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Simulation-based Evaluation of the Generalizability Index for Study Traits
Zhe He1, Praveen Chandar1, Patrick Ryan2
1Department of Biomedical Informatics, Columbia University, New York, NY USA.
Abstract:
The Generalizability Index for Study Traits (GIST) has been proposed recently for assessing the population representativeness of a set of related clinical trials using eligibility features (e.g., age or BMI), one each time. However, GIST has not yet been evaluated. To bridge this knowledge gap, this paper reports a simulation-based validation study for GIST. Using the National Health and Nutrition Examination Survey (NHANES) data, we demonstrated the effectiveness of GIST at quantifying the population representativeness of a set of related trials that differ in disease domains, study phases, sponsor types, and study designs, respectively. We also showed that among seven example medical conditions, the GIST of age increases from Phase I trials to Phase III trials in the seven disease domains and is the lowest in asthma trials. We concluded that GIST correlates with simulation-based generalizability results and is a valid metric for quantifying population representativeness of related clinical trials.
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