Estimating per-protocol effects in external comparator analyses using real-world data

Analysis of single arm trials complemented with external comparator arms (ECAs) may be used to support evidence of effectiveness of novel therapies in oncology research when a randomized trial is unavailable or unfeasible. However, the intention-to-treat effect, which is a common target of estimation in ECA studies, is difficult to interpret when there are differences in adherence between the trial and ECA. This paper describes an approach to estimation of per-protocol effects in ECA studies using the target trial emulation framework for study design and analysis based on the results from an exploratory case study (TBASEL). We highlight challenges, potential solutions and future opportunities from the perspectives of protocol specification, data suitability and analysis, to help guide future implementations of per-protocol effects in ECAs.