Meta-Analysis of Bias in Non-Small Cell Lung Cancer External Control Arms That Use Real-World Progression-Free Survival as the End Point.

Abstract

Results from single-arm clinical trials can be contextualized by comparing against external controls (ECs) derived from real-world data (RWD). However, lack of randomization and differences in variable capture between data sources may introduce bias into estimates of treatment effect and standard error, the extent of which can be assessed via meta-analysis of comparisons between clinical trial control arms and their EC replicates. Clinical trial progression-free survival (PFS) outcomes from the 14 chemotherapy control arms of 12 non-small cell lung cancer clinical trials were replicated using the US nationwide deidentified Flatiron Health electronic health record-derived database, with real-world PFS (rwPFS) as the end point. A meta-analysis of log_e hazard ratios (HRs) comparing randomized controlled trial (RCT) and RWD control arms was conducted. For illustration, the meta-analysis results were used to restore correct operating characteristics of a hypothetical prospective single-arm study with EC. With the exception of one outlier, rwPFS outcomes were on average similar to PFS outcomes, albeit with substantial between-study variation. RCT compared with RWD arms differed by a mean log_e HR of -0.001, with a standard deviation of 0.164 (including the outlier). Applying these estimates to adjust error probabilities in a hypothetical prospective EC study revealed that between-study variation of bias in this setting should be adjusted for, to avoid incorrect decision making. The close alignment of results between RCT and RWD increases confidence that RWD ECs using the rwPFS end point in this disease setting can provide context for future single-arm clinical trials despite potential differences in end point assessment.