Novartis, Basel, Switzerland.
Clin Pharmacol Ther. 2020 Apr;107(4):806-816. doi: 10.1002/cpt.1723. Epub 2019 Dec 17.
Randomized controlled trials are the gold standard to investigate efficacy and safety of new treatments. In certain settings, however, randomizing patients to control may be difficult for ethical or feasibility reasons. Borrowing strength using relevant individual patient data on control from external trials or real-world data (RWD) sources may then allow us to reduce, or even eliminate, the concurrent control group. Naive direct use of external control data is not valid due to differences in patient characteristics and other confounding factors. Instead, we suggest the rigorous application of meta-analytic and propensity score methods to use external controls in a principled way. We illustrate these methods with two case studies: (i) a single-arm trial in a rare cancer disease, using propensity score matching to construct an external control from RWD; (ii) a randomized trial in children with multiple sclerosis, borrowing strength from past trials using a Bayesian meta-analytic approach.
随机对照试验是研究新疗法疗效和安全性的金标准。然而，在某些情况下，由于伦理或可行性原因，将患者随机分配到对照组可能具有挑战性。那么，借用来自外部试验或真实世界数据（RWD）来源的相关个体患者数据来增强对照组力量，可能会减少甚至消除同期对照组。由于患者特征和其他混杂因素的差异，直接使用外部对照数据是不可行的。相反，我们建议严格应用荟萃分析和倾向评分方法，以有原则的方式使用外部对照。我们用两个案例研究来说明这些方法：（i）一种罕见癌症疾病的单臂试验，使用倾向评分匹配从 RWD 中构建外部对照；（ii）一种多发性硬化症儿童的随机试验，使用贝叶斯荟萃分析方法从过去的试验中借力。
