Considerations for the Integration of Randomized Controlled Trials and Real-World Data

Fuente: arXiv
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Main Authors: Qiu, Sky, Barr, Charles, Dang, Lauren, Dahabreh, Issa, Han, Larry, Kvist, Kajsa, Lee, Hana, Mertens, Andrew, Nance, Nerissa, Nie, Lei, Rudolph, Kara, Shi, Xu, Tarp, Jens, Waddy, Salina P., Wiley, Kenneth, Wilson, Andy, Yann, Margot Lisa Jing, Zhang, Zhiwei, Zhou, Tianyue, Petersen, Maya, van der Laan, Mark
Format: Preprint
Published: 2026
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author Qiu, Sky
Barr, Charles
Dang, Lauren
Dahabreh, Issa
Han, Larry
Kvist, Kajsa
Lee, Hana
Mertens, Andrew
Nance, Nerissa
Nie, Lei
Rudolph, Kara
Shi, Xu
Tarp, Jens
Waddy, Salina P.
Wiley, Kenneth
Wilson, Andy
Yann, Margot Lisa Jing
Zhang, Zhiwei
Zhou, Tianyue
Petersen, Maya
van der Laan, Mark
author_facet Qiu, Sky
Barr, Charles
Dang, Lauren
Dahabreh, Issa
Han, Larry
Kvist, Kajsa
Lee, Hana
Mertens, Andrew
Nance, Nerissa
Nie, Lei
Rudolph, Kara
Shi, Xu
Tarp, Jens
Waddy, Salina P.
Wiley, Kenneth
Wilson, Andy
Yann, Margot Lisa Jing
Zhang, Zhiwei
Zhou, Tianyue
Petersen, Maya
van der Laan, Mark
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2604_10308
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Considerations for the Integration of Randomized Controlled Trials and Real-World Data
Qiu, Sky
Barr, Charles
Dang, Lauren
Dahabreh, Issa
Han, Larry
Kvist, Kajsa
Lee, Hana
Mertens, Andrew
Nance, Nerissa
Nie, Lei
Rudolph, Kara
Shi, Xu
Tarp, Jens
Waddy, Salina P.
Wiley, Kenneth
Wilson, Andy
Yann, Margot Lisa Jing
Zhang, Zhiwei
Zhou, Tianyue
Petersen, Maya
van der Laan, Mark
Methodology
Applications
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.
title Considerations for the Integration of Randomized Controlled Trials and Real-World Data
topic Methodology
Applications
url https://arxiv.org/abs/2604.10308