An Overview of Current Methods for Real-world Applications to Generalize or Transport Clinical Trial Findings to Target Populations of Interest

Author:

Ling Albee Y.1ORCID,Montez-Rath Maria E.2ORCID,Carita Paulo3,Chandross Karen J.4,Lucats Laurence3,Meng Zhaoling5,Sebastien Bernard3,Kapphahn Kris1,Desai Manisha1ORCID

Affiliation:

1. Quantitative Sciences Unit, Division of Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA

2. Division of Nephrology, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA

3. Sanofi R&D Region, France

4. Sanofi R&D Bridgewater, NJ

5. Sanofi R&D Cambridge, MA.

Abstract

It has been well established that randomized clinical trials have poor external validity, resulting in findings that may not apply to relevant—or target—populations. When the trial is sampled from the target population, generalizability methods have been proposed to address the applicability of trial findings to target populations. When the trial sample and target populations are distinct, transportability methods may be applied for this purpose. However, generalizability and transportability studies present challenges, particularly around the strength of their conclusions. We review and summarize state-of-the-art methods for translating trial findings to target populations. We additionally provide a novel step-by-step guide to address these challenges, illustrating principles through a published case study. When conducted with rigor, generalizability and transportability studies can play an integral role in regulatory decisions by providing key real-world evidence.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Epidemiology

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