Division of Biostatistics, University of Minnesota, Minneapolis, MN, 55414, USA.
Cooper Medical School of Rowan University and Medicine, Division of Infectious Diseases, Cooper University Hospital, Camden, New Jersey, 08103, USA.
Biostatistics. 2024 Jul 1;25(3):617-632. doi: 10.1093/biostatistics/kxad024.
The traditional trial paradigm is often criticized as being slow, inefficient, and costly. Statistical approaches that leverage external trial data have emerged to make trials more efficient by augmenting the sample size. However, these approaches assume that external data are from previously conducted trials, leaving a rich source of untapped real-world data (RWD) that cannot yet be effectively leveraged. We propose a semi-supervised mixture (SS-MIX) multisource exchangeability model (MEM); a flexible, two-step Bayesian approach for incorporating RWD into randomized controlled trial analyses. The first step is a SS-MIX model on a modified propensity score and the second step is a MEM. The first step targets a representative subgroup of individuals from the trial population and the second step avoids borrowing when there are substantial differences in outcomes among the trial sample and the representative observational sample. When comparing the proposed approach to competing borrowing approaches in a simulation study, we find that our approach borrows efficiently when the trial and RWD are consistent, while mitigating bias when the trial and external data differ on either measured or unmeasured covariates. We illustrate the proposed approach with an application to a randomized controlled trial investigating intravenous hyperimmune immunoglobulin in hospitalized patients with influenza, while leveraging data from an external observational study to supplement a subgroup analysis by influenza subtype.
传统的试验范式通常被批评为缓慢、低效和昂贵。利用外部试验数据的统计方法已经出现，通过增加样本量来提高试验效率。然而，这些方法假设外部数据来自以前进行的试验，留下了丰富的尚未有效利用的真实世界数据（RWD）。我们提出了一种半监督混合（SS-MIX）多源可交换性模型（MEM）；一种灵活的两步贝叶斯方法，用于将 RWD 纳入随机对照试验分析。第一步是在修改后的倾向评分上进行 SS-MIX 模型，第二步是 MEM。第一步针对试验人群中的代表性亚组，第二步在试验样本和代表性观察性样本之间的结果存在实质性差异时避免借用。在一项模拟研究中，我们将提出的方法与竞争借用方法进行比较，发现当试验和 RWD 一致时，我们的方法可以有效地借用，而当试验和外部数据在测量或未测量协变量上存在差异时，可以减轻偏差。我们通过应用于一项静脉内高免疫球蛋白免疫球蛋白治疗住院流感患者的随机对照试验来说明该方法，同时利用外部观察性研究的数据来补充流感亚型的亚组分析。
