Predicting viral load suppression by self-reported adherence, pharmacy refill counts and real time medication monitoring among people living with HIV in Tanzania.

INTRODUCTION: Monitoring of adherence to antiretroviral treatment (ART) is of utmost importance to prevent treatment failure. Several measures to monitor adherence have been applied in low-resource settings and they all have pros and cons. Our objective was to examine whether any of the following adherence measures is a better predictor of participants' viral load suppression: (1) self-report, (2) pharmacy refill count, (3) Real Time Medication Monitoring (RTMM), (4) a combination of self-report and pharmacy refill count or (5) all three adherence assessment methods combined. METHODOLOGY: This was a post-hoc analysis of data from our 48-week REMIND-HIV randomized controlled trial in which adherence to ART was measured using self-report, pharmacy refill counts and RTMM among ART-experienced adults living with HIV subjectively judged to be nonadherent to ART. For each adherence measure, we calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for predicting virological failure defined as a viral load (VL) of > 20 copies/mL. To determine at which percentage of adherence the prediction was strongest, we evaluated adherence cut-offs of 80%, 85%, 90%, 95% and 100% using receiver operating characteristic (ROC) curves. VL data were obtained after 48 weeks of follow-up in the trial. RESULTS: A total of 233 people living with HIV (PLHIV) were included in this analysis. When comparing the ability of self-reported adherence with pharmacy refill count and RTMM adherence to predict viral load > 20 copies/ml, self-reported adherence had the lowest sensitivity, ranging from 6 to 17%, but the highest specificity, ranging from 100 to 86%, depending on cut-off values from 80 to 100%. Area under the ROC curves (AUC) were 0.54 for RTMM, 0.56 for pharmacy refill count and 0.52 for self-report, indicating low discriminatory capacity for each of the adherence measures. When we combined the self-report and pharmacy refill count measures, sensitivity increased, ranging from 28 to 57% but specificity decreased, ranging from 83 to 53%. When all three measures were combined, we observed the highest value of sensitivity, ranging from 46 to 92%, and PPV, ranging from 32 to 36%, at high cut-offs ranging from 80 to 100%. Upon combination of three adherence measures, the AUC increased to 0.59. CONCLUSION: Our results show that adherence assessed exclusively by self-report, pharmacy refill count or RTMM were insufficiently sensitive to predict virologic failure. Sensitivity markedly improved by combining all three measures, but the practical feasibility of such an approach would need to be studied.

Effect of Digital Adherence Tools on Adherence to Antiretroviral Treatment Among Adults Living With HIV in Kilimanjaro, Tanzania: A Randomized Controlled Trial.

BACKGROUND: Lifelong adherence to antiretroviral treatment remains challenging for people living with HIV (PLHIV). The aim of this study was to investigate whether any of 2 digital adherence tools could improve adherence among PLHIV in Kilimanjaro, Tanzania. METHODS: We performed a parallel 3-arm, nonblinded, randomized controlled trial with 1:1:1 allocation. We included adults aged between 18 and 65 years, living in Kilimanjaro region, and who were on antiretroviral treatment for at least 6 months. Their adherence, as judged by the study nurses, had to be suboptimal. In one arm, participants received reminder short message service (SMS) texts, followed by a question SMS. In the second arm, participants received a real-time medication monitoring (RTMM) device (Wisepill) with SMS reminders. In the third arm, participants received standard care only. The primary outcome of mean adherence over 48 weeks was compared between arms using between-group t tests in a modified intention-to-treat analysis. RESULTS: In each arm, we randomized 83 participants: data of 82 participants in the RTMM arm, 80 in the SMS arm, and 81 in the standard care arm were analyzed. The average (over 48 weeks) adherence in the SMS, RTMM, and control arms was 89.6%, 90.6%, and 87.9% for pharmacy refill; 95.9%, 95.0%, and 95.2% for self-report in the past week; and 97.5%, 96.6%, and 96.9% for self-report in the past month, respectively (P values not statistically significant). CONCLUSIONS: Receiving reminder SMS or RTMM combined with feedback about adherence levels and discussion of strategies to overcome barriers to adherence did not improve adherence to treatment and treatment outcome in PLHIV. CLINICAL TRIAL NUMBER: PACTR201712002844286.

Implementation and effectiveness of evriMED with short messages service (SMS) reminders and tailored feedback compared to standard care on adherence to treatment among tuberculosis patients in Kilimanjaro, Tanzania: proposal for a cluster randomized controlled trial.

BACKGROUND: Adherence to tuberculosis (TB) treatment is challenging because of many factors. The World Health Organization has recommended the use of digital adherence monitoring technologies in its End TB Strategy. However, evidence on improving adherence is limited. EvriMED is a real-time medication-monitoring device which was found to be feasible and acceptable in a few studies in Asia. In Tanzania, however, there may be challenges in implementing evriMED due to stigmatization, network and power access, accuracy, and cost effectiveness, which may have implications for treatment outcome. We propose a pragmatic cluster randomized trial to investigate the effectiveness of evriMED with reminder cues and tailored feedback on adherence to TB treatment in Kilimanjaro, Tanzania. METHODS/DESIGN: We will create clusters in Kilimanjaro based on level of health care facility. Clusters will be randomized in an intervention arm, where evriMED will be implemented, or a control arm, where standard practice directly observed treatment will be followed. TB patients in intervention clusters will take their medication from the evriMED pillbox and receive tailored feedback. We will use the 'Stages of Change' model, which assumes that a person has to go through the stages of pre-contemplation, contemplation, preparation, action, and evaluation to change behavior for tailored feedback on adherence reports from the device. DISCUSSION: If the intervention shows a significant effect on adherence and the devices are accepted, accurate, and sustainable, the intervention can be scaled up within the National Tuberculosis Programmes. TRIAL REGISTRATION: Pan African Clinical Trials Registry, PACTR201811755733759 . Registered on 8 November 2018.