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The HAART cell phone adherence trial (WelTel Kenya1): a randomized controlled trial protocol Lester, Richard T; Mills, Edward J; Kariri, Antony; Ritvo, Paul; Chung, Michael; Jack, William; Habyarimana, James; Karanja, Sarah; Barasa, Samson; Nguti, Rosemary; Estambale, Benson; Ngugi, Elizabeth; Ball, T B; Thabane, Lehana; Kimani, Joshua; Gelmon, Lawrence; Ackers, Marta; Plummer, Francis A Sep 22, 2009

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TrialsStudy protocolThe HAART cell phone adherence trial (WelTel Kenya1):a randomized controlled trial protocolRichard T Lester*1,2, Edward J Mills3, Antony Kariri1, Paul Ritvo4,Michael Chung5, William Jack6, James Habyarimana6, Sarah Karanja1,Samson Barasa1, Rosemary Nguti1, Benson Estambale7, Elizabeth Ngugi1,T Blake Ball2, Lehana Thabane8, Joshua Kimani1,2, Lawrence Gelmon1,2,Marta Ackers9 and Francis A Plummer2,10Address: 1Department of Medical Microbiology, University of Nairobi, UNITID Building, Nairobi, Kenya, 2Department of MedicalMicrobiology, University of Manitoba, Health Sciences Centre, Winnipeg, Manitoba, Canada, 3BC Centre for Excellence in HIV, St. Paul’sHospital, University of British Columbia, Vancouver, BC, Canada, 4School of Kinesiology and Health Sciences, Department of Psychology, YorkUniversity, York, Ontario, Canada, 5Department of Economics, Georgetown University, Washington, USA, 6Division of Allergy and InfectiousDiseases, Department of Medicine, University of Washington, Seattle, WA, USA, 7University of Nairobi Institute of Tropical and InfectiousDiseases (UNITID), Nairobi, Kenya, 8Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada,9US Centers for Disease Control and Prevention (CDC), Nairobi, Kenya and 10National Microbiology Laboratory, Public Health Agency ofCanada, Winnipeg, Manitoba, CanadaE-mail: Richard T Lester* - rlestr.id@gmail.com; Edward J Mills - emills@cfenet.ubc.ca; Antony Kariri - tkariri@csrtkenya.org;Paul Ritvo - paul.ritvo@gmail.com; Michael Chung - mhchung@u.washington.edu; William Jack - wgj@georgetown.edu;James Habyarimana - james.habyarimana@gmail.com; Sarah Karanja - sashkaranja@gmail.com; Samson Barasa - sbarasa@csrtkenya.org;Rosemary Nguti - rnguti@uonbi.ac.ke; Benson Estambale - bestambale@uonbi.ac.ke; Elizabeth Ngugi - Engugi@csrtkenya.orgT Blake Ball - tball@cc.umanitoba.ca; Lehana Thabane - thabanl@mcmaster.ca; Joshua Kimani - jkimani@csrtkenya.org;Lawrence Gelmon - lgelmon@csrtkenya.org; Marta Ackers - MAckers@ke.cdc.gov; Francis A Plummer - frank_plummer@phac-aspc.gc.ca*Corresponding authorPublished: 22 September 2009 Received: 18 May 2009Trials 2009, 10:87 doi: 10.1186/1745-6215-10-87 Accepted: 22 September 2009This article is available from: http://www.trialsjournal.com/content/10/1/87© 2009 Lester et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.AbstractBackground: The objectives are to compare the effectiveness of cell phone-supported SMSmessaging to standard care on adherence, quality of life, retention, and mortality in a populationreceiving antiretroviral therapy (ART) in Nairobi, Kenya.Methods and Design: A multi-site randomized controlled open-label trial. A centralrandomization centre provided opaque envelopes to allocate treatments. Patients initiating ARTat three comprehensive care clinics in Kenya will be randomized to receive either a structuredweekly SMS (’short message system’ or text message) slogan (the intervention) or current standardof care support mechanisms alone (the control). Our hypothesis is that using a structured mobilephone protocol to keep in touch with patients will improve adherence to ART and other patientoutcomes. Participants are evaluated at baseline, and then at six and twelve months after initiatingART. The care providers keep a weekly study log of all phone based communications with studyparticipants.Primary outcomes are self-reported adherence to ART and suppression of HIV viral load at twelvemonths scheduled follow-up. Secondary outcomes are improvements in health, quality of life, socialand economic factors, and retention on ART. Primary analysis is by ‘intention-to-treat’. SensitivityPage 1 of 10(page number not for citation purposes)BioMed CentralOpen Accessanalysis will be used to assess per-protocol effects. Analysis of covariates will be undertaken todetermine factors that contribute or deter from expected and determined outcomes.Discussion: This study protocol tests whether a novel structured mobile phone intervention canpositively contribute to ART management in a resource-limited setting.Trial Registration: Trial Registration Number: NCT00830622BackgroundThe most important factor for sustainable treatment ofHIV/AIDS for individuals and programs globally ishighly consistent use of highly active antiretroviraltherapy (ART). For patients, this means adhering todaily or twice daily medication schedules, typically at aminimum of at least 95% of the time, and for programsthis means supporting and monitoring patients toachieve those goals [1]. The World Health Organizationand UNAIDS have outlined ambitious goals of universalaccess to those in need among the 28 million peopleinfected with HIV globally, and include a directive toembrace new technologies to help achieve that goal [2].Mobile telephones have transformed telephone commu-nications dramatically in resource limited settings. InKenya, mobile phones penetration has reached over 60%and Africa has the highest rate of new uptake in theworld [3]. The reach of cellular networks among HIVinfected persons may be even higher than the generalAfrican population since both HIV and wireless networkcoverage are preferenced to areas of higher populationdensities such as urban areas and transport routes.Currently, mobile phones are used intensely in personallives and business transactions in the region. We there-fore feel that structured mobile phones communicationscan substantially improve clinical management of HIVpatients in resource-limited settings [4].No previous RCTs of cell-phones for ART adherence havebeen reported, thus, no systematic review is available.This protocol outlines our proposed methods of a multi-site randomized clinical trial (RCT) that tests if a novelmobile phone communication intervention improvesadherence to HAART, and improves other patientoutcomes in Kenya. Patient outcomes assessed includemortality, morbidity, quality of life, social and economicindicators. We hypothesize that the cell phone interven-tion may directly or indirectly improve these outcomes.If the intervention improves HAART adherence (primaryoutcome) and the drug effect (suppression of plasmaviral load), then health, quality of life, social andeconomic indicators could all be consequentlyimproved. Since the intervention also provides anenhanced communication link between patients andhealthcare providers, patient support may also influencepatient outcomes directly, independent of drug adher-ence. By using intention to treat (ITT) analysis, we willbroadly assess the effect of the intervention on patientoutcomes. By using sensitivity and subgroup analyses,we will assess the intervention effect more specifically.Methods and DesignWe registered our clinical trial with ClinicalTrials.govand received the number NCT00830622.FundingFunding was obtained through the President’s EmergencyPlan for AIDS Relief (PEPFAR) through a cooperativeagreement, #U62/PS024510, from the US Centers forDisease Control and Prevention.Study designThe study is a multi-site RCT. Patients will be randomizedto the cell phone (SMS) intervention group versus thestandard of care (SOC) control (no SMS) at a 1:1allocation ratio (see Figure 1 Consort diagram).RandomizationA project statistician generated 1:1 randomization numbersfor study arm assignments using a random numbergenerating program. The randomization was stratified ina 2:2:1 ratio to the three clinics (the rural clinic having thelower number of assignments). Written allocation ofassignment is sealed in individual opaque envelopesmarked with study identification numbers which aredistributed to all three study clinics in sufficient quantityto allocate the target numbers of participants. Afterconsenting to participate and meeting inclusion criteria,screened subjects are enrolled and immediately afterwardare assigned to the randomized study arm by a clinicianopening the sealed envelopes to determine allocation. Age,gender, and CD4 T cell counts will be assessed for balanceof study arm allocation at each site.Setting and participantsSubjects are recruited from three HIV comprehensivecare clinics (CCC) in Kenya. One facility is an urbanuniversity-run clinic situated in a lower socioeconomicarea of Nairobi, the second is an urban clinic attached toa faith-based hospital situated in a middle income areaTrials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 2 of 10(page number not for citation purposes)Figure 1Consort diagram of study design.Trials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 3 of 10(page number not for citation purposes)of Nairobi, and the third is a government-run clinicsituated in a vast rural district of Kenya populated bypastoralists.Patients are eligible to participate if they are initiatingHAART for the first time (within two weeks before or afterenrolment screening), if they are adults (at least 18 yrsold), if they owned or had sufficient access to a mobilephone (shared access is allowed if access is daily and thephone owner agrees to participate), and if they were able tosufficiently operate a cell phone to communicate usingtext-messaging (help by a partner is sufficient for illiteratesubjects). Patients need to provide oral and written consentto participate. For patients who are illiterate, clear oralconsent is obtained. Patients are excluded if they do notmeet inclusion criteria or are not planning to attend theenrolment clinic for the planned study period (at least twoyears). Patients are considered newly initiating HAART ifthey have not taken HAART in at least one year and havenot taken it ever for more than 2 months. Most preventionof mother to child transmission (PMTCT) regimens inKenya include limited antiretroviral regimens and not trueHAART, so participation in PMTCT is not an exclusioncriteria. Therefore, the study covers a broad range ofpatients attending comprehensive care clinics (CCC) forART in Kenya.Participants are compensated for their participation timewith money for lunch on study visit days (100 Kenyashillings). Patients are not provided cell phones or networkairtime credit.InterventionThe intervention being evaluated is a structured cellphone initiative to improve communications betweenhealthcare providers and patients. The interventionprotocol was conceived in 2005 by several brainstormingmeetings between health care provider staff at the clinics,and ultimately incorporated feedback from pilot patientsfrom a survey and from small group sessions [3].Every week, on Monday mornings, the site-clinician(typically a nurse or clinical officer) sends a text message(SMS) to all subjects in the intervention arm to remindthem about their support and enquire into how they aredoing. Typically, a slogan is used such as “Mambo?”which is Kiswahili for “How are you?”, but similarslogans in other local languages can also be used at theclinicians’ discretion. To simplify their work, theclinicians use the ‘send to many’ function on their cellphone for mass/group messaging. Intervention subjectsare instructed to respond within 48 hours either that theyare doing well ("Sawa”) or that they have a problem("Shida”) and request assistance. Sending an SMS isinexpensive (less than $0.05); however, in somecircumstances where network credit is not available orwas impractical, the patients can use the free ‘flashback’function to trigger a call from the clinician. The clinicianthen calls to follow-up and provide triage to any subjectsthat respond that there is a problem, or subjects who failto respond within two days.Clinicians are only expected to respond to text messagesduring regular clinic hours, but are not restricted to do so.Intervention participants are instructed that the interven-tion is a clinic utility and that all emergencies should behandled through their usual means such as attending thenearest hospital emergency department. All participantsreceive a brief training from the clinicians on use of thephone and the protocol if they were in the intervention.Use of any of the cell phone network providers is allowed.Receiving SMS text messages or voice calls in Kenya is freeon all networks.ControlPatients randomized to the control arm receive theirusual standard of care (SOC) clinic support but are notsent the weekly SMS slogans from the clinicians. Theyare, however, free to call the clinic staff at any time ontheir own initiative. All cell phone communicationsbetween clinicians and study participants, in both studyarms, are recorded in a study log.ObjectivesPrimary objectivesThe study is intended to test whether the cell phoneintervention (SMS) improves self-reported adherence toHAART and whether it affects a biological surrogate markerof adherence, specifically suppression of plasma HIV RNAload at 12 months follow-up. We hypothesize that the SMSintervention will remind patients taking HAART aboutclinic support and reinforce regular communications inorder to sort out any adherence related problemsefficiently. Thus, we hypothesize the intervention willpositively support patients’ adherence to HAART andconsequent suppression of HIV viral load compared topatients who only receive the standard of care (control).Secondary objectivesWewill also test the cell phone intervention (SMS) ability toimprove health, quality of life, social, economic outcomesand retention in ART programs. We hypothesize thatpatients who receive the weekly SMS reminders (interven-tion) may have improved immune reconstitution (CD4count), increased body weight, fewer opportunistic infec-tions, fewer adverse health events, improved quality of life,delayed death, improved social factors such as disclosure oftheir HIV status, and improved economic indicatorsTrials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 4 of 10(page number not for citation purposes)compared to those that do not receive the intervention(control). We also hypothesize that subjects in theintervention arm will be more frequently retained in theART program.Outcome measuresSampling and enrolmentWe determined that continuous sampling was imprac-tical since the clinics are often extremely busy and clinicstaff are obliged to provide rapid patient care in order tomeet service targets. Only a few patients (typically up tofive) can typically undergo the consenting and enrol-ment evaluation process daily at each site. Subjects arenot screened if they are participating in a differentadherence study, which occurs at one clinic site. Todetermine the comparative characteristics of studyparticipants with the general clinic population, we willcompare baseline characteristics of a sample of non-study participants with characteristics of subjectsenrolled in our study. Since mobile phone access is anenrolment criterion, we will include comparison ofbaseline characteristics of study enrolees with otherclinic attendees who do not have phone access.Primary outcomesThe first primary outcome is patient adherence to HAARTat twelve months. (See Appendix) This is assessed byself-report using a standard questionnaire of the numberof pills missed in the last 30 days and calculating percentadherence based on the expected number of doses taken.Percent adherence will be analyzed as a continuousvariable and dichotomous variable. Subjects are consid-ered either ‘adherent’ or ‘non-adherent’ using an optimaladherence cut off of > 95% of medications taken asdirected [1]. Adherence is assessed at each follow-up visitand ‘ever-non-adherent’ will be our dichotomous out-come. The twelve month scheduled follow-up (defined,allowing for non-exact timing of clinic attendance, asfollow-up up to 15 months if patients not present at12 months) is the primary analysis. The six monthassessment will allow for evaluating trends but is not theprimary outcome.The second primary outcome is suppression of plasmaHIV RNA load at twelve months after initiating ART. Ifpatients are adherent to HAART regimens, absorb thedrugs normally, and if their virus is not resistant to theHAART drugs in the regimen, then plasma HIV loadshould be suppressed to below detectable levels (≤400copies per ml) by six months and remain suppressedthereafter. Due to variability in when patients show upfor scheduled appointments, we accept follow-up on orafter 20 weeks as the six month outcome visit. Analysisof ‘suppressed’ (≤400 copies/ml) versus ‘failure’ tosuppress (>400 copies/ml) at twelve months as adichotomous variable is the primary analysis. However,decrease in plasma HIV load copies from baseline totwelve month follow-up will also be analyzed as thedifference in a continuous variable from baseline totwelve months.Secondary outcomesThe potential benefits of the intervention are quitebroad, so multiple secondary outcomes are of interestand were selected through academic collaboration. Thesecondary outcomes fall under the categories of health,quality of life, social factors, and economic indicators(see Table 1). The primary purpose of taking antiretro-viral medications for HIV infection is to maintain orrestore health in someone who is HIV infected. Severalother factors that contribute to a subject’s prosperity oroverall well-being may be affected directly (by way ofenhanced support mechanisms associated with theintervention), or indirectly (through improvements inhealth related to HAART effect). We therefore feel it isimportant to assess each of these outcomes indepen-dently.In addition, we hypothesize that the interventionwill lead to improved retention on ART [5]. Becauseparticipants are actively traced for twelve month follow-up visits, we will use composite retention outcomes. Wedefine ‘retained’ as someone who followed-up on theirscheduled visit without being traced and is still takingTable 1: Secondary Outcome MeasuresSecondary outcome measures (6 months and12 months post initiation of HAART)TypeHealth outcomesSelf-reported adherence as a percentage BinarySuppressed HIV viral load (in copies) ContinuousImmune reconstitution (change in CD4 T cell countfrom baseline)Time to virological failure ContinuousWeight gain [lbs] and BMI Time-to-eventOccurrence of opportunistic infections (OIs) ContinuousTime to reporting of adverse drug events (ADEs) BinaryDeaths (all cause) Time-to-eventQuality of life (QOL) Time-to-eventSF-12Satisfaction with care provided ContinuousSocial factors ContinuousLevel of disclosure of HIV statusImpression of stigma BinaryFamily dyamics ContinuousEconomic factors ContinuousEmployment attendanceHousehold member school attendance ContinuousCell phones lost/stolen ContinuousHAART = highly active antiretroviral therapy, SF-12 = short form 12adapted for regional application in Kiswahili.Trials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 5 of 10(page number not for citation purposes)ART versus ‘unretained’ which includes subjects whostopped taking ART before their twelve month visit, whoare lost to follow-up, or required active tracing aftermissing their scheduled twelve month appointment. Wewill report each element of the composite endpoints [6].Sample sizeThe primary objectives of this trial to improve adherenceto HAART and suppression of HIV viral load evaluated at12 months. The sample size calculation is based on thecomparison between proportions of patients withadherence rates (measured as percent of adherence>95%) in the two groups at 12 months because this isthe variable that required the larger sample size. Thecriterion for significance (alpha) has been set at 0.05.The test is 2-tailed, which means that an effect in eitherdirection will be interpreted.The sample was calculated using (Cary, NC). With theproposed sample size of 247 and 247 for the two groups(ie assuming a 1:1 allocation ratio), the study will havepower of 80% to yield a statistically significant resultusing a chi-squared test (assuming an intention-to-treatprinciple for the analysis) at alpha = 0.05/2 (ie usingthe Bonferroni correction factor for the two primaryoutcomes).This computation assumes 10% improvement in ‘perfectadherence’ over a baseline of 75% determined from ratesin a large adherence trial by AMPATH in Western Kenyawhich we felt is the most representative data available [7].This difference of 10% was selected as the smallestdifference that would be important to detect, in the sensethat any smaller difference would not be of clinical orsubstantive importance. It is also assumed that thisdifference is reasonable, in the sense that an effect of thismagnitude could be anticipated in this field of research.Assuming attrition rates of approximately 10% weintend to over-enrol by 10% resulting in an enrolmenttarget of at least 534 participants for randomization (267in the Intervention, and 267 in the Control).Data collectionData collection tools include a baseline questionnaire,follow-up questionnaire (used at 6 and 12 month visits),the SF-12 quality of life assessment adapted for localcontent, GPS co-ordinates of the clinics and participantshomes, and a household roster of economic indicators.Questionnaires include continuous and categorical vari-ables and Likert scales. All questionnaires were designedin English and translated to Kiswahili then backtranslated to verify meaning. Questionnaires are admi-nistered by clinic staff fluent in the languages ofparticipants. In instances where study participantsspeak only local languages, the clinician translatesquestions directly. Antiretroviral adherence is assessedat each follow-up visit by inquiring about missed dosesin the previous 30 days and calculating percentadherence according to pill counts. A visual analoguescale is used to confirm calculated adherence rates. Aweekly study log is kept to record the weekly SMSmessages and responses including details related tophone access, medication adherence and health orillness issues as they arose. Telephone communicationswith subjects in the control arm are also recorded in asimilar study log, even though they are not sent theweekly SMS messages. Clinic charts are reviewed forWHO stages and clinical data on health parameters andevents. A study register is kept to record follow-up.Attempts are made to obtain lab data from samplesobtained at usual clinical care time points and thus areeither collected at the same visit as the study ques-tionnaires are administered or within two weeks if notthe same day. The CD4 T cell counts are run on aFACScan (Becton Dickson) at a centralized site. Plasmasfor HIV viral load testing (Roche Amplicor) are separatedat the central laboratory for the Nairobi clinics, butseparated and frozen at -20C and batched for transportfrom the rural district clinic. All plasmas are frozen at -80C at the central lab. Viral loads are run in batchesusing manufacturer controls.Analysis planAnalysis of primary and secondary outcomesThe trial will be reported according to the CONSORTstandards for reporting randomized trials. We will useintention to treat (ITT) principles for primary outcomeanalysis and conduct additional sensitivity and ‘perprotocol’ analysis separately as outlined below. Inten-tion to treat implies all subjects randomized areconsidered in outcomes as per randomization. In thisanalysis we will impute missing outcome data astreatment failures. For adherence assessment, missingdata at 12 months will be considered as ‘non-adherent’;for viral suppression analysis, missing data at 12 monthswill be considered as virologic failures. We will usemultiple imputation for imputing missing data that arenot directly related to adherence. It is considered thegold standard for handling missing data because it leadsto unbiased estimates of the effect and standard errorscompared to single imputation methods [8].Sensitivity AnalysesSensitivity analysis and per-protocol analysis includesstudy subjects who meet certain criteria. For sensitivity,additional analysis of outcomes as stated above willTrials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 6 of 10(page number not for citation purposes)include only subjects who completed follow-up at theprimary 12 month endpoint. Because the SMS interven-tion protocol requires active participation of studysubjects to respond and thus conduct the interventionas fully intended, per-protocol analyses will also beperformed. Study participants in the intervention armwho respond to the weekly SMS’s with an SMS back(active response) at least 80% of the time with the 48hour time frame will be considered highly protocol-adherent; those who respond 50% to 80% of the timewill be considered moderately protocol-adherent; thosewho respond less than 50% will be considered poorlyprotocol-adherent; and those that respond less than 20%will be considered least protocol-adherent. Subjects whoare randomized to the SMS intervention but neverrespond with a return SMS, for whatever reason, willbe considered as never responding and not included inthe sensitivity analysis. We will also perform a sensitivityanalysis to assess the impact of potential clustering ofpatients cared for by the same clinic.Sub-group analysesBecause a large clinical trial on this type of interventionhas never been done before, we are interested in theinterventions effect on various subgroups and the effectof multiple covariates on treatment outcomes. Sub-groups of particular interests and potential covariatesproposed are outlined in Table 2. Treatment arms will becompared with respect to potential covariates usingcontinuous and categorical univariate analyses.Statistical methodsThe intervention arm (SMS) will be compared againstthe control (SOC) for all primary analysis. We will usechi-squared test for binary outcomes, and T-test forcontinuous outcomes. For subgroup analyses, we willuse regression methods with appropriate interactionterms (respective subgroup × treatment group). Multi-variable analyses will be based on logistic regression (SeeTable 2) for binary outcomes and linear regression forcontinuous outcomes. We will examine the residual toassess model assumptions and goodness-of-fit. Fortimed endpoints such as mortality we will use theKaplan-Meier survival analysis followed by multivariableCox proportional hazards model for adjusting forbaseline variables. We will calculate Relative Risk (RR)and RR Reductions (RRR) with corresponding 95%confidence intervals to compare dichotomous variables,and difference in means will be used for additionalanalysis of continuous variables. P-values will bereported to four decimal places with p-values less than0.001 reported as p < 0.001. Up-to-date versions of SAS(Cary, NC) and SPSS (Chicago, IL) will be used toconduct analyses. For all tests, we will use 2-sidedp-values with alpha = < 0.05 level of significance. We willuse the Bonferroni method to appropriately adjustthe overall level of significance for multiple primaryoutcomes, and secondary outcomes.To assess the impact of potential clustering for patientscared by the same clinic, we will use generalizedestimating equations [GEE] (ref) assuming an exchange-able correlation structure. Table 3 provides a summary ofmethods of analysis for each variable. Professionalacademic statisticians (LT, RN) blinded to study groupswill conduct all analyses.Nested studiesDescriptors from the study logsIt is unknown what types of problems and issues willarise as a result of the cell phone intervention initiatedby the study protocol. Detailed study logs kept by thestudy clinicians will allow description of the issues raisedby patients during phone contact and how they werehandled by the clinicians in both the SMS interventiongroup and standard of care control group.Healthcare worker surveysThe nurses and clinical officers (clinicians) that managethe SMS intervention will be asked to complete self-administered questionnaires regarding their experiences.They will also be asked about their time commitmentsand work load before and after instituting the interven-tion.Qualitative interviewsSemi-structured interviews will be designed to investi-gate in-depth experiences of subjects enrolled in thestudy. Twenty participants are targeted for a balance ofgender and other characteristics such as occupation andlifestyle. Interviews are conducted in English or KiSwa-hili and in the latter case back-translated into English bytwo separated translators.Table 2: List of subgroups and potential covariatesSubgroups of interest Potential covariatesUrban vs. rural AgeBy clinic GenderFemale vs. male Distance from clinicPhone ownership (owned vs. shared) Income levelOccupational designation Cost to attend clinicLevel of education Level of literacyUsual mode of transportation used Baseline quality of lifeHIV stagingLevel of disclosure of statusCrossover into interventionHAART = highly active antiretroviral therapy.Trials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 7 of 10(page number not for citation purposes)EthicsThe study is being conducted in accordance with theHelsinki declaration and established guideline forresearch on human subjects. The study protocol wasapproved by the University of Manitoba and KenyattaNational Hospital ethics review boards. All participantsprovide written consent. This study does not have a Dataand Safety Monitoring Board. We do not have a code-breaking procedure for randomization as the study isunblinded, except for analysis. All protocol amendmentsTable 3: Variables, Measures and Methods of AnalysisVariable/Outcome Hypothesis Outcome Measure Methods of Analysis1) Primary Intervention improvedoutcome from baselineto 6 monthsa) Adherence at 12 months Percent adherence in previous 30 days>95% [binary]Chi-squared testb) Suppression of HIV viral load at 12 months Viral load ≤400 copies/ml [binary] Chi-squared test2) SecondaryAdherence percentage at 12 monthsimprovement occurred Adherence % (>95%) [binary] Chi-squared testHIV viral load at 12 months improvement occurred Viral load (copies) T-testImmune reconstitution (change in CD4 T cellcount from baseline)improvement occurred Cd4 T-cells/mm3 (continuous) T-testTime to virological failure Improvement occurred Virological failure after successfulsuppressionKaplan-Meier survivalanalysisWeight gain [lbs] and BMI improvement occurred Change in weight (lbs) and BMI[continuous]T-testOccurrence of opportunistic infections (OIs) improvement occurred Presence of AIDS definingopportunistic infection [binary]Chi-squared testTime to reporting of adverse drug events (ADEs) improvement occurred Presence of drug-related adverse event[time to event]Kaplan-Meier survivalanalysisDeaths (all cause) improvement occurred All-cause mortality [binary] Chi-squared test and Kaplan-Meier survival analysisSF-12 improvement occurred Quality pf life questionnaire[continuous]T-testSatisfaction with care provided improvement occurred Questionnaire [continuous] T-testLevel of disclosure of HIV status improvement occurred Disclosed to a family member [binary] Chi-squared testImpression of stigma improvement occurred Questionnaire [continuous] T-testFamily dyamics improvement occurred Questionnaire [continuous] T-testEmployment attendance improvement occurred Questionnaire [continuous] T-testHousehold member school attendance improvement occurred Questionnaire [continuous] T-testCell phones lost/stolen improvement occurred Presence of cellphone [binary] Poisson regressionStopped taking HAART improvement occurred Self-report [binary] Chi-squared testRequired active tracing for 12 month follow-up improvement occurred Field officers [binary] Chi-squared test3) Subgroup Analyses: Regression methods withappropriate interaction termUrban vs. rural Distance affectsadherenceFemale vs. male Sex affects adherencePhone ownership (owned vs. shared) Ownership affectsadherenceLevel of education Low education affectsadherence4) Sensitivity Analyses: improvement occurred All outcomesa) Per protocol analysis a) Chi-squared/T-test testb) Adjusting for baseline covariates b) Multivariable regressionc) clustering among individuals within a clinic c) GEEIMPORTANT REMARKS:• The GEE [11] is a technique that allows to specify the correlation structure between patients within a hospital and this approach produces unbiasedestimates under the assumption that missing observations will be missing at random. An amended approach of weighted GEE will be employed ifmissingness is found not to be at random [12].• In all analyses results will be expressed as coefficient, standard errors, corresponding 95% and associated p-values.• Goodness-of-fit will be assessed by examining the residuals for model assumptions and chi-squared test of goodness-of-fit.Bonferroni method will be used to adjust the overall level of significance for multiple secondary outcomes.Trials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 8 of 10(page number not for citation purposes)will be approved first by the study primary investigators(RTL, JK, LG, and FP). The investigators have nocompeting interests. We will not provide post-trial careusing SMS until approval from the ART funding body.All study results will be publicly available.DiscussionThe intervention being tested provides the opportunityto improve health care delivery in resource limitedsettings. Our study is one of several planned randomizedtrials evaluating cell-phone based technology for adher-ence. In other settings, Collier et al. demonstrated that anintensive regular telephone-based adherence counsellingintervention did not significantly improve adherence toHAART in the United States, Italy, and Puerto Rico [8]. Ina separate randomized trial in the United States, astructured telephone counselling intervention didimprove adherence to HAART and there was a trendtoward improved clinical outcomes [9]. A recentlypiloted SMS text reminder to improve adherence toART among Los Angeles youths was acceptable andshowed early benefit on adherence [10]. In anotherstudy, a structured cell phone intervention to help HIVpatients attending an inner-city clinic in Texas quitsmoking was highly successful [10]. We feel that thebenefits of mobile telephony in resource limited settingsmay be greater than in countries with developedeconomies, since they are more widely used in manage-ment of daily life activities, and mark a great contrast topre-mobile phone era communication infrastructures.Additionally, our study is unique in that it focuses on asimple structured SMS protocol without a specifiedcounselling intervention. Thus we are directly testingthe ability for improved, efficient communications tohave an impact on patient care.The multi-site randomized controlled trial design wasspecifically designed to incorporate a broad sampling ofpopulations attending ART care clinics in Kenya. Thisapproach risks diluting the statistical power to detecttreatment responses which could be more easily seen inmore homogenous patient groups. However, we feelthere is a common thread of impact of cell phone usageacross all populations in the region. This study designand analysis plan will allow us to evaluate several factorsthat may contribute a variable array of patient benefits.We are also aware that by consenting and participating inthis study, both the healthcare providers and studysubjects (including controls), are made more aware ofthe potential benefits of increased cell phone commu-nications even outside the SMS protocol. This is knownas the Hawthorne effect of participation in clinical trials,and may reduce the power to compare the effect of theSMS intervention against the true standard of care seenin non-study environments. Since it would be unethicalto restrict communications between health care provi-ders and patients, we have applied for ethics approval tocompare adherence and other outcomes in this clinicaltrial with non-trial participants at the same or similarclinics. We recognize that blinding participants in a trialsuch as ours is impossible. However, our SMS texts aredelivered in such a way as to a) reduce likelihood ofdisclosure to others around the patient and b) to act as areminder of health, rather than HIV status, as our textssimply state ‘how are you?’All factors contributing to the success or failure of theintervention to improve health care management ofpatients are unlikely to have been predicted a priori.Therefore the results of this trial, including the qualita-tive nested studies and experiences of participatingclinicians, will not only test the effectiveness of thedescribed intervention protocol, but will instruct furtherdevelopment of the use of mobile telephony to improvehealth management in resource limited settings.Competing interestsThe authors declare that they have no competinginterests.Authors’ contributionsRTL conceived of the study. AK, EN, SB, PR, WJ, JH, andMC initiated the study design and JK and LG helped withimplementation. RTL, JK, LG, and FP are grant holders.LT and EM provided statistical expertise in clinical trialdesign and RN is conducting the primary statisticalanalysis. All authors contributed to refinement of thestudy protocol and approved the final manuscript.AppendixPrimary Outcome MeasuresHAART = highly active antiretroviral therapy.Primary binary outcomes (12 months post initiation ofHAART)1. Self-reported adherence (>95%) in previous 30days)2. Suppressed HIV viral load (≤400 copies/ml)AcknowledgementsThe authors would like to thank the many clinic staff and patients whocontributed to the design and optimization of the mobile phoneintervention. Funding. United States Centers for Disease Control(Kenya)References1. Wood E, Hogg RS, Yip B, Harrigan PR, O’Shaughnessy MV andMontaner JS: Effect of medication adherence on survival ofHIV-infected adults who start highly active antiretroviralTrials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 9 of 10(page number not for citation purposes)therapy when the CD4+ cell count is 0.200 to 0.350 × 10(9)cells/L. Annals of internal medicine 2003, 139:810–816.2. UNAIDS: AIDS Epidemic Update.2008 http://data.unaids.org/pub/EPISlides/2007/2007_epiupdate_en.pdf, (Accessed November26, 2008).3. Lester RT, Gelmon L and Plummer FA: Cell phones: tighteningthe communication gap in resource-limited antiretroviralprogrammes? Aids 2006, 20:2242–2244.4. Lester R and Karanja S: Mobile phones: exceptional tools forHIV/AIDS, health, and crisis management. Lancet Infect Dis2008, 8:738–739.5. Rosen S, Fox MP and Gill CJ: Patient retention in antiretroviraltherapy programs in sub-Saharan Africa: a systematicreview. PLoS Med 2007, 4:e298.6. Montori VM, Permanyer-Miralda G, Ferreira-Gonzalez I, Busse JW,Pacheco-Huergo V, Bryant D, Alonso J, Akl EA, Domingo-Salvany A,Mills E, Wu P, Schunemann HJ, Jaeschke R and Guyatt GH: Validityof composite end points in clinical trials. Bmj 2005,330:594–596.7. Liu H, Miller LG, Hays RD, Golin CE, Wu T, Wenger NS andKaplan AH: Repeated measures longitudinal analyses of HIVvirologic response as a function of percent adherence, dosetiming, genotypic sensitivity, and other factors. J AcquirImmune Defic Syndr 2006, 41:315–322.8. Little RJ and Rubin DB: Statistical Analysis with Missing Data.New York, NY: Wiley; 22002.9. Reynolds NR, Testa MA, Su M, Chesney MA, Neidig JL, Frank I,Smith S, Ickovics J and Robbins GK: Telephone support toimprove antiretroviral medication adherence: a multisite,randomized controlled trial. J Acquir Immune Defic Syndr 2008,47:62–68.10. Vidrine DJ, Arduino RC, Lazev AB and Gritz ER: A randomizedtrial of a proactive cellular telephone intervention forsmokers living with HIV/AIDS. Aids 2006, 20:253–260.11. Hardin JW: Generalized Estimating Equations. New York:Chapman and Hall/CRC; 2001.12. Diggle PJ, Liang KY and Zeger S: Analysis of Longitudinal Data.Oxford: Oxford Science Publications; 1994.Publish with BioMed Central   and  every scientist can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime."Sir Paul Nurse, Cancer Research UKYour research papers will be:available free of charge to the entire biomedical communitypeer reviewed and published immediately upon acceptancecited in PubMed and archived on PubMed Central yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralTrials 2009, 10:87 http://www.trialsjournal.com/content/10/1/87Page 10 of 10(page number not for citation purposes)


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