title: Simulation-based Evaluation of the Generalizability Index for Study Traits.
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.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY USA.
authors.forename: Zhe
authors.initials: Z
authors.lastname: He
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY USA.
authors.forename: Praveen
authors.initials: P
authors.lastname: Chandar
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY USA; Janssen Research and Development, Titusville, NJ USA.
authors.forename: Patrick
authors.initials: P
authors.lastname: Ryan
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY USA.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Weng
mesh_terms: D004608:Eligibility Determination; D006801:Humans; D009749:Nutrition Surveys; D018579:Patient Selection; D016032:Randomized Controlled Trials as Topic; D057170:Translational Research, Biomedical