A Bayesian averted infection framework for PrEP trials with low numbers of HIV infections: application to the results of the DISCOVER trial.
A Bayesian averted infection framework for PrEP trials with low numbers of HIV infections: application to the results of the DISCOVER trial.
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DOI：
10.1016/s2352-3018(20)30192-2
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发表时间：
2020-11
期刊：
影响因子：
--
通讯作者：
Dunn DT
中科院分区：
文献类型：
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作者：
Glidden DV;Stirrup OT;Dunn DT
HIV暴露前预防候选药物(PrEP)的试验可能在新药物(NPrEP)和口服联合配方恩曲他滨加替诺福韦富马酸(F/TDF)之间随机进行。这一设计在设计和解释方面提出了独特的挑战。首先，有了两个活跃的手臂，艾滋病毒的发病率可能会很低。其次，F/TDF的有效性因人群而异；因此，武器之间类似的艾滋病毒发病率可能与nPrEP的广泛有效性一致。我们提出了一个两部分的方法来处理试验结果。首先，我们使用贝叶斯方法来结合关于在没有PrEP的情况下关于背景试验HIV发病率的假设，可能通过外部数据来扩大。在此基础上，我们估计并比较两个试验组中每个试验组中避免(或预防)艾滋病毒感染的数量，计算避免感染比率(AIR)。我们将这些方法应用于最近完成的替诺福韦丙氨酰胺联合恩曲他滨(F/TAF)治疗PrEP的试验。我们的框架表明，利用外部信息来估计避免的感染和空气可以提高主动控制PrEP试验的效率和解释力。
Trials of candidate agents for HIV pre-exposure prophylaxis (PrEP) may randomise between a new agent (nPrEP) and oral co-formulated emtricitabine plus tenofovir disoproxil fumerate (F/TDF). This design presents unique challenges in design and interpretation. First with two active arms, HIV incidence may be low. Second, F/TDF effectiveness varies across populations; thus, similar HIV incidence between arms could be consistent with a wide range of effectiveness for the nPrEP. We propose a two-part approach to trial results. First, we use Bayesian methods to incorporate assumptions about the background trial HIV incidence in the absence of PrEP, possibly augmented by external data. Based on this, we estimate and compare the number of averted (or prevented) HIV infections in each of the two trial arms, calculating the averted infections ratio (AIR). We apply these methods to a recently completed trial of tenofovir alafenamide with emtricitabine (F/TAF) for PrEP. Our framework demonstrates that leveraging external information to estimate averted infections and the AIR enhances the efficiency and interpretation of active-controlled PrEP trials.