Mitchell M Conover, Patrick B Ryan, Yong Chen, Marc A Suchard, George Hripcsak, Martijn J Schuemie
{"title":"客观研究有效性诊断:一个框架,需要预先指定,经验验证,以增加对真实世界证据可靠性的信任。","authors":"Mitchell M Conover, Patrick B Ryan, Yong Chen, Marc A Suchard, George Hripcsak, Martijn J Schuemie","doi":"10.1093/jamia/ocae317","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Propose a framework to empirically evaluate and report validity of findings from observational studies using pre-specified objective diagnostics, increasing trust in real-world evidence (RWE).</p><p><strong>Materials and methods: </strong>The framework employs objective diagnostic measures to assess the appropriateness of study designs, analytic assumptions, and threats to validity in generating reliable evidence addressing causal questions. Diagnostic evaluations should be interpreted before the unblinding of study results or, alternatively, only unblind results from analyses that pass pre-specified thresholds. We provide a conceptual overview of objective diagnostic measures and demonstrate their impact on the validity of RWE from a large-scale comparative new-user study of various antihypertensive medications. We evaluated expected absolute systematic error (EASE) before and after applying diagnostic thresholds, using a large set of negative control outcomes.</p><p><strong>Results: </strong>Applying objective diagnostics reduces bias and improves evidence reliability in observational studies. Among 11 716 analyses (EASE = 0.38), 13.9% met pre-specified diagnostic thresholds which reduced EASE to zero. Objective diagnostics provide a comprehensive and empirical set of tests that increase confidence when passed and raise doubts when failed.</p><p><strong>Discussion: </strong>The increasing use of real-world data presents a scientific opportunity; however, the complexity of the evidence generation process poses challenges for understanding study validity and trusting RWE. Deploying objective diagnostics is crucial to reducing bias and improving reliability in RWE generation. Under ideal conditions, multiple study designs pass diagnostics and generate consistent results, deepening understanding of causal relationships. Open-source, standardized programs can facilitate implementation of diagnostic analyses.</p><p><strong>Conclusion: </strong>Objective diagnostics are a valuable addition to the RWE generation process.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Objective study validity diagnostics: a framework requiring pre-specified, empirical verification to increase trust in the reliability of real-world evidence.\",\"authors\":\"Mitchell M Conover, Patrick B Ryan, Yong Chen, Marc A Suchard, George Hripcsak, Martijn J Schuemie\",\"doi\":\"10.1093/jamia/ocae317\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Propose a framework to empirically evaluate and report validity of findings from observational studies using pre-specified objective diagnostics, increasing trust in real-world evidence (RWE).</p><p><strong>Materials and methods: </strong>The framework employs objective diagnostic measures to assess the appropriateness of study designs, analytic assumptions, and threats to validity in generating reliable evidence addressing causal questions. Diagnostic evaluations should be interpreted before the unblinding of study results or, alternatively, only unblind results from analyses that pass pre-specified thresholds. We provide a conceptual overview of objective diagnostic measures and demonstrate their impact on the validity of RWE from a large-scale comparative new-user study of various antihypertensive medications. We evaluated expected absolute systematic error (EASE) before and after applying diagnostic thresholds, using a large set of negative control outcomes.</p><p><strong>Results: </strong>Applying objective diagnostics reduces bias and improves evidence reliability in observational studies. Among 11 716 analyses (EASE = 0.38), 13.9% met pre-specified diagnostic thresholds which reduced EASE to zero. Objective diagnostics provide a comprehensive and empirical set of tests that increase confidence when passed and raise doubts when failed.</p><p><strong>Discussion: </strong>The increasing use of real-world data presents a scientific opportunity; however, the complexity of the evidence generation process poses challenges for understanding study validity and trusting RWE. Deploying objective diagnostics is crucial to reducing bias and improving reliability in RWE generation. Under ideal conditions, multiple study designs pass diagnostics and generate consistent results, deepening understanding of causal relationships. Open-source, standardized programs can facilitate implementation of diagnostic analyses.</p><p><strong>Conclusion: </strong>Objective diagnostics are a valuable addition to the RWE generation process.</p>\",\"PeriodicalId\":50016,\"journal\":{\"name\":\"Journal of the American Medical Informatics Association\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Medical Informatics Association\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1093/jamia/ocae317\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Medical Informatics Association","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1093/jamia/ocae317","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Objective study validity diagnostics: a framework requiring pre-specified, empirical verification to increase trust in the reliability of real-world evidence.
Objective: Propose a framework to empirically evaluate and report validity of findings from observational studies using pre-specified objective diagnostics, increasing trust in real-world evidence (RWE).
Materials and methods: The framework employs objective diagnostic measures to assess the appropriateness of study designs, analytic assumptions, and threats to validity in generating reliable evidence addressing causal questions. Diagnostic evaluations should be interpreted before the unblinding of study results or, alternatively, only unblind results from analyses that pass pre-specified thresholds. We provide a conceptual overview of objective diagnostic measures and demonstrate their impact on the validity of RWE from a large-scale comparative new-user study of various antihypertensive medications. We evaluated expected absolute systematic error (EASE) before and after applying diagnostic thresholds, using a large set of negative control outcomes.
Results: Applying objective diagnostics reduces bias and improves evidence reliability in observational studies. Among 11 716 analyses (EASE = 0.38), 13.9% met pre-specified diagnostic thresholds which reduced EASE to zero. Objective diagnostics provide a comprehensive and empirical set of tests that increase confidence when passed and raise doubts when failed.
Discussion: The increasing use of real-world data presents a scientific opportunity; however, the complexity of the evidence generation process poses challenges for understanding study validity and trusting RWE. Deploying objective diagnostics is crucial to reducing bias and improving reliability in RWE generation. Under ideal conditions, multiple study designs pass diagnostics and generate consistent results, deepening understanding of causal relationships. Open-source, standardized programs can facilitate implementation of diagnostic analyses.
Conclusion: Objective diagnostics are a valuable addition to the RWE generation process.
期刊介绍:
JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.