Abaasa Andrew, Mayanja Yunia, Anywaine Zacchaeus, Kusemererwa Sylvia, Ruzagira Eugene, Kaleebu Pontiano
MRC/UVRI & LSHTM Uganda Research Unit, Entebbe P.O. Box 49, Uganda.
London School of Hygiene & Tropical Medicine (LSHTM), London WC1E 7HT, UK.
Vaccines (Basel). 2025 Aug 8;13(8):844. doi: 10.3390/vaccines13080844.
Assessment of efficacy in HIV prevention trials remains a challenge in the era of widespread use of active controls. We investigated use of counterfactual groups to assess treatment efficacy.
We used data from placebo arms of two previous HIV prevention efficacy trials (Pro2000 vaginal microbicide trial, 2005-2009: ISRCTN64716212 and dapivirine vaginal ring trial, 2013-2016: NCT01539226) and four observational cohorts (two in each of the periods; (a) during the conduct of a simulated HIV vaccine efficacy trial (SiVET), 2012-2017, and (b) prior to SiVET (2005-2011)) and compared HIV prevention efficacy trial targeted outcomes with SiVETs. SiVET participants were administered a licensed hepatitis B vaccine at 0, 1 and 6 months mimicking an HIV vaccine efficacy trial schedule. Participants were tested for HIV quarterly for one year. The probability of the SiVET assignment conditioned on the measured participants' baseline characteristics were estimated using propensity scores (PS) and matched between SiVET and placebo arm of trials. Similar calculations were repeated for observational cohorts in the pre- and during SiVET periods. We compared HIV incidence rate ratio (IRR) between SiVET and the trials or observational data before and after PS matching.
This analysis involved data from 3387 participants; observational cohorts before SiVET 1495 (44.2%), placebo arms of previous trials 367 (10.8%), observational cohorts during SiVET conduct 953 (28.1%) and SiVETs 572 (16.9%). Before propensity score matching (PSM), there were significant imbalances in participants' baseline characteristics between SiVET, and all the other studies and HIV incidence was lower in SiVET. After PSM, the participants' characteristics were comparable. The HIV incidence in SiVET was similar to that in the previous trial, IRR = 1.01 95% CI: 0.16-4.70), = 0.968, and observational data during SiVET, IRR = 0.74, 95% CI 0.34-1.54), = 0.195, but much lower compared to the observational data pre-SiVET, IRR = 0.48, 95% CI: 0.20-1.04), = 0.023.
PSM can be used to create counterfactual groups from other data sources. The best counterfactual group for assessing treatment effect is provided by data collected in the placebo arm of previous trials followed by that from observational data collected concurrently to the current trial (SiVET). Even with PSM, observational data collected prior to the current trial may overestimate treatment effect.
在广泛使用活性对照的时代，评估HIV预防试验的疗效仍然是一项挑战。我们研究了使用反事实组来评估治疗效果。
我们使用了两项先前HIV预防疗效试验（2005 - 2009年的Pro2000阴道杀菌剂试验：ISRCTN64716212和2013 - 2016年的达匹韦林阴道环试验：NCT01539226）的安慰剂组数据以及四个观察性队列（每个时期两个；(a) 在2012 - 2017年模拟HIV疫苗疗效试验（SiVET）进行期间，以及(b) 在SiVET之前（2005 - 2011年）），并将HIV预防疗效试验的目标结果与SiVET进行比较。SiVET参与者在0、1和6个月时接种了许可的乙型肝炎疫苗，模拟HIV疫苗疗效试验的时间表。参与者每季度进行一次HIV检测，持续一年。使用倾向得分（PS）估计基于测量的参与者基线特征的SiVET分配概率，并在SiVET和试验的安慰剂组之间进行匹配。在SiVET之前和期间对观察性队列重复类似计算。我们比较了PS匹配前后SiVET与试验或观察数据之间的HIV发病率比（IRR）。
该分析涉及3387名参与者的数据；SiVET之前的观察性队列1495名（44.2%），先前试验的安慰剂组367名（10.8%），SiVET进行期间的观察性队列953名（28.1%）和SiVETs 572名（16.9%）。在倾向得分匹配（PSM）之前，SiVET与所有其他研究之间参与者的基线特征存在显著不平衡，且SiVET中的HIV发病率较低。PSM之后，参与者的特征具有可比性。SiVET中的HIV发病率与先前试验相似，IRR = 1.01，95% CI：0.16 - 4.70），P = 0.968，以及SiVET期间的观察数据，IRR = 0.74，95% CI 0.34 - 1.54），P = 0.195，但与SiVET之前的观察数据相比要低得多，IRR = 0.48，95% CI：0.20 - 1.04），P = 0.023。
PSM可用于从其他数据源创建反事实组。评估治疗效果的最佳反事实组由先前试验的安慰剂组收集的数据提供，其次是与当前试验同时收集的观察数据（SiVET）。即使采用PSM，当前试验之前收集的观察数据可能会高估治疗效果。
