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Drug use patterns associated with risk of non-adherence to antiretroviral therapy among HIV-positive… Azar, Pouya; Wood, Evan; Nguyen, Paul; Luma, Maxo; Montaner, Julio; Kerr, Thomas; Milloy, M-J Apr 18, 2015

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RESEARCH ARTICLE Open AccessDrug use patterns associareJuThe development of antiretroviral therapy (ART) has led and morbidity [3] and elevated rates of viral resistanceAzar et al. BMC Infectious Diseases  (2015) 15:193 DOI 10.1186/s12879-015-0913-02Division of AIDS, Department of Medicine, University of British Columbia,Vancouver, BC, Canadato substantial declines in HIV/AIDS-associated morbid-ity and mortality among many groups in many settingsworldwide [1]. Adherence to ART is the primary factordetermining the degree and durability of optimal re-sponse to treatment, including achieving non-detectablelevels of plasma HIV RNA. [2]. Studies indicate that upto 95% adherence is required to achieve maximum viralload suppression [3]. Suboptimal adherence is associatedto treatment [4].In many studies, active illicit drug use among individ-uals living with HIV/AIDS is associated with decreasedaccess to HIV treatment, reduced medication adherenceand increased mortality [5]. Although many studies havefocused on the impact of heroin use on the clinical man-agement of HIV infection [6,7] fewer studies have exam-ined the influence of distinct illicit drug use patterns.Thus, we sought to examine the relative contribution ofdifferent illicit drug use patterns on ART non-adherenceamong a group of HIV-positive illicit drug users.* Correspondence: uhri-mjsm@cfenet.ubc.ca1BC Centre for Excellence in HIV/AIDS, St. Paul’s Hospital, 608-1081 BurrardStreet, Vancouver, BC, CanadaBackgroundAbstractBackground: Among people living with HIV/AIDS, illicit drug use is a risk for sub-optimal treatment outcomes.However, few studies have examined the relative contributions of different patterns of drug use on adherence toantiretroviral therapy (ART). We sought to estimate the effect of different types of illicit drug use on adherence in asetting of universal free HIV/AIDS treatment and care.Methods: Using data from ongoing prospective cohorts of HIV-positive illicit drug users linked to comprehensivepharmacy dispensation records in Vancouver, Canada, we examined factors associated with ≥95% prescription refilladherence using generalized estimating equations (GEE) logistic regression.Results: Between 1996 and 2013, 692 ART-exposed individuals were followed for a median of 42.7 months (InterquartileRange: 29.1–71.7). In multivariable GEE analyses, heroin injection (Adjusted Odds Ratio [AOR] = 0.75, 95% ConfidenceInterval [CI]: 0.66–0.85) as well as cocaine injection (AOR = 0.80, 95% CI: 0.72–0.90) were associated with lower likelihoodsof optimal adherence. Methadone maintenance therapy (AOR = 1.88, 95% CI: 1.68–2.11) was associated with a greaterlikelihood of adherence.Conclusions: Periods of heroin and cocaine injection appeared to have the most deleterious impact upon antiretroviraladherence. The findings point to the need for improved access to treatment for heroin use disorder, particularly methadone,and highlight the need to identify strategies to support ART adherence among cocaine injectors.Keywords: HIV, Antiretroviral therapy, Illicit drug use, Heroin, Cocaine, Adherencewith an increased risk of HIV/AIDS-associated mortalitynon-adherence to antiretHIV-positive illicit drug usa longitudinal analysisPouya Azar1, Evan Wood1,2, Paul Nguyen1, Maxo Luma1,© 2015 Azar et al.; licensee BioMed Central. ThCommons Attribution License (http://creativecreproduction in any medium, provided the orDedication waiver (http://creativecommons.orunless otherwise stated.ted with risk ofoviral therapy amongrs in a Canadian setting:lio Montaner1,2, Thomas Kerr1,2 and M-J Milloy1,2*is is an Open Access article distributed under the terms of the Creativeommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andiginal work is properly credited. The Creative Commons Public Domaing/publicdomain/zero/1.0/) applies to the data made available in this article,Azar et al. BMC Infectious Diseases  (2015) 15:193 Page 2 of 6MethodsData for these analyses were derived from the VancouverInjection Drug Users Study (VIDUS) and AIDS Care Co-hort to evaluate Exposure to Survival Services (AC-CESS), two ongoing prospective observational cohorts ofillicit drug users in Vancouver, Canada. Beginning in1996, persons who had injected illicit drugs other thancannabinoids in the previous month were recruited intoVIDUS. Since 2005, persons who used illicit drugs andwere HIV-seropositive at baseline or during the studyare subsequently followed in ACCESS. Both cohorts useidentical recruitment and follow-up procedures to allowfor combined analyses.Described in detail previously [8-10], the cohorts werepopulated through snowball sampling and extensivestreet outreach in the city’s Downtown Eastside neigh-bourhood, an area with an open drug market and highlevels of injection drug use, poverty and HIV infection[11,12]. Participants of these studies were 18 years of ageor older and provided written informed consent. At base-line and every six-month follow-up interview, participantsanswered a standardized interviewer-administered ques-tionnaire, were examined by a study nurse and providedblood samples for serologic analysis. Participants are ac-tively referred to primary care services and drug treatmentprograms where available and were provided with a $30stipend per study visit. A unique feature of these studies isthat the Canadian province of British Columbia deliversall HIV care including medications at no charge and em-ploys a system in which every instance of antiretroviraldispensation and all HIV clinical monitoring is capturedthrough a centralized registry [8,13,14]. This allows a com-prehensive retrospective and prospective clinical HIV pro-file for all participants. Ethics approval has been providedannually by University of British Columbia/ProvidenceHealth Care Research Ethics Board.The present analyses considered all HIV-seropositiveparticipants who had been dispensed at least one day ofantiretroviral therapy (ART) between May 1996 andMay 2013. The primary outcome of interest in this studywas adherence to ART in the six month period prior toeach study interview. As in previous studies [9,15], weestimated antiretroviral adherence using a validatedmeasure based on pharmacy refill records provided bythe confidential record linkage with the database of theDrug Treatment Program. Specifically, adherence wasestimated by calculating the number of days for whichan individual was dispensed ART in the previous sixmonths over the number of days since they had initiatedART, capped at 180 days. We dichotomized this measureas ≥95% vs. <95%. The cut-off threshold of 95% waschosen as this level has previously been shown to beclosely associated with virological suppression and sur-vival [15,16].Explanatory variables of interest included socio-demographic data: age (per 10 years older), gender (fe-male vs. male), and Caucasian ancestry (yes vs. no).Variables related to drug use characteristics included: her-oin injection (yes vs. no), cocaine injection (yes vs. no),amphetamine injection (e.g., “speed”, “uppers”, crystalmethamphetamine; yes vs. no), crack cocaine smoking(yes vs. no), and enrollment in methadone maintenancetherapy (yes vs. no). All drug use characteristics definedabove were treated as time-updated based on question-naire data pertaining to the six month period prior to eachstudy interview [8,13]. We also included CD4 cell count(per 100 cells/μL increase) at ART initiation using the lastCD4 cell count observation conducted prior to the firstdispensation of ART. We also included a time-updatedvariable measuring the time since the participant initiatedantiretroviral therapy (per year increase), using recordsfrom this setting’s comprehensive antiretroviral dispensary.As a first step, we visually inspected trends in the propor-tion of all participants reporting heroin injecting, cocaineinjecting, crack smoking and amphetamine injecting ateach interview period. Next, we visually inspected changesin median adherence rate at each interview period overtime.Since serial measures for each subject (i.e., multiple 6-month observation periods) were available for many par-ticipants, we estimated the relationships between differ-ent socio-demographic, drug use and clinical factors andadherence using generalized estimating equations (GEE)with a logit-link function. As a first step, we conductedbivariable GEE analyses to determine which variables werestatistically associated with adherence in unadjusted ana-lyses. To adjust for potential confounding and identify fac-tors that were associated with the outcome, all significantvariables in the bivariable analyses were considered in thefull multivariable model. With the drug use patterns beingforced into the model, a backwards model selection pro-cedure was used to identify the multivariate model withthe best overall fit as indicated by the lowest quasilikeli-hood under the independence model criterion value. Allstatistical analyses were performed using the SAS softwareversion 9.3 (SAS, Cary, NC). All p-values are two-sided.ResultsDuring the study period, 692 individuals were includedin these analysis, among whom 213 (30.8%) were female,the median age at baseline was 42 years (Inter-quartileRange (IQR): 35–47) and the median follow-up durationwas 42.7 months (IQR: 29.1–71.7). At baseline (Table 1),338 (48.8%) individuals reported heroin injection in theprevious six months, 388 (56.1%) reported cocaine injec-tion in the previous six months, 84 (12.1%) reported am-phetamine injection in the previous six months and 451(65.2%) reported smoking crack cocaine in the previousug≥342112Azar et al. BMC Infectious Diseases  (2015) 15:193 Page 3 of 6Table 1 Baseline characteristics of 692 HIV-positive illicit drmonthsCharacteristic <95% adherence301 (43.5) n (%)AgeMedian (IQR) 40 (34 – 45)GenderMale 195 (64.8)Female 106 (35.2)Caucasian ancestryNo 143 (47.5)Yes 158 (52.5)3six months. The proportions of participants at each inter-view period reporting these drug use patterns are shownin Figure 1. Figure 2 depicts the median adherence ratefor all participants at each interview period as well as thelower and upper quartiles. Over the entire study period,the median adherence rate was 98% (Inter-Quartile Range[IQR]: 37, 100). Among all observation periods, 3073(51%) were characterized by ≥95% adherence. Correlationbetween the adherence rate and plasma HIV-1 RNA viralload (log10 transformed) was −0.67; correlation betweenthe adherence rate and CD4+ cell count was 0.17.The bivariable and multivariable GEE analyses of ad-herence to ART are shown in Table 2. In the final multi-variable model, heroin injection (Adjusted Odds Ratio[AOR] = 0.76, 95% Confidence Interval [CI]: 0.67–0.85),cocaine injection (AOR = 0.74, 95% CI: 0.66–0.83), femaleHeroin injectionNo 141 (47.0) 2Yes 159 (53.0) 1Cocaine injection3No 126 (41.9) 1Yes 175 (58.1) 2Amphetamine injection3No 271 (90.0) 3Yes 30 (10.0) 5Crack cocaine smoking3No 107 (35.5) 1Yes 194 (64.5) 2MMT3No 202 (67.1) 2Yes 99 (32.9) 1Time since ART initiation (per year) 5.1 (2.5 – 8.9) 6Median (IQR)CD4+ cells at ART initiationMedian (IQR) 260 (150 – 390) 21. Odds Ratio; 2. 95% Confidence Interval; 3. Refers to 180 day period prior to the busers stratified by adherence to ART in the previous six95% adherence OR1 95% CI2 p value92 (56.6) n (%)3 (36 – 48) 1.05 1.02 – 1.06 <0.00184 (72.6) 1.0007 (27.5) 0.69 0.50 – 0.96 0.02740 (35.8) 1.0051 (64.2) 1.62 1.19 – 2.20 0.002sex (AOR = 0.77, 95% CI: 0.68 – 0.87) and CD4 cell countat ART initiation (AOR = 0.87, 95% CI: 0.83 – 0.92) werenegatively associated with optimal adherence to ART.Older age (AOR = 1.66, 95% CI: 1.54 – 1.80) and use ofmethadone maintenance therapy (AOR = 1.88, 95% CI:1.68 –2.11) were independently and positively associatedwith optimal adherence to ART.DiscussionIn this long-running community-recruited study of illicitdrug users linked to comprehensive HIV clinical recordsin a setting of universal free HIV/AIDS treatment andcare, we observed that periods of heroin and cocaine in-jection were independently and negatively associatedwith the likelihood of optimal adherence to ART. Wedid not observe a statistical relationship between periods11 (54.1) 1.0079 (45.9) 0.75 0.56 – 1.02 0.06478 (45.5) 1.0013 (54.5) 0.86 0.64 – 1.17 0.33637 (86.2) 1.004 (13.8) 1.45 0.90 – 2.33 0.12534 (34.2) 1.0057 (65.7) 1.06 0.77 – 1.45 0.72710 (53.7) 1.0081 (46.3) 1.76 1.29 – 2.40 <0.001.5 (3.1 – 11.4) 0.94 0.91 – 0.97 <0.00120 (140 – 360) 1.00 1.00 – 1.00 0.074aseline interview.+++ + + + + ++ + + + +++++ + +++ + + + + + + + + + + + + +Heroin injectionSurvey PeriodProportion0204060801001 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33+ +++ ++ ++ + ++ ++ +++ + + ++ + ++ + ++ + ++ + + + + +Cocaine injectionSurvey PeriodProportion0204060801001 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33+++ ++ +++ + +++++++++ ++ + ++ +++ + + + + + + + +Crack cocaine smokingProportion0204060801001 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33+ + + + + + + + + + + + + ++ + + + ++ + + + + ++ + ++ + + + ++Amphetamine injectionProportion0204060801001 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33g h5%Azar et al. BMC Infectious Diseases  (2015) 15:193 Page 4 of 6of either amphetamine injection or crack cocaine smok-ing and the likelihood of optimal adherence to ART.Meanwhile, engagement in methadone maintenancetherapy was independently and positively associated withoptimal adherence to ART.Our finding of strong and independent links betweenSurvey PeriodFigure 1 Drug use patterns over time; Proportion of all participants reportininjection in the previous 180 days at each survey period (plus symbol), with 9heroin use, engagement in methadone maintenance andthe likelihood of optimal ART adherence suggests that theexpansion of evidence-based addiction treatment strategies,Antiretroviral adherence (%)0204060801001 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1Figure 2 Antiretroviral adherence patterns over time; Median antiretroviraleach survey period (diamond), with lower and upper quartiles.such as methadone, will likely improve retention in HIV/AIDS care among opioid-dependent illicit drug users[17-19]. Improving access to methadone will requirescale-up treatment slots in settings where methadone iscurrently available and removal of legal impediments tothis evidence-based opioid treatment modality [20].Survey Perioderoin injection, cocaine injection, crack cocaine smoking and amphetamineconfidence intervals.In our study, we did not observe a statistical relation-ship between amphetamine use and adherence to ART.Crystal methamphetamine use is particularly prevalentSurvey Period6 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34adherence rate achieved in the last 180 days among all participants atngused,Azar et al. BMC Infectious Diseases  (2015) 15:193 Page 5 of 6among some populations of people living with HIV/AIDS and persons at risk for HIV, especially men whohave sex with men. [21-23] Numerous studies havefound that, among this population, amphetamine use inis linked to decreased medication adherence as a resultof binging episodes, and in the long-term, has been asso-ciated with the development of antiretroviral-resistantviral strains [23]. In the current study, which contained ahigh proportion of individuals reporting periods of poly-substance use, this association was not observed. Thismight reflect the relatively smaller number of individualsreporting periods of amphetamine injection and with co-horts of men who have sex with men, which would bemore heterogeneous with respect to drug use. Instead, thepresent study observed a strong and independent link be-tween injection cocaine use and sub-optimal adherence,underling the urgent need for effective pharmacotherapiesto address stimulant use, especially in the context of HIVTable 2 Univariable and multivariable generalized estimatiadherence to antiretroviral therapy among 692 illicit drugCharacteristic OR1Gender (female vs. male) 0.70Age (per 10 years older) 2.04Caucasian (yes vs. no) 1.37Heroin injection (yes vs. no)4 0.67Cocaine injection (yes vs. no)4 0.73Amphetamine injection (yes vs. no)4 1.14Crack cocaine smoking (yes vs. no)4 0.95Methadone maintenance therapy (yes vs. no)4 1.74Time since ART initiation (per year increase) 1.08CD4+ cell count at ART initiation (per 100 cells/mL increase) 0.871. Odds Ratio; 2. 95% confidence interval; 3. Adjusted Odds Ratio; 4. Time-updatdisease.Although we observed increasing levels of adherenceover time, a substantial proportion of all participants dis-played sub-optimal adherence to prescribed treatment atevery interview period. Our model indicates that specificdrug use patterns each had different relationships to anti-retroviral adherence. For example, while periods of heroininjection were 23% less likely to be characterized by ≥95%adherence, there was no significant difference betweenlevels of optimal adherence during periods of amphet-amine injection. Unfortunately, our model does not offerspecific insights into possible explanations for these diver-gent results. Thus, future research should investigate thepossible behavioural-, psychologic-, social- and structural-level barriers and facilitators of adherence for differentgroups of illicit drug users in order to optimize substanceabuse treatment and support ART adherence.There are some limitations to this study to note. Par-ticipant selection for this observational study was notrandom and the results of this study cannot be general-ized to the wider population of HIV-positive illicit drugusers. Regarding associations drawn from the results ofthe study, there is potential for unmeasured confound-ing. In an attempt to minimize the impact of confound-ing on the observed relationships we used multivariablemodelling. Also, we have previously observed that atleast 95% adherence to prescribed ART is strongly asso-ciated with viral suppression and survival [15,16]. Newerformulations of ART are more potent and evidence sug-gests they may deliver comparable rates of viral suppres-sion at lower adherence thresholds [24,25]. Thus, futureresearch might consider the effects of illicit drug use onattaining different adherence thresholds and viral sup-pression. Finally, we recognize that we are unable to de-termine the possible temporal relationships betweenillicit drug use behaviours and antiretroviral dispensationpatterns within any 180-day observation period.equations analyses of factors associated with ≥ 95%ers95% CI2 p AOR3 95% CI2 p0.56 – 0.88 0.002 0.77 0.68 – 0.87 0.0381.75 – 2.38 <0.001 1.66 1.54 – 1.80 <0.0011.12 – 1.69 0.002 1.07 0.95 – 1.19 0.5710.58 – 0.78 <0.001 0.76 0.67 – 0.85 0.0020.63 – 0.85 <0.001 0.74 0.66 – 0.83 0.0010.89 – 1.47 0.3050.82 – 1.10 0.5251.45 – 2.10 <0.001 1.96 1.75 – 2.19 <0.0011.06 – 1.11 <0.001 1.02 0.99 – 1.04 0.0900.83 – 0.92 <0.001 0.88 0.85 – 0.90 <0.001refers to the six-month period prior to the interview.ConclusionsTo conclude, our study utilized data from a long-runningcommunity-recruited prospective cohort of HIV-seropositiveillicit drug users in the setting of free and universal accessto HIV care. Periods of injection heroin use and injectioncocaine use were both independently and negatively asso-ciated with a lower likelihood of optimal adherence toART while engagement in MMT was associated withhigher levels of optimal adherence. Given the importanceof addressing substance use in the community and theproven success of MMT at reducing the risk of drug-related harms, our findings support the need to spur ef-forts to improve access to treatment for problematicsubstance use among individuals living with HIV/AIDS.Competing interestsDr. Milloy is supported in part by the United States National Institutes ofHealth (R01-DA021525.) This work was supported in part by a Tier 1 CanadaResearch Chair in Inner-City Medicine awarded to Dr. Wood. Dr. Montaner isand the role of opioid substitution treatment (OST). Int J Drug Policy.2007;18:262–70.19. Strain EC, Bigelow GE, Liebson IA, Stitzer ML. Moderate- vs high-dosemethadone in the treatment of opioid dependence: a randomized trial.JAMA. 1999;281:1000–5.20. Wolfe D, Carrieri MP, Shepard D. Treatment and care for injecting drugusers with HIV infection: a review of barriers and ways forward. Lancet.2010;376:355–66.21. Carrico AW, Woolf-King SE, Neilands TB, Dilworth SE, Johnson MO. Stimulantuse and HIV disease management among men in same-sex relationships.Drug Alcohol Depend. 2014;139:174–7.22. Marquez C, Mitchell SJ, Hare CB, John M, Klausner JD. Methamphetamine use,sexual activity, patient-provider communication, and medication adherenceamong HIV-infected patients in care, San Francisco 2004-2006. AIDS Care.2009;21:575–82.23. Reback CJ, Larkins S, Shoptaw S. Methamphetamine abuse as a barrier toAzar et al. BMC Infectious Diseases  (2015) 15:193 Page 6 of 6supported by the British Columbia Ministry of Health and through an Avant-GardeAward (No. 1DP1DA026182) from the National Institute of Drug Abuse (NIDA), atthe US National Institutes of Health (NIH). He has also received financial supportfrom the International AIDS Society, United Nations AIDS Program, World HealthOrganization, National Institutes of Health Research-Office of AIDS Research,National Institute of Allergy & Infectious Diseases, The United States President’sEmergency Plan for AIDS Relief (PEPfAR), UNICEF, the University of British Columbia,Simon Fraser University, Providence Health Care and Vancouver Coastal HealthAuthority. The other authors declare they have no competing interests.Authors’ contributionsEW and PA conceived this study. PN conducted the statistical analyses. EW,PA, TK, M-JM and ML contributed to the interpretation of the analyses; JSGM,M-JM, TK and EW contributed to the acquisition of data; PA drafted themanuscript and revised it; all authors provided commentary on the manuscriptand gave final approval for the final version to be published.AcknowledgementsThe authors thank the study participants for their contributions to the research,as well as current and past researchers and staff. We would specifically like tothank: Kristie Starr, Deborah Graham, Tricia Collingham, Carmen Rock, BrandonMarshall, Caitlin Johnston, Steve Kain, Benita Yip and Guillaume Colley for theirresearch and administrative assistance. The study is supported by the US NationalInstitutes of Health (R01-DA021525) and the Canadian Institutes of Health Research(MOP-79297 and RAA-79918. The funders had no role in the design of the study;collection, analysis and interpretation of data; in the writing of the manuscript;and in the decision to submit the manuscript for publication.Received: 29 August 2014 Accepted: 25 March 2015References1. Zwahlen M, Harris R, May M, Hogg R, Costagliola D, de Wolf F, et al. Mortalityof HIV-infected patients starting potent antiretroviral therapy: comparison withthe general population in nine industrialized countries. Int J Epidemiol.2009;38:1624–33.2. Wood E, Hogg RS, Yip B, Harrigan PR, Montaner J. Why are baseline HIV RNAlevels 100,000 copies/mL or greater associated with mortality after the initiationof antiretroviral therapy? J Acquir Immune Defic Syndr. 2005;38:289–95.3. Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, et al. Adherenceto protease inhibitor therapy and outcomes in patients with HIV infection. AnnIntern Med. 2000;133:21–30.4. Deeks SG. Treatment of antiretroviral-drug-resistant HIV-1 infection. 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Wood E, Hogg RS, Bonner S, Kerr T, Li K, Palepu A, et al. Staging for antiretroviraltherapy among HIV-infected drug users. JAMA. 2004;292:1175–7.11. Strathdee SA, Patrick DM, Currie SL, Cornelisse PG, Rekart ML, Montaner JS,et al. Needle exchange is not enough: lessons from the Vancouver injectingdrug use study. AIDS. 1997;11:F59–65.12. Tyndall MW, Currie S, Spittal P, Li K, Wood E, O apos Shaughnessy MV, et al.Intensive injection cocaine use as the primary risk factor in the VancouverHIV-1 epidemic. AIDS. 2003;17:887–93.13. Palepu A, Tyndall MW, Joy R, Kerr T, Wood E, Press N, et al. Antiretroviraladherence and HIV treatment outcomes among HIV/HCV co-infected injectiondrug users: the role of methadone maintenance therapy. Drug Alcohol Depend.2006;84:188–94.HIV medication adherence among gay and bisexual men. AIDS Care.2003;15:775–85.24. Hughes CA, Robinson L, Tseng A, MacArthur RD. 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