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      The Burden of Proof studies: assessing the evidence of risk

      research-article
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      Nature Medicine
      Nature Publishing Group US
      Diseases, Risk factors

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          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.

          Abstract

          A new Burden of Proof meta-analytic method that accounts for between-study heterogeneity and corrects for bias between different study designs is used to interpret the strength of evidence between different pairs of risk factors and health outcomes.

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          Bias in meta-analysis detected by a simple, graphical test

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            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              Regression Shrinkage and Selection Via the Lasso

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                Author and article information

                Contributors
                cjlm@uw.edu
                Journal
                Nat Med
                Nat Med
                Nature Medicine
                Nature Publishing Group US (New York )
                1078-8956
                1546-170X
                10 October 2022
                10 October 2022
                2022
                : 28
                : 10
                : 2038-2044
                Affiliations
                [1 ]GRID grid.34477.33, ISNI 0000000122986657, Institute for Health Metrics and Evaluation, , University of Washington, ; Seattle, WA USA
                [2 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Health Metrics Sciences, School of Medicine, , University of Washington, ; Seattle, WA USA
                [3 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, School of Population and Public Health, , University of British Columbia, ; Vancouver, British Columbia Canada
                [4 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, School of Public Health, , The University of Queensland, ; Brisbane, Queensland Australia
                [5 ]GRID grid.466965.e, ISNI 0000 0004 0624 0996, Queensland Centre for Mental Health Research, ; Wacol, Queensland Australia
                [6 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Anesthesiology & Pain Medicine, , University of Washington, ; Seattle, WA USA
                [7 ]GRID grid.34477.33, ISNI 0000000122986657, Division of Cardiology, , University of Washington, ; Seattle, WA USA
                [8 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, The George Institute for Global Health, , The University of New South Wales, ; Sydney, New South Wales Australia
                [9 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Applied Mathematics, , University of Washington, ; Seattle, WA USA
                Author information
                http://orcid.org/0000-0002-9103-9343
                http://orcid.org/0000-0002-0289-7814
                http://orcid.org/0000-0002-8992-591X
                http://orcid.org/0000-0002-0611-7272
                http://orcid.org/0000-0002-4299-9348
                http://orcid.org/0000-0003-2690-3198
                http://orcid.org/0000-0003-2145-6528
                http://orcid.org/0000-0002-0098-9563
                http://orcid.org/0000-0003-2209-8478
                http://orcid.org/0000-0002-4310-1632
                http://orcid.org/0000-0002-4930-9450
                Article
                1973
                10.1038/s41591-022-01973-2
                9556298
                36216935
                f736a7d3-e15b-4e58-8f0b-7102de001117
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 October 2021
                : 28 July 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000865, Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation);
                Award ID: OPP1152504
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100007500, Bloomberg Family Foundation (Bloomber Philanthropies);
                Funded by: FundRef https://doi.org/10.13039/501100001782, University of Melbourne (Melbourne University);
                Funded by: FundRef https://doi.org/10.13039/100010230, Department of Health, Queensland (Queensland Health);
                Funded by: FundRef https://doi.org/10.13039/501100000925, Department of Health | National Health and Medical Research Council (NHMRC);
                Funded by: FundRef https://doi.org/10.13039/501100002141, Public Health England (PHE);
                Funded by: FundRef https://doi.org/10.13039/100007737, St. Jude Children’s Research Hospital;
                Funded by: FundRef https://doi.org/10.13039/100000025, U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH);
                Award ID: R01MH110163
                Award Recipient :
                Funded by: the Norwegian Institute of Public Health; the Cardiovascular Medical Research and Education Fund; the National Institute on Ageing of the NIH (award P30AG047845)
                Funded by: The funders for this study are listed in full under Christopher JL Murray
                Categories
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                © The Author(s), under exclusive licence to Springer Nature America, Inc. 2022

                Medicine
                diseases,risk factors
                Medicine
                diseases, risk factors

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