학술논문
The Burden of Proof studies: assessing the evidence of risk.
Document Type
Academic Journal
Author
Zheng P; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Afshin A; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Biryukov S; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Bisignano C; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Brauer M; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.; Bryazka D; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Burkart K; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Cercy KM; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Cornaby L; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Dai X; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Dirac MA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Estep K; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Fay KA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Feldman R; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Ferrari AJ; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; School of Public Health, The University of Queensland, Brisbane, Queensland, Australia.; Queensland Centre for Mental Health Research, Wacol, Queensland, Australia.; Gakidou E; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Gil GF; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Griswold M; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Hay SI; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; He J; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Irvine CMS; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Kassebaum NJ; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA.; LeGrand KE; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Lescinsky H; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Lim SS; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Lo J; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Mullany EC; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Ong KL; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Rao PC; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Razo C; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Reitsma MB; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Roth GA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Division of Cardiology, University of Washington, Seattle, WA, USA.; Santomauro DF; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; School of Public Health, The University of Queensland, Brisbane, Queensland, Australia.; Queensland Centre for Mental Health Research, Wacol, Queensland, Australia.; Sorensen RJD; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Srinivasan V; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Stanaway JD; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Vollset SE; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Vos T; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Wang N; The George Institute for Global Health, The University of New South Wales, Sydney, New South Wales, Australia.; Welgan CA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Wozniak SS; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Aravkin AY; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Department of Applied Mathematics, University of Washington, Seattle, WA, USA.; Murray CJL; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. cjlm@uw.edu.; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA. cjlm@uw.edu.
Source
Publisher: Nature Publishing Company Country of Publication: United States NLM ID: 9502015 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1546-170X (Electronic) Linking ISSN: 10788956 NLM ISO Abbreviation: Nat Med Subsets: MEDLINE
Subject
Language
English
Abstract
Exposure to risks throughout life results in a wide variety of outcomes. Objectively judging the relative impact of these risks on personal and population health is fundamental to individual survival and societal prosperity. Existing mechanisms to quantify and rank the magnitude of these myriad effects and the uncertainty in their estimation are largely subjective, leaving room for interpretation that can fuel academic controversy and add to confusion when communicating risk. We present a new suite of meta-analyses-termed the Burden of Proof studies-designed specifically to help evaluate these methodological issues objectively and quantitatively. Through this data-driven approach that complements existing systems, including GRADE and Cochrane Reviews, we aim to aggregate evidence across multiple studies and enable a quantitative comparison of risk-outcome pairs. We introduce the burden of proof risk function (BPRF), which estimates the level of risk closest to the null hypothesis that is consistent with available data. Here we illustrate the BPRF methodology for the evaluation of four exemplar risk-outcome pairs: smoking and lung cancer, systolic blood pressure and ischemic heart disease, vegetable consumption and ischemic heart disease, and unprocessed red meat consumption and ischemic heart disease. The strength of evidence for each relationship is assessed by computing and summarizing the BPRF, and then translating the summary to a simple star rating. The Burden of Proof methodology provides a consistent way to understand, evaluate and summarize evidence of risk across different risk-outcome pairs, and informs risk analysis conducted as part of the Global Burden of Diseases, Injuries, and Risk Factors Study.
(© 2022. The Author(s).)
(© 2022. The Author(s).)