{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T06:55:03Z","timestamp":1791269703705,"version":"4.1.0"},"reference-count":64,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T00:00:00Z","timestamp":1791158400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T00:00:00Z","timestamp":1791158400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clin Pharma and Therapeutics"],"abstract":"<jats:p>As clinical decision\u2010making increasingly moves toward individualized and context\u2010specific treatment recommendations, reliance on any single evidence source, randomized or observational, may be insufficient. Principled integration of randomized controlled trials and real\u2010world 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\u2010world 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\u2010source 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\u2010world data in ways that can support more reliable treatment recommendations while maintaining regulatory\u2010grade evidentiary standards.<\/jats:p>","DOI":"10.1002\/cpt.70513","type":"journal-article","created":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T06:45:47Z","timestamp":1791269147000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Considerations for the Integration of Clinical Trials and Real\u2010World Data"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-5944-0782","authenticated-orcid":false,"given":"Sky","family":"Qiu","sequence":"first","affiliation":[{"name":"Division of Biostatistics, School of Public Health University of California  Berkeley California USA"},{"name":"Center for Targeted Machine Learning and Causal Inference, School of Public Health University of California  Berkeley California USA"},{"name":"Targeted ML Solutions, Inc.  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