Aim: Single-arm trials with external control arms (ECAs) have gained popularity in oncology. ECAs may consist of primary data from previous trials, electronic health records (EHRs) or aggregate data from the literature. We sought to provide a description of how such studies achieve similarity of patients, comparability of data quality and outcome assessment. Materials & methods: In a stratified convenience sample of 15 studies, five used primary data from trials as ECAs, five used secondary data from EHRs and five used aggregate data from the literature. Data were collected from the published literature and public web resources, blinded to the eventual approval decision. Results: Studies using ECAs from primary data and EHR data displayed methods to achieve comparability of information, including matched baseline characteristics. Aggregate data from published studies did not attempt to match covariates. The EHR controls often showed calendar time overlap for collecting information while trial data were mostly historic. Outcome data were not consistently reported across studies. US FDA approval was only seen when primary data from trials or EHR data were used as the ECA, however no ECA in this sample directly contributed to approval. Discussion: In this nonsystematic review of ECAs for single-arm trials, the ECAs derived from primary data collected by other trials or EHRs show patterns of patient comparability, time overlap, and realistic methodological approaches to achieving balance between treatment arms. They are often submitted to regulators while literature-derived aggregate findings as ECA may serve as benchmarks for pipeline decisions.
Keywords: adaptive clinical trials; clinical trials; nonrandomized trials; oncology; real-world evidence; trial design.