Abstract

The design of HIV prevention trials in the context of effective HIV preventive methods is a challenge. Alternate designs, including using non-randomised ‘observational control arms’ have been proposed. We used HIV simulated vaccine efficacy trials (SiVETs) to show pitfalls that may arise from using such observational controls and suggest how to conduct the analysis in the face of the pitfalls. Two SiVETs were nested within previously established observational cohorts of fisherfolk (FF) and female sex workers (FSW) in Uganda. SiVET participants received a licensed Hepatitis B vaccine in a schedule (0, 1 and 6 months) similar to that for a possible HIV vaccine efficacy trial. All participants received HIV counselling and testing every quarter for one year to assess HIV incidence rate ratio (IRR) between SiVET and non-SiVET (observational data). Propensity scores, conditional on baseline characteristics were calculated for SiVET participation and matched between SiVET and non-SiVET in the period before and during the SiVET study. We compared IRR before and after propensity score matching (PSM). In total, 3989 participants were enrolled into observational cohorts prior to SiVET, (1575 FF prior to Jul 2012 and 2414 FSW prior to Aug 2014). SiVET enrolled 572 participants (Jul 2012 to Apr 2014 in FF and Aug 2014 to Apr 2017 in FSW), with 953 non-SiVET participants observed in the SiVET concurrent period and 2928 from the pre-SiVET period (before Jul 2012 in FF or before Apr 2014 in FSW). Imbalances in baseline characteristics were observed between SiVET and non-SiVET participants in both periods before PSM. Similarly, HIV incidence was lower in SiVET than non-SiVET; SiVET-concurrent period, IRR = 0.59, 95% CI 0.31–0.68, p = 0.033 and pre-SiVET period, IRR = 0.77, 95% CI 0.43–1.29, p = 0.161. After PSM, participants baseline characteristics were comparable and there were minimal differences in HIV incidence between SiVET and non-SiVET participants. The process of screening for eligibility for efficacy trial selects participants with baseline characteristics different from the source population, confounding any observed differences in HIV incidence. Propensity score matching can be a useful tool to adjust the imbalance in the measured participants’ baseline characteristics creating a counterfactual group to estimate the effect of interventions on HIV incidence.

Highlights

  • The design of HIV prevention trials in the context of effective HIV preventive methods is a challenge

  • We screened 5902 volunteers and enrolled 3989 (67.6%) participants into the three observational cohorts before any screening was done for the simulated vaccine efficacy trial (SiVET)

  • The results suggest that participation in SiVET showed a decrease in HIV incidence of approximately 23% and 40% from that observed in the non-SiVET in the pre-SiVET and SiVET concurrent periods respectively

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Summary

Introduction

The design of HIV prevention trials in the context of effective HIV preventive methods is a challenge. With the AIR approach, investigators might propose use of incidence from, e.g., a run-in period in a registration cohort, epidemiological surveillance systems or sexually transmitted infection incidence from another trial as a surrogate for hypothetical placebo arm HIV i­ncidence[11]. These sources of incidence data introduce significant uncertainty and are likely to provide a biased estimate due to population and study differences. Propensity score provides the probability of treatment assignment conditional on measured baseline characteristics This allows us to design and analyze an observational study mimicking some of the attributes of a randomized controlled trial. A similar approach has been used previously to balance baseline characteristics between trials and observational data or other studies to estimate treatment e­ ffects[14,15,16,17]

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