Trials of candidate agents for HIV pre-exposure prophylaxis (PrEP) might randomly assign participants to be given a new PrEP agent or oral coformulated tenofovir disoproxil fumarate plus emtricitabine. This design presents unique challenges in interpretation. First, with two active arms, HIV incidence might be low. Second, the effectiveness of tenofovir disoproxil fumarate plus emtricitabine varies across populations; thus, similar HIV incidence between groups could be consistent with a wide range of effectiveness for the new PrEP. We propose a two-part approach to trial results. First, we use Bayesian methods to incorporate assumptions about the background incidence of HIV in the trial in the absence of PrEP, possibly augmented by external data. On the basis of the estimated background incidence, we estimate and compare the number of averted (or prevented) HIV infections in each of the two trial groups, calculating the averted infections ratio. We apply these methods to a completed trial of tenofovir alafenamide plus emtricitabine for PrEP. Our framework shows that leveraging external information to estimate averted infections and the averted infections ratio enhances the efficiency and interpretation of active-controlled PrEP trials.

Objectives

The averted infections ratio (AIR) is a novel measure for quantifying the preservation-of-effect in active-control non-inferiority clinical trials with a time-to-event outcome. In the main formulation, the AIR requires an estimate of the counterfactual placebo incidence rate. We describe two approaches for calculating confidence limits for the AIR given a point estimate of this parameter, a closed-form solution based on a Taylor series expansion (delta method) and an iterative method based on the profile-likelihood.

Methods

For each approach, exact coverage probabilities for the lower and upper confidence limits were computed over a grid of values of (1) the true value of the AIR (2) the expected number of counterfactual events (3) the effectiveness of the active-control treatment.

Results

Focussing on the lower confidence limit, which determines whether non-inferiority can be declared, the coverage achieved by the delta method is either less than or greater than the nominal coverage, depending on the true value of the AIR. In contrast, the coverage achieved by the profile-likelihood method is consistently accurate.

Conclusions

The profile-likelihood method is preferred because of better coverage properties, but the simpler delta method is valid when the experimental treatment is no less effective than the control treatment. A complementary Bayesian approach, which can be applied when the counterfactual incidence rate can be represented as a prior distribution, is also outlined.

Tenofovir disoproxil fumarate combined with emtricitabine is a highly effective oral pre-exposure prophylaxis (PrEP) agent for preventing the acquisition of HIV. This effectiveness has consequences for the design and analysis of trials assessing experimental PrEP regimens, which now generally include an active-control tenofovir disoproxil fumarate plus emtricitabine group, rather than a placebo group, as a comparator. Herein, we describe major problems in the interpretation of the primary measure of effectiveness proposed for these trials, namely the ratio of HIV incidence in the experimental agent group to that in the active-control group. We argue that valid interpretation requires an assumption about one of two parameters: either the incidence among trial participants had they not received PrEP or the effectiveness of tenofovir disoproxil fumarate plus emtricitabine within the trial. However, neither parameter is directly observed because of the absence of a no-treatment group, thus requiring the use of external evidence or subjective judgment. We propose an alternative measure of effectiveness based on the concept of averted infections, which incorporates one of these parameters. The measure is simple to interpret, has clinical and public health relevance, and is a natural preservation-of-effect criterion for assessing statistical non-inferiority. Its adoption could also allow the use of smaller sample sizes, currently a major barrier to the assessment of experimental PrEP regimens.

Introduction

Randomized trials of new agents for HIV pre-exposure prophylaxis (PrEP) compare against emtricitabine and tenofovir disoproxil fumarate (F/TDF), without a placebo group. We used the well-characterized adherence-efficacy relationship for F/TDF to back-calculate the (non-PrEP) counterfactual background HIV incidence (bHIV) in a randomized trial of a novel PrEP agent and estimate comparative efficacy (to counterfactual bHIV).

Methods

The DISCOVER trial (ClinicalTrials.gov: NCT02842086) randomized 5387 men who have sex with men (MSM) and transgender women who have sex with men and demonstrated non-inferiority of emtricitabine and tenofovir alafenamide (F/TAF) to F/TDF (HIV incidence rate ratio [IRR] 0·47, 95% CI: 0·19 to 1.15). Tenofovir diphosphate (TFV-DP) levels in dried blood spots (DBS) were assessed for all diagnosed with HIV and in a random 10% of the cohort. We used a Bayesian model with a diffuse prior distribution, derived from established data relating tenofovir diphosphate levels to HIV prevention efficacy. This prior, combined with the F/TDF seroconversion rate and tenofovir diphosphate levels in DISCOVER, yielded Bayesian inferences on the counterfactual bHIV.

Results

There were six versus 11 postbaseline HIV infections (0.14 vs. 0.25/100 person-years [PY]) on F/TAF and F/TDF respectively. Of the 11 on F/TDF, 10 had low, none had medium and one had high tenofovir diphosphate levels; among HIV-negative controls, 5% of the person-time years had low, 9% had medium and 86% had high TFV-DP levels. A non-informative prior distribution for counterfactual bHIV, combined with the prior for TFV-DP level-efficacy relationship, yielded a posterior counterfactual bHIV of 3·4 infections/100 PY (0.80 Bayesian credible interval [CrI] 1·9 to 5·9), which suggests a median HIV efficacy of 96% (0.95 CrI [88% to 99%]) for F/TAF and 93% (0.95 CrI [87% to 96%]) for F/TDF compared to bHIV.

Conclusions

Based on the established connection of drug concentrations to PrEP prevention efficacy, a Bayesian framework can be used to estimate a synthetic non-PrEP control group in randomized, active-controlled PrEP trials that include a F/TDF-comparator group.