Considerations for the Integration of Randomized Controlled Trials and Real-World Data
Abstract
As clinical decision-making increasingly moves toward individualized and context-specific treatment recommendations, reliance on any single evidence source, randomized or observational, may be insufficient. Principled integration of randomized controlled trials and real-world data, grounded in explicit causal frameworks, offers a path toward evidence that is both internally credible and externally relevant. In this article, we describe distinct objectives for the integration of randomized controlled trials and real-world data and discuss how these objectives shape key design and analytic considerations, illustrating the resulting choices through example estimands. We highlight practical issues that commonly arise in applied settings, including data relevance and curation, cross-source comparability, estimand specification, and sensitivity analysis. We aim for this article to help readers evaluate and implement principled approaches to integrating randomized controlled trials and real-world data in ways that can support more reliable treatment recommendations while maintaining regulatory-grade evidentiary standards.
Cite
@article{arxiv.2604.10308,
title = {Considerations for the Integration of Randomized Controlled Trials and Real-World Data},
author = {Sky Qiu and Charles Barr and Lauren Dang and Issa Dahabreh and Larry Han and Kajsa Kvist and Hana Lee and Andrew Mertens and Nerissa Nance and Lei Nie and Kara Rudolph and Xu Shi and Jens Tarp and Salina P. Waddy and Kenneth Wiley and Andy Wilson and Margot Lisa Jing Yann and Zhiwei Zhang and Tianyue Zhou and Maya Petersen and Mark van der Laan},
journal= {arXiv preprint arXiv:2604.10308},
year = {2026}
}