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• W3006162251 abstract "Abstract Clinical studies, especially randomized, controlled trials, are essential for generating evidence for clinical practice. However, generalizability is a long‐standing concern when applying trial results to real‐world patients. Generalizability assessment is thus important, nevertheless, not consistently practiced. We performed a systematic review to understand the practice of generalizability assessment. We identified 187 relevant articles and systematically organized these studies in a taxonomy with three dimensions: (i) data availability (i.e., before or after trial ( a priori vs. a posteriori generalizability)); (ii) result outputs (i.e., score vs. nonscore); and (iii) populations of interest. We further reported disease areas, underrepresented subgroups, and types of data used to profile target populations. We observed an increasing trend of generalizability assessments, but < 30% of studies reported positive generalizability results. As a priori generalizability can be assessed using only study design information (primarily eligibility criteria), it gives investigators a golden opportunity to adjust the study design before the trial starts. Nevertheless, < 40% of the studies in our review assessed a priori generalizability. With the wide adoption of electronic health records systems, rich real‐world patient databases are increasingly available for generalizability assessment; however, informatics tools are lacking to support the adoption of generalizability assessment practice." @default.
• W3006162251 created "2020-02-24" @default.
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• W3006162251 date "2020-04-10" @default.
• W3006162251 modified "2023-10-14" @default.
• W3006162251 title "Clinical Trial Generalizability Assessment in the Big Data Era: A Review" @default.
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• W3006162251 doi "https://doi.org/10.1111/cts.12764" @default.
• W3006162251 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7359942" @default.
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