Supplementary materials: Augmenting external control arms using Bayesian borrowing: a case study in first-line non-small cell lung cancer

These are peer-reviewed supplementary materials for the article 'Augmenting external control arms using Bayesian borrowing: a case study in first-line non-small cell lung cancer' published in the Journal of Comparative Effectiveness Research.Supplementary figure 1aSupplementary figure 1bSupplementary figure 2aSupplementary figure 2bSupplementary figure 3Supplementary table 1Supplementary table 2Supplementary table 3Supplementary table 4Supplementary table 5Supplementary table 6Aim: This study aimed to improve comparative effectiveness estimates and discuss challenges encountered through the application of Bayesian borrowing (BB) methods to augment an external control arm (ECA) constructed from real-world data (RWD) using historical clinical trial data in first-line non-small-cell lung cancer (NSCLC). Materials & methods: An ECA for a randomized controlled trial (RCT) in first-line NSCLC was constructed using ConcertAI Patient360™ to assess chemotherapy with or without cetuximab, in the bevacizumab-inappropriate subpopulation. Cardinality matching was used to match patient characteristics between the treatment arm (cetuximab + chemotherapy) and ECA. Overall survival (OS) was assessed as the primary outcome using Cox proportional hazards (PH). BB was conducted using a static power prior under a Weibull PH parameterization with borrowing weights from 0.0 to 1.0 and augmentation of the ECA from a historical control trial. Results: The constructed ECA yielded a higher overall survival (OS) hazard ratio (HR) (HR = 1.53; 95% CI: 1.21–1.93) than observed in the matched population of the RCT (HR = 0.91; 95% CI: 0.73–1.13). The OS HR decreased through the incorporation of BB (HR = 1.30; 95% CI: 1.08–1.54, borrowing weight = 1.0). BB was applied to augment the RCT control arm via a historical control which improved the precision of the observed HR estimate (1.03; 95% CI: 0.86–1.22, borrowing weight = 1.0), in comparison to the matched population of the RCT alone. Conclusion: In this study, the RWD ECA was unable to successfully replicate the OS estimates from the matched population of the selected RCT. The inability to replicate could be due to unmeasured confounding and variations in time-periods, follow-up and subsequent therapy. Despite these findings, we demonstrate how BB can improve precision of comparative effectiveness estimates, potentially aid as a bias assessment tool and mitigate challenges of traditional methods when appropriate external data sources are available.

本数据集为发表于《比较疗效研究杂志》的论文《利用贝叶斯借用的外部控制臂增强：一线非小细胞肺癌案例研究》的同行评审补充材料。补充图1a、补充图1b、补充图2a、补充图2b、补充图3、补充表1、补充表2、补充表3、补充表4、补充表5、补充表6。研究目的：本研究的目的是通过将贝叶斯借用（BB）方法应用于构建基于真实世界数据（RWD）的外部控制臂（ECA），并使用一线非小细胞肺癌（NSCLC）的历史临床试验数据，以提高比较疗效估计，并讨论所遇到挑战。材料与方法：利用ConcertAI Patient360™构建了一线NSCLC随机对照试验（RCT）的外部控制臂，以评估在贝伐珠单抗不适用亚群中化疗是否联合西妥昔单抗。采用基数匹配方法，对治疗臂（西妥昔单抗+化疗）与ECA之间的患者特征进行匹配。以总生存期（OS）作为主要结局，使用Cox比例风险模型（PH）进行评估。在Weibull PH参数化下，使用静态功率先验进行BB，借权值从0.0到1.0，并对ECA从历史对照试验中进行增强。结果：构建的ECA产生的总生存期（OS）风险比（HR）高于在RCT匹配人群中的观察值（HR = 1.53；95% CI：1.21–1.93，HR = 0.91；95% CI：0.73–1.13）。随着BB的引入，OS HR有所下降（HR = 1.30；95% CI：1.08–1.54，借权值 = 1.0）。通过历史对照试验，将BB应用于增强RCT控制臂，提高了观察HR估计的精确性（1.03；95% CI：0.86–1.22，借权值 = 1.0），与仅RCT匹配人群相比。结论：在本研究中，基于RWD的ECA未能成功复制所选RCT匹配人群的OS估计。未能复制的原因可能是未测量的混杂因素和时间段的差异、随访及后续治疗。尽管如此，我们展示了BB如何提高比较疗效估计的精确性，可能作为偏差评估工具，并在适当的外部数据源可用时，减轻传统方法的挑战。