Considerations for the Integration of Randomized Controlled Trials and Real-World Data
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866915933227843584 |
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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 |