Risk of Bias Associated with Varying Sampling Strategies for External Comparator Cohorts for Single-Arm Trials: Insights from Aggressive Lymphoma.

Authors

Mikkel Runason Simonsen, Shiva Leisner, Ahmed Ludvigsen Al-Mashhadi, Laurids Østergaard Poulsen, Matthew Maurer, Lasse Hjort Jakobsen, Tarec Christoffer El-Galaly

Published in

Clinical pharmacology and therapeutics. Aug 04, 2026. Epub Aug 04, 2026.

Abstract

Marketing authorizations for oncology drugs are often based on single-arm trials (SATs), and real-world data-based external comparator cohorts (ECCs) are increasingly explored to contextualize results. In retrospective studies, comparators may be identified by time of diagnosis but included based on time of relapse; such sampling strategies can introduce bias, potentially leading to erroneous efficacy conclusions. Simulated diffuse large B-cell lymphoma (DLBCL) cohorts were generated using published time-to-relapse and post-relapse survival distributions. Three ECC sampling strategies were evaluated: naïve (screening and inclusion periods coincide), delayed (inclusion period extends beyond screening), and displacement (screening and inclusion periods shifted relative to each other). Different sampling strategies caused significant changes in the time-to-relapse distribution in the ECC and, by proxy, the estimated 2-year post-relapse overall survival (22.5-52.2%). Naïve sampling consistently resulted in oversampling of early relapses, though bias was reduced with extended inclusion periods; in hypothetical trials, it produced inflated Type I errors (10.5-84.9%) despite α = 0.025. Delayed sampling reduced bias when the inclusion period was sufficiently extended to capture late relapses, yielding unbiased estimates under long delays (Type I error of 2.5% at a 6-year delay). Displacement sampling depended strongly on the degree of shift: moderate shifts minimized bias, whereas long displacements introduced substantial distortion (Type I error of 2.7% and 0.0% at displacements of 2 and 5, respectively). Real-world data-based ECCs in relapsed/refractory oncology are susceptible to selection bias from sampling strategies, particularly through distortions in time-to-relapse, leading to erroneous efficacy conclusions; similar bias may occur in non-oncology settings where time-to-treatment initiation is prognostic.

PMID:
42549598
Bibliographic data and abstract were imported from PubMed on 04 Aug 2026.

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