ArticleJournal of biomedical informatics2016
GIST 2.0: A scalable multi-trait metric for quantifying population representativeness of individual clinical studies.
Article in Journal of biomedical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical Trial Generalizability Assessment in the Big Data Era: A Review.Clinical and translational science · 2020Pooled it
- Data-driven trial design: use of target trial emulation to evaluate eligibility criteria in asthma and COPD.Frontiers in medicine · 2026Article
- CLEAR: A vision to support clinical evidence lifecycle with continuous learning.Journal of biomedical informatics · 2025Article
- Computational strategic recruitment for representation and coverage studied in the All of Us Research Program.NPJ digital medicine · 2025Article
- Computational Phenomapping of Randomized Clinical Trial Participants to Enable Assessment of Their Real-World Representativeness and Personalized Inference.Circulation. Cardiovascular quality and outcomes · 2025Article
- POP-REFINE: A Comprehensive Framework for Evaluating and Optimizing Representativeness in Clinical Trials.Clinical pharmacology and therapeutics · 2025Article
- A Standardized Guideline for Assessing Extracted Electronic Health Records Cohorts: A Scoping Review.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- Eligibility of Asian and European registry patients for phase III trials in heart failure with reduced ejection fraction.ESC heart failure · 2024Article
- A review of research on eligibility criteria for clinical trials.Clinical and experimental medicine · 2023Review
- Applicability of Transcatheter Aortic Valve Replacement Trials to Real-World Clinical Practice: Findings From EXTEND-CoreValve.JACC. Cardiovascular interventions · 2021Article
- The Problem of Fairness in Synthetic Healthcare Data.Entropy (Basel, Switzerland) · 2021Article
- A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data.Applied clinical informatics · 2021Article
- Clinical comparison between trial participants and potentially eligible patients using electronic health record data: A generalizability assessment method.Journal of biomedical informatics · 2021Article
- Quantifying representativeness in randomized clinical trials using machine learning fairness metrics.JAMIA open · 2021Article
- A knowledge base of clinical trial eligibility criteria.Journal of biomedical informatics · 2021Article
- Using Real-World Data to Rationalize Clinical Trials Eligibility Criteria Design: A Case Study of Alzheimer's Disease Trials.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- Assessing the Use and Perception of Dietary Supplements Among Obese Patients with National Health and Nutrition Examination Survey.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020Article
- Assessing the Validity of aAMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Article
- Desiderata for sharable computable biomedical knowledge for learning health systems.Learning health systems · 2018Article
- The representativeness of eligible patients in type 2 diabetes trials: a case study using GIST 2.0.Journal of the American Medical Informatics Association : JAMIA · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The design of randomized controlled clinical studies can greatly benefit from iterative assessments of population representativeness of eligibility criteria. We propose a multi-trait metric - GIST 2.0 that can compute the a priori generalizability based on the population representativeness of a clinical study by explicitly modeling the dependencies among all eligibility criteria. We evaluate this metric on twenty clinical studies of two diseases and analyze how a study's eligibility criteria affect its generalizability (collectively and individually). We statistically analyze the effects of trial setting, trait selection and trait summarizing technique on GIST 2.0. Finally we provide theoretical as well as empirical validations for the expected properties of GIST 2.0.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.