Insights into foundational medications for heart failure with reduced ejection fraction. Clin Cardiol. 2022;45 Suppl 1:S26-S30. doi:10.1002/clc.23847 Database Included 27 Docherty KF, McMurray JJV. Foundational medications for HFrEF: the growing evidence for a rapid sequencing strategy. Br J Cardiol. 2022;29:12-15. doi:10.5837/bjc.2022.002 Database Included 131 # Citation Source (Database or Non-Database) Verdict (Included or excluded) Reasons for exclusion (If excluded) Combined into article (If included) 28 Lokre A, Vala DR. Medication of heart failure (heart failure with reduced ejection fraction): New sequencing (medication medication). JOURNAL OF INDIAN COLLEGE OF CARDIOLOGY. 2021;11(2):44. doi:10.4103/jicc.jicc_8_21 Database Included 29 Sharma A, Verma S, Bhatt DL, et al. Optimizing Foundational Medications in Patients With HFrEF: How Do We Translate These Findings Into Clinical Care? JACC: Basic to Translational Science. Published online March 2, 2022. doi:10.1016/j.jacbts.2021.10.018 Database Included 1 article describes 1 strategy: (C) de novo non-ischemic heart failure with reduced ejection fraction 30 Silva-Cardoso J, Fonseca C, Franco F, Morais J, Ferreira J, Brito D. Optimization of heart failure with reduced ejection fraction prognosis-modifying medications: A 2021 heart failure expert consensus paper. Revista Portuguesa de Cardiologia. 2021;40(12):975-983. doi:10.1016/j.repc.2021.07.009 Database Included 1 article describes 1 strategy: Heart failure with reduced ejection fraction non-diabetic patients 31 Straw S, McGinlay M, Witte KK. Four pillars of heart failure: contemporary pharmacological medication for heart failure with reduced ejection fraction. Open Heart. 2021;8(1):e001585. doi:10.1136/openhrt-2021-001585 Non-Database Included 1 article describes 1 strategy 32 Howlett JG. The time has finally come to prioritize medication initiation before dose titration for patients with heart failure and reduced ejection fraction. European Journal of Heart Failure. 2020;22(8):1483-1485. doi:10.1002/ejhf.1936 Database Included 1 article describes 1 strategy 33 Miller RJH, Howlett JG, Fine N. A Novel Approach to Medical Management of Heart Failure With Reduced Ejection Fraction. Canadian Journal of Cardiology. 2021;37(4):632-643. doi:10.1016/j.cjca.2020.12.028 Database Included 34 Hussein MTE, Negash S. Cluster Scheme Approach to Foundational Heart Failure With Reduced Ejection Fraction Non-Database Included 132 # Citation Source (Database or Non-Database) Verdict (Included or excluded) Reasons for exclusion (If excluded) Combined into article (If included) Medication. The Journal for Nurse Practitioners. 2022;18(6):628-635. doi:10.1016/j.nurpra.2022.02.009 35 Sinagra G, Pagura L, Stolfo D, et al. Combining New Classes of Medications for HFrEF: from Trials to Clinical Practice. Eur J Intern Med. 2021;90:10-15. doi:10.1016/j.ejim.2021.05.017 Database Excluded Require inpatient initiation of 1 or multiple medication classes 36 Di Lenarda A, Di Tano G, Cipriani M, et al. [ANMCO Position paper: Double, triple or quadruple medication for heart failure with reduced ejection fraction. Current evidence and new strategies]. G Ital Cardiol (Rome). 2021;22(10):861-868. doi:10.1714/3666.36518 Database Included 1 article describes 1 strategy 37 Khan MS, Butler J, Greene SJ. Simultaneous or rapid sequence initiation of medical medications for heart failure: seeking to avoid the case of âtoo little, too late.â European Journal of Heart Failure. 2021;23(9):1514-1517. doi:10.1002/ejhf.2311 Database Included 1 article describes 1 strategy 38 Greene SJ, Butler J, Fonarow GC. Simultaneous or Rapid Sequence Initiation of Quadruple Medical Medication for Heart FailureâOptimizing Medication With the Need for Speed. JAMA Cardiology. 2021;6(7):743-744. doi:10.1001/jamacardio.2021.0496 Database Included 39 Brownell NK, Ziaeian B, Fonarow GC. The Gap to Fill: Rationale for Rapid Initiation and Optimal Titration of Comprehensive Disease-modifying Medical Medication for Heart Failure with Reduced Ejection Fraction. Card Fail Rev . 2021;7(e18). doi:10.15420/cfr.2021.18. Database Included 40 Tomasoni D, Fonarow GC, Adamo M, et al. Sodium-glucose co-transporter 2 inhibitors as an early, first-line medication in patients with heart failure and reduced ejection fraction. Eur J Heart Fail. 2022;24(3):431-441. doi:10.1002/ejhf.2397 Database Included 133 # Citation Source (Database or Non-Database) Verdict (Included or excluded) Reasons for exclusion (If excluded) Combined into article (If included) 41 Borovac JA. Early in-hospital initiation and optimization of comprehensive disease-modifying pharmacomedication in patients with heart failure with reduced ejection fraction: a time for the paradigm shift. Expert Review of Cardiovascular Medication. 2022;20(2):91-94. doi:10.1080/14779072.2022.2039626 Non-Database Excluded Require inpatient initiation of 1 or multiple medication classes 134 B.4 Table B4: Characteristics of included studies - Identification Overview Identification Reference Article type Year of publication Strategy name Strategy description 1. Shen, L. et al. 2022.53 Primary Research â Modelling study 2020 Sequence 1b Step 1: Initiate and titrate ARNI Step 2: Initiate and titrate BB Step 3: Initiate and titrate MRA Step 4: Initiate SGLT2I Sequence 2 Step 1: Initiate SGLT2I Step 2: Initiate and titrate MRA Step 3: Initiate and titrate ARNI Step 4: Initiate and titrate BB Sequence 3 Step 1: Initiate SGLT2I Step 2: Initiate and titrate MRA Step 3: Initiate and titrate BB Step 4: Initiate and titrate ARNI Sequence 4 Step 1: Initiate SGLT2I Step 2: Initiate and titrate MRA Step 3: Initiate and titrate BB Step 4: Initiate and titrate ARNI Sequence 5 Step 1: Initiate and titrate MRA Step 2: Initiate SGLT2I Step 3: Initiate and titrate BB Step 4: Initiate and titrate ARNI Sequence duo 1 Step 1: Initiate SGLT2I, MRA Step 2: Titrate MRA Step 3: Initiate and titrate BB Step 4: Initiate and titrate ARNI Sequence duo 2 Step 1: Initiate SGLT2I, MRA Step 2: Titrate MRA Step 3: Initiate and titrate ARNI Step 4: Initiate and titrate BB 135 Overview Identification Reference Article type Year of publication Strategy name Strategy description Sequence duo 3 Step 1: Initiate SGLT2I, BB Step 2: Titrate BB Step 3: Initiate and titrate MRA Step 4: Initiate and titrate ARNI Sequence duo 4 Step 1: Initiate BB, ARNI Step 2: Titrate BB, ARNI Step 3: Initiate SGLT2I Step 4: Initiate and titrate MRA Sequence duo 5 Step 1: Initiate MRA, BB Step 2: Titrate MRA, BB Step 3: Initiate SGLT2I Step 4: Initiate and titrate ARNI Sequence duo 6 Step 1: Initiate MRA, ARNI Step 2: Titrate MRA, ARNI Step 3: Initiate SGLT2I Step 4: Initiate and titrate BB 2. Packer, M., et al., 2021;24 McMurray, JJV., et al., 2021, 2022;25,34 Docherty, KF. et al., 2021;32 Lorke, A., et al., 2021.54 Viewpoint/ commentaries 2021 Rapid sequencing Step 1: Initiate BB and SGLT2I (1 - 2 weeks) Step 2: Initiate ARNI (or MRA) (1 - 2 weeks) Step 3: Initiate MRA (or ARNI) Step 4: Titrate ARNI, BB, MRA 3. Sharma, A. et al. 202233 Viewpoint/ commentaries 2022 Not reported Step 1: Initiate ARNI, BB (2-4 weeks) Step 2: Initiate MRA, SGLT2I & Titrate ARNI, BB Step 3: Titrate ARNI, BB, MRA (Titration details until completion are not provided) 136 Overview Identification Reference Article type Year of publication Strategy name Strategy description 4. Silva-Cardoso J, et al. 202126 Viewpoint/ commentaries 2021 Not reported Step 1: Initiate ARNI, BB (2 - 3 weeks) Step 2: Initiate MRA (2 â 3 weeks) Step 3: Initiate SGLT2I Step 4: Titrate ARNI (2 weeks â 1 visit) Step 5: Titrate BB (4 weeks â 2 visits) Step 6: Titrate MRA (2 weeks â 1 visit) 5. Straw, S. et al. 202135 Viewpoint/ commentaries 2021 Not reported Step 1: Initiate ARNI & SGLT2I (1 week) Step 2: Initiate BB & MRA Step 3: Titrate ARNI (2 visits), BB (3 visits), MRA (1 visit) 6. Howlett, JG., 2020;29 Miller, RJH., et al., 2021;27 El Hussein, MT., et al., 2022.36 Viewpoint/ commentaries 2020 Cluster Titration Scheme Step 1: Initiate SGLT2I, ARNI, BB (1-2 weeks) Step 2: Initiate MRA, Titrate BB (1-2 weeks) Step 3: Titrate ARNI, BB Step 4: Titrate MRA 7. Di Lenarda, A, et al. 202137 Viewpoint/ commentaries 2021 Not reported S1: Initiate ARNI (ACEI/ARB) +BB + SGLT2I S2: Initiate MRA S3: Titrate ARNI, MRA, BB 8. Brownell NK, et al. 202128; Khan MS , et al. 202131; Greene SJ, et al Viewpoint/ commentaries 2021 Simultaneous sequencing Step 1: Initiate ARNI, BB, MRA, SGLT2I (1 Week) Step 2: Titrate BB, continue ARNI, MRA (1 Week) 137 Overview Identification Reference Article type Year of publication Strategy name Strategy description 202130; Tomasoni, et al. 2022.38 Step 3: Titrate BB, ARNI, MRA (1-2 weeks) Step 4: Titrate BB, ARNI 138 B.5 Table B5: Characteristics of Included Studies - Categorization Reference Strategy Name Attributes Identity (& Number) of medications started during the first visit Order of initiation Timing of starting titration (relative to completing initiation) Characteristic of medications adjustment Average frequency of medications adjustment visits The minimum expected time to complete initiation of all medications The minimum expected time to complete titration of all medications 1. Shen, L. et al. 2022.53 Sequence 1b ARNI ARNI > BB > MRA > SGLT2I Before completing all 4-medication initiations Sequential Not reported 11 weeks 12 weeks Sequence 2 SGLT2I SGLT2I > MRA > ARNI > BB Not reported 11 weeks 12 weeks Sequence 3 SGLT2I SGLT2I > MRA > BB > ARNI Not reported 8 weeks 12 weeks Sequence 4 SGLT2I SGLT2I > BB > MRA > ARNI Not reported 7 weeks 12 weeks Sequence 5 MRA MRA > SGLT2I > BB > ARNI Not reported 7 weeks 12 weeks 139 Reference Strategy Name Attributes Identity (& Number) of medications started during the first visit Order of initiation Timing of starting titration (relative to completing initiation) Characteristic of medications adjustment Average frequency of medications adjustment visits The minimum expected time to complete initiation of all medications The minimum expected time to complete titration of all medications Sequence duo 1 MRA & SGLT2I SGLT2I = MRA > BB > ARNI Simultaneous Not reported 6 weeks 11 weeks Sequence duo 2 MRA & SGLT2I SGLT2I = MRA > ARNI > BB Not reported 7 weeks 11 weeks Sequence duo 3 SGLT2I & BB BB = SGLT2I > MRA > ARNI Not reported 6 weeks 11 weeks Sequence duo 4 BB & ARNI ARNI = BB > SGLT2I > MRA Not reported 6 weeks 8 weeks Sequence duo 5 SGLT2I & BB BB = MRA > SGLT2I >ARNI Not reported 5 weeks 10 weeks 140 Reference Strategy Name Attributes Identity (& Number) of medications started during the first visit Order of initiation Timing of starting titration (relative to completing initiation) Characteristic of medications adjustment Average frequency of medications adjustment visits The minimum expected time to complete initiation of all medications The minimum expected time to complete titration of all medications Sequence duo 6 MRA & ARNI ARNI = MRA > SGLT2I > BB Not reported 6 weeks 10 weeks 2. Packer, M., et al., 2021;24 McMurray, JJV., et al., 2021, 2022;25,34 Docherty, KF. et al., 2021;32 Lorke, A., et al., 2021.54 Rapid sequencing SGLT2I & BB BB = SGLT2I > ARNI > MRA After completing all 4-medication initiations Not reported Every 1-2 weeks 2-4 weeks Not reported 3. Sharma, A. et al. 202233 Not reported ARNI & BB ARNI = BB > SGLT2I = MRA After completing all 4-medication initiations Simultaneous Every 2-4 weeks 2-4 weeks Not reported 141 Reference Strategy Name Attributes Identity (& Number) of medications started during the first visit Order of initiation Timing of starting titration (relative to completing initiation) Characteristic of medications adjustment Average frequency of medications adjustment visits The minimum expected time to complete initiation of all medications The minimum expected time to complete titration of all medications 4. Silva-Cardoso, J. et al. 202126 Not reported ARNI & BB ARNI = BB > MRA > SGLT2I After completing all 4-medication initiations Sequential Every 2-3 weeks 4-6 weeks 12-14 weeks (8 weeks up-titration) 5. Straw, S. et al. 202135 Not reported SGLT2I & ARNI SGLT2I = ARNI > BB = MRA After completing all 4-medication initiations Simultaneous Not reported âWithin first few weeksâ Not reported 6. Howlett, JG., 2020;29 Miller, RJH., et al., 2021;27 El Hussein, MT., et al., 2022.36 Cluster Titration Scheme ARNI & SGLT2I & BB ARNI = BB = SGLT2I > MRA After completing all 4-medication initiations Simultaneous Every 1-2 weeks 1-2 weeks â¤12 weeks 7. Di Lenarda, Not reported ARNI & BB & SGLT2I ARNI = BB = SGLT2I > MRA After completing all Not reported Every 2-4 weeks 4-8 weeks Not reported 142 Reference Strategy Name Attributes Identity (& Number) of medications started during the first visit Order of initiation Timing of starting titration (relative to completing initiation) Characteristic of medications adjustment Average frequency of medications adjustment visits The minimum expected time to complete initiation of all medications The minimum expected time to complete titration of all medications A, et al. 202137 4-medication initiations 8. Brownell, NK. et al. 2021,28 Khan, MS. et al. 2021,31 Greene, SJ. et al. 2021,30 Tomasoni, et al. 2022.38 Simultaneous sequencing ARNI & BB & SGLT2I & MRA ARNI = BB = SGLT2I = MRA After completing all 4-medication initiations Simultaneous Every 1-2 weeks Immediately 8 weeks (2 months) 143 B.6 Table B6: Characteristics of Included Studies - Rationalization Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration 1. Shen, L. et al., 2022.53 Sequence 1b âIf it is accepted that each of these five life-saving therapies acts independently and that their effects are additive, then the goal should be to start as many therapies as quickly as possible, especially as each of them exhibits benefit early after initiation (within <30 days). A relevant consideration here is the number of titration steps and the time taken to achieve the evidence-based dose. Clearly, this varies greatly between, for example, beta-blockers and SGLT2 inhibitors (SGLT2I), where the former requires up to four titration steps, over 6â12 weeks, and the latter is used in a single fixed dose for all patients.â Not reported Sequence 2 Sequence 3 Sequence 4 Sequence 5 Sequence duo 1 Sequence duo 2 Sequence duo 3 Sequence duo 4 Sequence duo 5 Sequence duo 6 144 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration 2. Packer, M., et al., 2021;24 McMurray, JJV., et al., 2021, 2022;25,34 Docherty, KF. et al., 2021;32 Lorke, A., et al., 2021.54 Rapid sequencing âFourth, the proper sequencing of drug classes can improve safety and tolerability. Specifically, neprilysin inhibition can reduce the risk of renal insufficiency produced by an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and both neprilysin inhibitors and SGLT2 inhibitors can minimize the risk of hyperkalemia with the use of MRAs.â25 âStep 1 is simultaneous initiation of treatment with a β-blocker and an SGLT2I. β-Blockers are (arguably) our single most effective drug class for the treatment of HFrEF, particularly with respect to the reduction of sudden death. SGLT2Is have a striking effect to reduce the risk of hospitalizations for heart failure, and this benefit (potentially acting in concert with their early diuretic action) may mitigate the short-term risk of worsening heart failure that may occur after a β-blocker is started.â 25 âAdditionally, among the four foundational drug classes, beta-blockers are most likely to exert favorable effects on left ventricular remodeling during long-term treatment, yielding important recovery of a depressed ejection fraction.â24 âtreatment with a beta-blocker and an SGLT2 inhibitor does not require specialized safety monitoring or laboratory testing. As a result, the ability of patients to tolerate a combination of a beta-blocker and an SGLT2 inhibitor can generally be fully âSecond, low starting doses of foundational drugs are effective in reducing morbidity and mortality.â 25 âThird, the addition of a new drug class yields benefits that are greater in magnitude than up-titration of existing drug classes.â 25 âFifth, and importantly, because much of the benefits of foundational treatments are seen within 30 days of initiating treatment, the algorithm should achieve therapy with all 4 classes of drugs within 4 weeks.â 25 âUsed in appropriate patients, the approach outlined achieves treatment with all 4 foundational treatments within 4 weeks. Up-titration to target doses should be pursued thereafter. This sequencing maximizes the likelihood that highly effective therapies will be implemented in a manner that rapidly prevents deaths and hospitalizations and enhances the tolerability of concurrently or subsequently administered treatments.â 25 145 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration established within 2 weeks of starting outpatient treatment with both classes of drugs.â 24 âSacubitril/valsartan has a rapid and profound effect to lower natriuretic peptides, a biomarker of cardiac wall stress, which may portend a beneficial effect on cardiac remodelingâ¦Adding a neprilysin inhibitor to an angiotensin receptor blocker greatly enhances the therapeutic effects of a conventional inhibitor of the reninâangiotensin system, while minimizing the possibility that inhibition of the reninâangiotensin system can worsen renal function. Furthermore, neprilysin inhibition can prevent the excess hyperkalemia that can be seen with a mineralocorticoid receptor antagonist.â 24 âThe favorable effects of neprilysin inhibitors and SGLT2I to improve renal function and potassium homeostasis may increase the tolerability of MRAs. MRAs may be step 2 in a patient with troublesome hypotension.â 25 âSpironolactone and eplerenone reduce morbidity and mortality (including a benefit on sudden cardiac death), and major advantages of these drugs include once-daily dosing, minimal up-titration and a modest effect on blood pressure; however, treatment with mineralocorticoid receptor antagonists can worsen renal function and produce hyperkalaemia. Therefore, when starting a mineralocorticoid receptor antagonist, it seems advisable to have patients treated with a 146 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration neprilysin inhibitor and an SGLT2 inhibitor, since these two drugs may mitigate the effect of spironolactone and eplerenone to worsen azotaemia and increase serum potassium, and thereby, increase the likelihood that patients can be maintained on long-term treatment with a mineralocorticoid receptor antagonist.â 24 3. Sharma, A., et al., 2022.33 Titration Strategies by Clinical Scenario - de novo non-ischemic heart failure with reduced ejection fraction âInitiation of multiple therapies upfront, specifically ARNI and SGLT2I, rather than sequentially, may facilitate stabilization of potassium and kidney function to enable initiation of MRAs in the future.â âThe first consideration is that these therapies reduce morbidity and mortality very rapidly after initiation, thus emphasizing the need to add multiple classes of therapy in rapid succession. Furthermore, each therapy has a treatment effect that is independent of dose or prior initiation of other therapies. In addition, low doses of each of the pillars of the quadruple therapies have additive therapeutic efficacy; initiating low doses of all 4 categories of quadruple therapies should be prioritized over strict sequencing and dose escalation as recommended by the historical therapy paradigm. Finally, most recommendations for rapid therapy sequencing suggest that all therapy classes, in the absence of any contraindications, should be initiated within 4 weeks of identification of HFrEF.â 4. Silva-Cardoso, J, et al., 2021.26 A three-step sequence for the initiation of the four foundational drugs for âThis proposal of the Portuguese HF Expert Panel for a HFrEF drug initiation algorithm builds on the McMurray and Packerâs paper, the 2021 update to the 2017 ACC HF Expert Consensus, the 2021 update to the CCS/CHFS Heart Failure Guidelines, and the 2021 ESC/HFA Heart Failure Guidelines preview.â ââ¢ Time matters when initiating HFrEF disease-modifying therapy, since ARNI, BB, MRA, and SGLT2I all show a positive prognostic impact as early as a few weeks after the initiation of therapy; â¢ The combined action of two disease-modifying drugs at low doses shows a higher prognostic impact than a high dose of a single drug;â 147 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration non-diabetic patients ââ¢ In HFrEF patients, sacubitril/valsartan is clearly superior to ACEI in terms of prognostic impact; â¢ dapagliflozin or empagliflozin, on top of optimized HfrEF therapy (ACEI/ARB/ARNI+BB+MRA) further reduce the risk of HF-hospitalisations and cardiovascular mortality, regardless of the presence of diabetes.â âFor HFrEF patients with no T2D, a three-step disease modifying drug initiation with a SGLT2I on top of ARNI, BB and MRA, is recommended.â âStep 1 is in line with the 2021 guidelines of the American Diabetes Association which, as mentioned above, recommends timely SGLT2I therapy for T2D with HF. For HFrEF patients with no T2D, a three-step disease modifying drug initiation with a SGLT2I on top of ARNI, BB and MRA, is recommended.â âIn summary, we recommend that the traditional start low and go slow HFrEF therapy initiation aphorism be changed to a start low and add fast strategy, which means starting the four foundational HF disease-modifying drug classes within a four to six week interval. This initial effort should be implemented at low drug doses. Dose up-titration follows thereafter, as quickly as possible, guided by an effective safety monitoring protocol.â âAnother important concept is that time is of essence when targeting better outcomes for HFrEF patients. Thus, ideally, all four drug classes should be introduced at a low dose during a four to six week period and up-titrated thereafter during a period of 8 week.â âIn HF, SGLT2I up-titration is not required. For the other three disease-modifying drug classes, we recommend uptitrating one drug at a time, to minimize the occurrence of complications. Up-titration steps for each drug should occur every two weeks at an in-person visit. Considering on average, one up-titrating step for ARNI, two for BBs and one for MRAs, most HFrEF patients may initiate and fully uptitrate all four disease-modifying drugs within a 12 to 14 week period.â 5. Straw, S. et al., 2021.35 Not reported âInitiating ARNI at the point of diagnosis would mitigate the risk of inertia while also providing a more effective treatment to patients during the period of highest risk.â âThis attempt to avoid âunnecessaryâ treatments in patients who ârespondâ but has several important limitations. First, while guidelines do not stipulate a time interval between alterations to therapy, the need for further assessment and re-evaluation of LV function inevitably results in delays 148 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration âLack of dosing considerations and clear evidence from randomised trials of an early beneficial effect, SGLT2i are an obvious first choice It seems likely that impairment of renal function following up-titration of ARNI and MRA will become lesser concerns following the introduction of SGLT2I.â initiating additional agents as well as contributing further follow-up and imaging costs. In clinical practice it typically takes many months before patients receive optimised doses of these medications, and many never do, even where integrated hospital and community care is available.â âIt remains the case, that very few patients become asymptomatic with even optimal doses of disease-modifying therapy suggesting that slow up-titration, followed by a decision to embark on the next step based on symptoms is folly.â 6. Howlett, JG., 2020;29 Miller, RJH., et al., 2021;27 El Hussein, MT., et al., 2022.36 Cluster Titration Scheme âAt each clinical interaction, efforts should be made to initiate or titrate a drug within each cluster. For most nonfrail patients, this will result in 3 medication adjustments per interaction.â 27 âChanges are made with one eligible medication in each group, to a maximum of three changes per visit, with an attempt to initiate/titrate the other eligible medication in that group during the next visit. At each visit, the medication deemed easiest/safest to alter would be the preferred option during that visit, with a default to alternate changes when possible. In this manner, all appropriate evidence-based therapies are initiated within two visits. This approach emphasizes to the patient that HFrEF is a combination medication condition, not unlike many cancers, and avoids the perception of the need for patients to âfailâ early therapy as a condition to receive optimal medical therapyâ29 âOur preferred drug for each cluster includes SGLT2I (excepting the need for diuretic manipulation symptoms of congestion or evidence of volume depletion) in Cluster A, ARNI (excepting hypotension) for Cluster B, and b-blocker for Cluster C.* For Cluster C, rapid and progressive b-blocker titration to target dose is preferred before use of ivabradine.â 27 âBased on cluster approach, it is possible to adjust dose of medications with different neurohormonal effect in the same visit.â âTitration within each medication class should be no more frequent than every 1 to 2 weeks to limit side effects but should not be longer to achieve full titration within 12 weeks.â27 149 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration âMedications with similar effects/side effects can be grouped together into three groups â group 1 for drugs with diuretic effects (loop diuretics, SGLT2I), group 2 for drugs directly affecting renal/potassium metabolism (ARNI and MRAs), and group 3 for drugs directly affecting blood pressure or heart rate (BB, sinus node inhibitors). Importantly, ARNI therapy replaces ACEI/ARB therapy as the superior first-line therapy.â29 âTitration protocols of landmark trials supporting quadruple medication mandated completion of titration within 2 to 3 monthsâ.27,93,98 âSlow optimization of HF medications postpones initiation other life-prolonging medical therapies as well as device therapies, creating an unnecessary window of excess risk.â âHowever, the rationale for sequential initiation of medical therapy is related to avoiding potentially unnecessary costs associated with newer therapies, which is mitigated by an increased number of clinic visits and testing.â 27 âMedication initiation strategies that rely on patient response, either in terms of LVEF recovery or symptom status, may unnecessarily deprive patients of beneficial therapies and induce delays in medication titration.â 27 ââ¦a strategy of single-drug initiation and titration before addition of other drug classes, which may contribute to less comprehensive treatment and slower times to medical optimization.â 27 7. Di Lenarda, A., et al. , 2021.37 Not reported âThe immediate initiation of SGLT2 inhibitors facilitates the rapid initiation of aldosterone inhibitors in the following weeks, with a lower risk of hyperkalemia and worsening renal function. This way, the patient would already be protected by some form of quadruple treatment in the first month, albeit imperfect.â âThe sequence of drug implementation can instead impact drug safety and tolerability, particularly in patients with acute heart failure. Tolerability may also âOn the other hand, the additional effect obtainable by increasing the dose of ACE inhibitors, sartans, or beta-blockers from low to high is not so evident. In reality, the favorable effect of cornerstone drugs in HFrEF, initiated simultaneously or in rapid succession, seems to be already present and additive at low doses.â âCompared to the conventional strategy (sequential initiation of individual drugs with titration to the target dose) (Figure 2A), this innovative scheme (rapid stepwise initiation of quadruple therapy at low doses) (Figure 2B-150 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration vary depending on the sequence of initiation of different drugs. The early use of low-dose ARNI and/or SGLT2 inhibitors reduces the risk of hyperkalemia or worsening of renal insufficiency from aldosterone antagonists, the opposite risk for starting an aldosterone antagonist in patients on ACE inhibitors or ARB Starting an RAAS in patients with advanced heart failure could improve hemodynamic tolerability to beta-blockers. On the contrary, the start of a single SRA inhibitor drug, titrated to the maximum dose, can preclude the initiation of other drugs due to hypotension.â C) is based on solid considerations regarding the possibility of maximizing the effect and the speed of achieving clinical benefit.â 8. Greene, SJ., et al., 202130; Khan, MS., et al., 202131; Brownell, NK., et al., 202128; Tomasoni, et al., 2022.38 Simultaneous sequencing âSimultaneous or rapid sequence initiation of quadruple therapy seeks to break clinical inertia and treats HFrEF with the urgency it deserves.â30 âSimultaneous rapid sequence initiation and titration leverages the early clinical benefits of each individual therapy and seeks to treat heart failure with reduced ejection fraction (HFrEF) with the urgency it deserves.â31 âSimultaneous initiation and continuation of each medication may improve tolerance, adherence, and persistence to the quadruple therapy regimen.â30 âUp-front immediate initiation of comprehensive disease-modifying quadruple therapy and subsequent prompt dose up-titration leverages the fact that (i) each member of quadruple therapy substantially reduces risk for death and hospitalization within days to weeks of initiation, and (ii) risk reductions with each individual therapy are substantial and fully additive.â 31 âSwitching from angiotensin-converting enzyme inhibitors (ACEI) to ARNI therapy decreases risk of hyperkalemia, which may favor less discontinuation of MRA. Likewise, use of SGLT2i may decrease risk of hyperkalemia. Additionally, SGLT2I therapy slows âClinicians may have concerns that simultaneous initiation of all 4 or multiple HFrEF therapies may increase risk for adverse events or medication intolerance. â¦ Yet, worsening of the underlying HFrEF disease state may be misattributed as a medication-associated adverse event, and disease-state worsening is more likely to occur if initiation of any of these 151 Reference Strategy Name Rationales Rationales for the order of medication prioritization Rationales for the timing and characteristics of initiation and titration progression of kidney dysfunction, which may enable persistence of ARNI and MRA therapy.â30 âIn the context of high rates of drug discontinuation in the current study, simultaneous or very early use of quadruple therapy should be considered as a strategy for maximizing overall tolerance to the four-drug regimen. For example, multiple studies have suggested that apart from exposing patients to excess risk of death and hospitalization, delaying initiation of SGLT2i and delaying a switch from ACEI to ARNI may needlessly expose patients to excess risk of hyperkalaemia and risk of MRA discontinuation.â 31 âTreatment with an ARNI, compared to an ACEI, has less risk of severe hyperkalaemia, which could reduce discontinuation of an MRA. Treatment with an SGLT2i reduces the worsening of renal function and delays progression to end-stage renal disease, which may allow for longer usage of ARNIs and MRAs.â28 â(SGLT2I) embody most of the ideal characteristics for a HFrEF medication, including single dose, once daily administration, no need for titration, early beneficial effects on clinical events and patient-reported quality of life, and favourable safety and tolerability profile.â38 medications is delayedâ¦delaying initiation exposes patients to excess risk of clinical worsening and death and the possibility of never having the medication prescribedâ30 âThe goal is to immediately provide eligible patients the opportunity to benefit from lifesaving therapy, rather than needlessly withholding medications and exposing patients to excess risk of clinical worsening or subsequent development of medication contraindications.â 31 âThere is no evidence to suggest that the traditional and needlessly protracted and sequential approach to GDMT titration accomplishes anything beneficial, and there is no evidence that this approach improves medication tolerance.â 31 âWhile some may feel uncomfortable with a rapid initiation of multiple medications for HFrEF, there is no evidence to date that suggests such a strategy would produce adverse events; in fact, a delay in treatment would lead to unnecessary clinical worsening and cardiovascular death.â 28 152 Appendix C - Modeling study C.1 Table C1: Inputs for one-way sensitivity analysis Parameter/Variables Value Lower Upper Note HF Hospitalization (HFH) incidence rate (S -> HFH) 0.006768 0.003384 0.010152 ± 50% Value All-cause mortality incidence rate (S -> M) â¢ In-trial SOLVD (0-4 year) 0.003265156 0.001632578 0.004897734 ± 50% Value â¢ Follow-up SOLVD (4-12 year & longer) 0.002715964 0.001357982 0.004073946 ± 50% Value In-Hospital mortality incidence rate (HFH -> M) 0.089925 0.0449625 0.1348875 ± 50% Value Hypotension rate 0.000463 0.0002315 0.0006945 ± 50% Value Bradycardia rate 0.000177 0.0000885 0.0002655 ± 50% Value Hyperkalemia rate 0.000026 0.000013 0.000039 ± 50% Value Renal impairment rate 0.001168 0.000584 0.001752 ± 50% Value Discount rate 1.5% 0% 3% Cost of HFH $14,194 $7,097 $21,291 ± 50% Value Cost of medication adjustment $36.47 18.235 54.705 ± 50% Value 153 C.2 Table C2: Inputs for scenario analyses Variable set Description Base scenario Scenario 1 Scenario 2 RR_BradyC_sub_BB Risk ratio for bradycardia sub-dose BB 3.542853538 3.542853538 1 RR_HyperK_sub_ACEI Risk ratio for hyperkalemia sub-dose ACEI 2.255681785 2.255681785 1 RR_HyperK_sub_ARNI Risk ratio for hyperkalemia sub-dose ARNI 2.465944765 2.465944765 1 RR_HyperK_sub_MRA Risk ratio for hyperkalemia sub-dose MRA 2.034416007 2.034416007 1 RR_HypoT_sub_ACEI Risk ratio for hypotension sub-dose ACEI 1.49368262 1.49368262 1 RR_HypoT_sub_ARNI Risk ratio for hypotension sub-dose ARNI 2.321153199 2.321153199 1 RR_HypoT_sub_BB Risk ratio for hypotension sub-dose BB 1.243320781 1.243320781 1 RR_ReImp_sub_ACEI Risk ratio for renal impairment sub-dose ACEI 1.334772687 1.334772687 1 RR_ReImp_sub_ARNI Risk ratio for renal impairment sub-dose ARNI 1.249512511 1.249512511 1 RR_S_HFH_sub_ACEI Risk ratio for HFH sub-dose ACEI 0.817529758 0.817529758 1 RR_S_HFH_sub_ARNI Risk ratio for HFH sub-dose ARNI 0.561301118 0.561301118 1 RR_S_HFH_sub_BB Risk ratio for HFH sub-dose BB 0.631172914 0.631172914 1 RR_S_HFH_sub_MRA Risk ratio for HFH sub-dose MRA 0.80203647 0.80203647 1 RR_S_M_sub_ACEI Risk ratio for mortality sub-dose ACEI 0.89595941 0.89595941 1 RR_S_M_sub_ARNI Risk ratio for mortality sub-dose ARNI 0.721301212 0.721301212 1 RR_S_M_sub_BB Risk ratio for mortality sub-dose BB 0.651424223 0.651424223 1 RR_S_M_sub_MRA Risk ratio for mortality sub-dose MRA 0.830369733 0.830369733 1 dose_adjustment_duration Duration of medication adjustment 53 13 53 154 C.3 Table C3: Benefit-harm analysis â Base scenario Base Scenario (No PSA) Mean values per 10,000 patients/trials QALYs Life years Number of HFH Number of bradycardia Number of hypotension Number of hyperkalemia Number of renal impairment âUntreatedâ 3.514 5.785 2.531 - - - - Profile 1a 8.884 16.280 2.137 0.0260 0.0571 0.0046 0.0594 Profile 1b 8.967 16.434 2.130 0.0278 0.0632 0.0050 0.0529 Profile 2a 8.939 16.377 2.118 0.0232 0.0615 0.0048 0.0447 Profile 2b 9.006 16.506 2.126 0.0263 0.0651 0.0047 0.0457 Profile 3a 9.046 16.580 2.130 0.0291 0.0666 0.0049 0.0463 Profile 3b 9.052 16.591 2.130 0.0289 0.0675 0.0050 0.0466 Profile 4a 9.049 16.587 2.133 0.0291 0.0682 0.0051 0.0492 Profile 4b 9.050 16.586 2.130 0.0291 0.0680 0.0051 0.0477 Profile 5a 9.049 16.586 2.129 0.0290 0.0680 0.0050 0.0467 Profile 5b 9.052 16.591 2.129 0.0290 0.0681 0.0050 0.0467 Profile 6a 9.054 16.595 2.129 0.0290 0.0681 0.0051 0.0467 Profile 6b 9.055 16.597 2.130 0.0290 0.0682 0.0051 0.0467 155 C.4 Table C4: Benefit-harm analysis â Scenario 1 Scenario 1 (Deterministic) Mean values per 10,000 patients/trials QALYs Life years Number of HFH Number of bradycardia Number of hypotension Number of hyperkalemia Number of renal impairment âUntreatedâ 3.514 5.785 2.531 - - - - Profile 1a 5.942 10.283 2.454 0.0052 0.0104 0.0005 0.0199 Profile 1b 8.872 16.250 2.147 0.0068 0.0130 0.0006 0.0192 Profile 2a 8.832 16.178 2.131 0.0024 0.0112 0.0004 0.0115 Profile 2b 9.009 16.530 2.137 0.0052 0.0144 0.0005 0.0121 Profile 3a 9.048 16.602 2.140 0.0079 0.0159 0.0006 0.0126 Profile 3b 9.054 16.614 2.140 0.0078 0.0167 0.0007 0.0129 Profile 4a 9.046 16.599 2.140 0.0078 0.0175 0.0007 0.0155 Profile 4b 9.055 16.615 2.140 0.0078 0.0173 0.0007 0.0140 Profile 5a 9.054 16.614 2.139 0.0078 0.0173 0.0007 0.0130 Profile 5b 9.060 16.625 2.140 0.0078 0.0174 0.0007 0.0130 Profile 6a 9.061 16.627 2.140 0.0078 0.0174 0.0008 0.0130 Profile 6b 9.062 16.629 2.140 0.0078 0.0174 0.0008 0.0130 156 C.5 Table C5: Cost-effectiveness ranking â Scenario 1 Category Dominance Strategy Cost ÎCost QALYs ÎQALYs ICER NMB Excluding dominated undominated Profile 1a 31,720.75 5.94 265,366.17 Excluding dominated undominated Profile 3a 82,631.40 50,910.64 9.05 3.11 16,389.60 369,769.40 Excluding dominated undominated Profile 6a 82,844.03 212.63 9.06 0.01 16,775.05 370,190.54 Excluding dominated undominated Profile 6b 83,102.71 258.68 9.06 0.00 190,345.26 369,999.81 All undominated Profile 1a 31,720.75 5.94 265,366.17 All abs. dominated âUntreatedâ 32,726.92 1,006.17 3.51 -2.43 -414.52 142,994.49 All ext. dominated Profile 2a 80,936.16 49,215.41 8.83 2.89 17,029.05 360,655.03 All ext. dominated Profile 1b 81,151.82 215.66 8.87 0.04 5,408.81 362,433.00 All ext. dominated Profile 2b 82,538.37 1,386.55 9.01 0.14 10,107.84 367,905.23 All undominated Profile 3a 82,631.40 50,910.64 9.05 3.11 16,389.60 369,769.40 All abs. dominated Profile 4a 82,662.63 31.23 9.05 0.00 -14,496.87 369,630.44 All ext. dominated Profile 5a 82,790.47 159.07 9.05 0.01 26,840.44 369,906.66 All undominated Profile 6a 82,844.03 212.63 9.06 0.01 16,775.05 370,190.54 All abs. dominated Profile 3b 82,967.76 123.74 9.05 -0.01 -18,653.35 369,735.14 All abs. dominated Profile 4b 83,005.49 161.46 9.05 -0.01 -26,357.71 369,722.79 All abs. dominated Profile 5b 83,080.49 236.46 9.06 0.00 -234,580.32 369,903.69 All undominated Profile 6b 83,102.71 258.68 9.06 0.00 190,345.26 369,999.81 157 C.6 Table C6: Probabilistic sensitivity analysis â Scenario 1 Scenario 1 (Probabilistic) Mean values per 1,000 samples & 10,000 patients/trials NMB 95% Lower Bound 95% Upper Bound Cost 95% Lower Bound 95% Upper Bound QALYs 95% Lower Bound 95% Upper Bound % Optimal âUntreatedâ 143,456.63 142,228.99 144,684.27 35,479.21 34,365.27 36,593.16 3.579 3.567 3.590 0.00% Profile 1a 268,514.74 266,970.70 270,058.79 33,612.33 32,629.60 34,595.05 6.043 6.018 6.067 0.10% Profile 1b 368,881.47 366,362.41 371,400.54 81,961.84 80,392.72 83,530.96 9.017 8.974 9.060 0.00% Profile 2a 366,109.30 363,590.86 368,627.74 81,415.64 79,850.62 82,980.66 8.950 8.907 8.994 0.00% Profile 2b 373,549.78 370,980.37 376,119.19 83,009.04 81,415.94 84,602.13 9.131 9.087 9.175 0.00% Profile 3a 375,268.11 372,687.87 377,848.35 83,053.94 81,454.81 84,653.07 9.166 9.122 9.211 0.60% Profile 3b 375,350.70 372,767.31 377,934.09 83,403.57 81,801.88 85,005.27 9.175 9.131 9.219 0.30% Profile 4a 375,473.95 372,891.66 378,056.24 83,144.80 81,542.19 84,747.42 9.172 9.128 9.217 3.10% Profile 4b 375,448.57 372,864.11 378,033.02 83,458.48 81,854.75 85,062.20 9.178 9.134 9.222 0.00% Profile 5a 375,730.54 373,145.08 378,316.00 83,268.73 81,664.42 84,873.04 9.180 9.136 9.224 2.00% Profile 5b 375,578.91 372,992.56 378,165.26 83,527.02 81,922.49 85,131.56 9.182 9.138 9.226 0.50% Profile 6a 375,891.36 373,305.00 378,477.71 83,297.33 81,692.55 84,902.12 9.184 9.139 9.228 85.50% Profile 6b 375,714.53 373,127.79 378,301.28 83,554.20 81,949.23 85,159.17 9.185 9.141 9.230 7.90% 158 C.7 Table C7: Benefit-harm analysisâ Scenario 2 Scenario 2 (Deterministic) Mean values per 10,000 patients/trials QALYs Life years Number of HFH Number of bradycardia Number of hypotension Number of hyperkalemia Number of renal impairment âUntreatedâ 3.514 5.785 2.531 - - - - Profile 1a 8.796 16.118 2.135 0.0227 0.0534 0.0040 0.0573 Profile 1b 8.923 16.350 2.129 0.0252 0.0607 0.0049 0.0515 Profile 2a 8.878 16.265 2.122 0.0213 0.0562 0.0046 0.0440 Profile 2b 8.973 16.444 2.124 0.0251 0.0625 0.0048 0.0449 Profile 3a 8.923 16.353 2.120 0.0236 0.0603 0.0047 0.0442 Profile 3b 9.003 16.502 2.130 0.0268 0.0646 0.0049 0.0450 Profile 4a 8.905 16.318 2.123 0.0229 0.0605 0.0048 0.0467 Profile 4b 8.996 16.489 2.132 0.0263 0.0648 0.0050 0.0458 Profile 5a 8.948 16.398 2.123 0.0255 0.0608 0.0047 0.0440 Profile 5b 9.016 16.526 2.130 0.0282 0.0644 0.0048 0.0454 Profile 6a 8.966 16.432 2.124 0.0258 0.0632 0.0048 0.0444 Profile 6b 9.026 16.543 2.130 0.0282 0.0651 0.0049 0.0458 159 C.8 Table C8: Cost-effectiveness ranking â Scenario 2 Category Dominance Strategy Cost ÎCost QALYs ÎQALYs ICER NMB Excluding dominated undominated âUntreatedâ 32,726.92 3.51 142,994.49 Excluding dominated undominated Profile 1a 80,474.04 47,747.12 8.80 5.28 9,040.32 359,326.14 Excluding dominated undominated Profile 6a 82,852.76 2,378.71 8.97 0.17 13,958.50 365,468.08 Excluding dominated undominated Profile 6b 84,208.80 1,356.04 9.03 0.06 22,604.68 367,111.51 All undominated âUntreatedâ 32,726.92 3.51 142,994.49 All undominated Profile 1a 80,474.04 47,747.12 8.80 5.28 9,040.32 359,326.14 All ext. dominated Profile 2a 81,890.44 1,416.40 8.88 0.08 17,259.22 362,013.05 All ext. dominated Profile 4a 82,383.38 492.93 8.91 0.03 17,985.13 362,890.51 All ext. dominated Profile 3a 82,395.97 12.59 8.92 0.02 699.07 363,778.61 All ext. dominated Profile 5a 82,730.32 334.36 8.95 0.02 13,547.81 364,678.24 All abs. dominated Profile 1b 82,804.51 74.18 8.92 -0.03 -2,917.59 363,332.77 All undominated Profile 6a 82,852.76 2,378.71 8.97 0.17 13,958.50 365,468.08 All ext. dominated Profile 2b 83,603.11 750.35 8.97 0.01 112,368.94 365,051.61 All ext. dominated Profile 3b 83,974.43 371.32 9.00 0.03 12,397.00 366,177.91 All abs. dominated Profile 4b 83,994.89 20.47 9.00 -0.01 -2,766.61 365,787.56 All ext. dominated Profile 5b 84,145.71 171.29 9.02 0.01 12,864.01 366,672.38 All undominated Profile 6b 84,208.80 1,356.04 9.03 0.06 22,604.68 367,111.51 160 C.9 Table C9: Probabilistic sensitivity analysis â Scenario 2 Scenario 2 (Probabilistic) Mean values per 1,000 samples & 10,000 patients/trials NMB 95% Lower Bound 95% Upper Bound Cost 95% Lower Bound 95% Upper Bound QALYs 95% Lower Bound 95% Upper Bound % Optimal âUntreatedâ 143,456.63 142,228.99 144,684.27 35,479.21 34,365.27 36,593.16 3.58 3.57 3.59 0.00% Profile 1a 365,502.43 363,008.75 367,996.11 81,190.71 79,647.40 82,734.01 8.93 8.89 8.98 0.10% Profile 1b 368,993.18 366,454.03 371,532.32 83,437.87 81,864.45 85,011.30 9.05 9.01 9.09 0.00% Profile 2a 367,870.68 365,332.00 370,409.37 82,523.59 80,950.75 84,096.42 9.01 8.96 9.05 0.00% Profile 2b 370,514.49 367,950.53 373,078.46 84,155.28 82,565.85 85,744.72 9.09 9.05 9.14 0.10% Profile 3a 369,768.58 367,214.33 372,322.83 83,088.21 81,502.72 84,673.69 9.06 9.01 9.10 0.00% Profile 3b 371,473.60 368,900.92 374,046.28 84,442.60 82,847.06 86,038.14 9.12 9.07 9.16 0.00% Profile 4a 368,832.47 366,284.05 371,380.89 83,083.90 81,497.99 84,669.82 9.04 8.99 9.08 0.00% Profile 4b 370,990.80 368,420.81 373,560.79 84,446.92 82,850.96 86,042.88 9.11 9.06 9.15 0.00% Profile 5a 370,669.34 368,106.62 373,232.06 83,385.16 81,792.67 84,977.65 9.08 9.04 9.13 0.00% Profile 5b 371,918.73 369,340.94 374,496.52 84,605.57 83,006.65 86,204.49 9.13 9.09 9.17 0.30% Profile 6a 371,380.44 368,813.50 373,947.38 83,479.20 81,884.76 85,073.63 9.10 9.05 9.14 5.80% Profile 6b 372,445.67 369,865.20 375,026.14 84,690.88 83,090.47 86,291.30 9.14 9.10 9.19 93.70% 161 C.10 Figure C1: Cost-effectiveness acceptability curve â Scenario 1 PSA A cost-effectiveness acceptability curve was generated to visualize the results of the 1,000 samples conducted in the probabilistic sensitivity analysis. The x-axis indicates the WTP range ($0-$100,000/QALY), while the y-axis represents the proportion (%) of samples a profile has the highest NMB, indicating the probability of one profile being the most cost-effective strategy at that particular WTP. The profile that is most likely to be cost-effective at a certain WTP will have its curve on top of the others. 162 C.11 Figure C2: Cost-effectiveness acceptability curve â Scenario 2 PSA A cost-effectiveness acceptability curve was generated to visualize the results of the 1,000 samples conducted in the probabilistic sensitivity analysis. The x-axis indicates the WTP range ($0-$100,000/QALY), while the y-axis represents the proportion (%) of samples a profile has the highest NMB, indicating the probability of one profile being the most cost-effective strategy at that particular WTP. The profile that is most likely to be cost-effective at a certain WTP will have its curve on top of the others.
Thesis/Dissertation
eng
Pharmaceutical Sciences
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Turgeon, Ricky
Loewen, Peter
An analysis of heart failure reduced ejection fraction pharmacotherapy sequencing strategies
Text