ArticleAnnals of the New York Academy of Sciences2017
Correlating eligibility criteria generalizability and adverse events using Big Data for patients and clinical trials.
Article in Annals of the New York Academy of Sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 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
- How Many Anxious Kids in Community Mental Health Would Be Eligible for an RCT? And Does It Matter? Insights from a Naturalistic Sample and a Non-Systematic Review.Children (Basel, Switzerland) · 2026Article
- Article
- Selection and Prejudice: Addressing Clinical Trial Disparities With a Review of Current Shortcomings and Future Directions.Seminars in radiation oncology · 2023Review
- From clinical trials to clinical practice: How long are drugs tested and then used by patients?Journal of the American Medical Informatics Association : JAMIA · 2021Article
- A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data.Applied clinical informatics · 2021Article
- Applying advanced technologies to improve clinical trials: a systematic mapping study.Scientometrics · 2021Article
- Chia, a large annotated corpus of clinical trial eligibility criteria.Scientific data · 2020Article
- [Analysis of clinical efficacy, safety and prognosis of anlotinib hydrochloride in the treatment of advanced primary liver cancer].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2020Article
- 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 Validity of aAMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Article
- 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
7 authors.
Funding
Abstract
Randomized controlled trials can benefit from proactive assessment of how well their participant selection strategies during the design of eligibility criteria can influence the study generalizability. In this paper, we present a quantitative metric called generalizability index for study traits 2.0 (GIST 2.0) to assess the a priori generalizability (based on population representativeness) of a clinical trial by accounting for the dependencies among multiple eligibility criteria. The metric was evaluated on 16 sepsis trials identified from ClinicalTrials.gov, with their adverse event reports extracted from the trial results sections. The correlation between GIST scores and adverse events was analyzed. We found that the GIST 2.0 score was significantly correlated with total adverse events and serious adverse events (weighted correlation coefficients of 0.825 and 0.709, respectively, with P < 0.01). This study exemplifies the promising use of Big Data in electronic health records and ClinicalTrials.gov for optimizing eligibility criteria design for clinical studies.
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