Cystic Fibrosis Therapeutics Development Network Coordinating Center, Seattle Children's Hospital, Seattle, WA, United States of America; Department of Pediatrics, University of Washington, Seattle, WA, United States of America; Department of Biostatistics, University of Washington, Seattle, WA, United States of America.
Department of Epidemiology, University of Washington, Seattle, WA, United States of America.
J Cyst Fibros. 2022 Mar;21(2):293-299. doi: 10.1016/j.jcf.2021.11.007. Epub 2021 Dec 5.
Given future challenges in conducting large randomized, placebo controlled trials for future CF therapeutics development, we evaluated the potential for using external historical controls to either enrich or replace traditional concurrent placebo groups in CF trials.
The study included data from sequentially completed, randomized, controlled clinical trials, EPIC and OPTIMIZE respectively, evaluating optimal antibiotic therapy to reduce the risk of pulmonary exacerbation in children with early Pseudomonas aeruginosa infection. The primary treatment effect in OPTIMIZE, the risk of pulmonary exacerbation associated with azithromycin, was re-estimated in alternative designs incorporating varying numbers of participants from the earlier trial (EPIC) as historical controls. Bias and precision of these estimates were characterized. Propensity scores were derived to adjust for baseline differences across study populations, and both Poisson and Cox regression were used to estimate treatment efficacy.
Replacing 86 OPTIMIZE placebo participants with 304 controls from EPIC to mimic a fully historically controlled trial resulted an 8% reduction in risk of pulmonary exacerbations (Hazard ratio (HR):0.92 95% CI 0.61, 1.34) when not adjusting for key baseline differences between study populations. After adjustment, a 37% decrease in risk of exacerbation (HR:0.63, 95% CI 0.50, 0.80) was estimated, comparable to the estimate from the original trial comparing the 86 placebo participants to 77 azithromycin participants on azithromycin (45%, HR:0.55, 95% CI: 0.34, 0.86). Other adjusted approaches provided similar estimates for the efficacy of azithromycin in reducing exacerbation risk: pooling all controls from both studies provided a HR of 0.60 (95% x`CI 0.46, 0.77) and augmenting half the OPTIMIZE placebo participants with EPIC controls gave a HR 0.63 (95% CI 0.48, 0.82).
The potential exists for future CF trials to utilize historical control data. Careful consideration of both the comparability of controls and of optimal methods can reduce the potential for biased estimation of treatment effects.
鉴于未来在开展大型随机、安慰剂对照试验以开发新的 CF 疗法方面所面临的挑战，我们评估了利用外部历史对照来丰富或替代 CF 试验中传统同期安慰剂组的潜力。
这项研究纳入了分别连续完成的、随机、对照临床试验 EPIC 和 OPTIMIZE 的数据，这两项试验分别评估了优化抗生素治疗方案以降低早期铜绿假单胞菌感染患儿肺部恶化风险的效果。OPTIMIZE 中的主要治疗效果，即阿奇霉素相关的肺部恶化风险，通过纳入来自先前试验（EPIC）的不同数量的参与者作为历史对照，在替代设计中重新估计。描述了这些估计的偏差和精度。推导了倾向评分来调整研究人群之间的基线差异，同时使用泊松回归和 Cox 回归来估计治疗效果。
在不调整研究人群之间关键基线差异的情况下，用 EPIC 中 304 名对照替换 OPTIMIZE 中 86 名安慰剂参与者来模拟完全历史对照试验，可使肺部恶化风险降低 8%（风险比 (HR)：0.92，95%CI：0.61，1.34）。调整后，估计恶化风险降低 37%（HR：0.63，95%CI：0.50，0.80），与比较 86 名安慰剂参与者和 77 名阿奇霉素参与者的原始试验中估计的阿奇霉素降低恶化风险的效果相当（45%，HR：0.55，95%CI：0.34，0.86）。其他调整方法也提供了阿奇霉素降低恶化风险效果的类似估计：从两项研究中汇总所有对照，HR 为 0.60（95%CI：0.46，0.77）；用 EPIC 对照扩充 OPTIMIZE 中一半的安慰剂参与者，HR 为 0.63（95%CI：0.48，0.82）。
未来 CF 试验有可能利用历史对照数据。仔细考虑对照的可比性和最佳方法，可以降低治疗效果估计的偏倚风险。
