The Burden of Proof studies: assessing the evidence of risk
Open accessAbstract
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.
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The validity of the BPRF approach has been extensively and rigorously evaluated by Zheng and colleagues.
“The validity of the BPRF approach to meta-analyze data extracted across studies has been extensively and rigorously evaluated by Zheng and colleagues430.”
From Health effects associated with exposure to secondhand smoke: a Burden of Proof study (2024) · cites this paper as [430]
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Cites
Global mortality, disability, and the contribution of risk factors: Global Burden of Disease Study
Murray, C. J., & Lopez, A. D. (1997) · The Lancet · doi:10.1016/s0140-6736(96)07495-8 · Cited by 4,492 · see citing works
Self-citationGRADE guidelines: 4. Rating the quality of evidence—study limitations (risk of bias)
Guyatt, G. H., Oxman, A. D., Vist, G., Kunz, R., Brozek, J., Alonso-Coello, P., Montori, V., Akl, E. A., Djulbegovic, B., & Falck-Ytter, Y. (2011) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2010.07.017 · Cited by 2,798 · see citing works
One-stage dose–response meta-analysis for aggregated data
Crippa, A., Discacciati, A., Bottai, M., Spiegelman, D., & Orsini, N. (2019) · Statistical Methods in Medical Research · doi:10.1177/0962280218773122 · Cited by 365 · see citing works
Why animal studies are often poor predictors of human reactions to exposure
Bracken, M. B. (2009) · Journal of the Royal Society of Medicine · doi:10.1258/jrsm.2008.08k033 · Cited by 362 · see citing works
Flagged first, then by citations
Research works printed but not linked: 37
- [1]Murray CJL Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 Lancet 2020 396 1223 1249 10.1016/S0140-6736(20)30752-2 33069327 PMC7566194 · DOI · Paper page
- [3]Murray CJ Ezzati M Lopez AD Rodgers A Vander Hoorn S Comparative quantification of health risks: conceptual framework and methodological issues Popul. Health Metr. 2003 1 1 10.1186/1478-7954-1-1 12780936 PMC156894 · DOI · Paper page
- [4]Stanley K Evaluation of randomized controlled trials Circulation 2007 115 1819 1822 10.1161/CIRCULATIONAHA.106.618603 17404173 · DOI
- [5]Deaton A Cartwright N Understanding and misunderstanding randomized controlled trials Soc. Sci. Med. 2018 210 2 21 10.1016/j.socscimed.2017.12.005 29331519 PMC6019115 · DOI · Paper page
- [6]Tenny, S., Kerndt, C. C. & Hoffman, M. R. Case control studies. StatPearls https://www.statpearls.com/ArticleLibrary/viewarticle/18989 (2021). 28846237
- [7]Chouinard E Walter S Recall bias in case-control studies: an empirical analysis and theoretical framework J. Clin. Epidemiol. 1995 48 245 254 10.1016/0895-4356(94)00132-A 7869070 · DOI
- [10]Viechtbauer W Conducting meta-analyses in R with the metafor package J. Stat. Softw. 2010 36 1 48 10.18637/jss.v036.i03 · DOI · Paper page
- [11]Orsini N Li R Wolk A Khudyakov P Spiegelman D Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software Am. J. Epidemiol. 2012 175 66 73 10.1093/aje/kwr265 22135359 PMC3244608 · DOI
- [12]Micha R Wallace SK Mozaffarian D Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis Circulation 2010 121 2271 2283 10.1161/CIRCULATIONAHA.109.924977 20479151 PMC2885952 · DOI · Paper page
- [13]Ioannidis JPA Patsopoulos NA Evangelou E Uncertainty in heterogeneity estimates in meta-analyses Brit. Med. J. 2007 335 914 916 10.1136/bmj.39343.408449.80 17974687 PMC2048840 · DOI · Paper page
- [14]Moolgavkar SH Chang ET Watson HN Lau EC An assessment of the Cox proportional hazards regression model for epidemiologic studies Risk Anal. 2018 38 777 794 10.1111/risa.12865 29168991 · DOI
- [15]Flegal KM Kit BK Orpana H Graubard BI Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis JAMA 2013 309 71 82 10.1001/jama.2012.113905 23280227 PMC4855514 · DOI · Paper page
- [16]Ioannidis JP The challenge of reforming nutritional epidemiologic research JAMA 2018 320 969 970 10.1001/jama.2018.11025 30422271 · DOI
- [17]Pope CA III Coleman N Pond ZA Burnett RT Fine particulate air pollution and human mortality: 25+ years of cohort studies Environ. Res. 2020 183 108924 10.1016/j.envres.2019.108924 31831155 · DOI
- [18]Johnston BC Unprocessed red meat and processed meat consumption: dietary guideline recommendations from the Nutritional Recommendations (NutriRECS) Consortium Ann. Intern. Med. 2019 171 756 764 10.7326/M19-1621 31569235 · DOI
- [19]Higgins, J. P. et al. Cochrane Handbook for Systematic Reviews of Interventions (Wiley, 2019).
- [20]Siemieniuk, R. & Guyatt, G. What is GRADE? BMJ Best Practice https://bestpractice.bmj.com/info/us/toolkit/learn-ebm/what-is-grade/ (2021).
- [22]Liu Q Cook NR Bergström A Hsieh C-C A two-stage hierarchical regression model for meta-analysis of epidemiologic nonlinear dose–response data Comput. Stat. Data Anal. 2009 53 4157 4167 10.1016/j.csda.2009.05.001 · DOI
- [24]Crippa A Orsini N Multivariate dose-response meta-analysis: the dosresmeta R package J. Stat. Softw. 2016 72 1 15 10.18637/jss.v072.c01 · DOI
- [25]Dai X Health effects associated with smoking: a Burden of Proof study Nat. Med. 2022 10.1038/s41591-022-01978-x 36216941 PMC9556318 · DOI
- [26]Razo C Effects of elevated systolic blood pressure on ischemic heart disease: a Burden of Proof study Nat. Med. 2022 10.1038/s41591-022-01974-1 36216934 PMC9556328 · DOI
- [27]Stanaway JD Health effects associated with vegetable consumption: a Burden of Proof study Nat. Med. 2022 10.1038/s41591-022-01970-5 36216936 PMC9556321 · DOI
- [28]Lescinsky H Health effects associated with unprocessed red meat: a Burden of Proof study Nat. Med. 2022 10.1038/s41591-022-01968-z 36216940 PMC9556326 · DOI
- [32]Stevens, G. A. et al. Guidelines for accurate and transparent health estimates reporting: the GATHER statement. Lancet388, e19–e23 (2016). 27371184
- [33]de Boor, C. A Practical Guide to Splines (Springer, 2001).
- [34]Rousseeuw, P. J. & Leroy, A. M. Robust Regression and Outlier Detection Vol. 589 (Wiley, 2005).
- [35]Rousseeuw PJ Least median of squares regression J. Am. Stat. Assoc. 1984 79 871 880 10.1080/01621459.1984.10477105 · DOI
- [36]Huber, P. J. Robust Statistics (Wiley, 2004).
- [37]Rousseeuw, P. Multivariate estimation with high breakdown point. In Mathematical Statistics and Applications: Proc. 4th Pannonian Symposium on Mathematical Statistics Vol. B (eds Grossman, W. et al.) 283–297 (Reidel Publishing Company, 1985).
- [38]Aravkin A Davis D Trimmed statistical estimation via variance reduction Math. Oper. Res. 2020 45 292 322 10.1287/moor.2019.0992 · DOI
- [39]Motzkin, T. S., Raiffa, H., Thompson, G. L. & Thrall, R. M. in Contributions to the Theory of Games (AM-28) Vol. 2 (eds Kuhn, H. W. & Tucker, A. W.) Ch. 3 (Princeton Univ. Press, 2016).
- [41]Efron B Hastie T Johnstone I Tibshirani R Least angle regression Ann. Stat. 2004 32 407 499 10.1214/009053604000000067 · DOI · Paper page
- [43]Kontopantelis E Springate DA Reeves D A re-analysis of the Cochrane Library data: the dangers of unobserved heterogeneity in meta-analyses PLoS ONE 2013 8 e69930 10.1371/journal.pone.0069930 23922860 PMC3724681 · DOI
- [44]Biggerstaff BJ Tweedie RL Incorporating variability in estimates of heterogeneity in the random effects model in meta-analysis Stat. Med. 1997 16 753 768 10.1002/(SICI)1097-0258(19970415)16:7<753::AID-SIM494>3.0.CO;2-G 9131763 · DOI
- [45]Higgins JP Thompson SG Quantifying heterogeneity in a meta-analysis Stat. Med. 2002 21 1539 1558 10.1002/sim.1186 12111919 · DOI · Paper page
- [46]Sterne, J. A. & Egger, M. in Publication Bias in Meta-analysis: Prevention, Assessment and Adjustments (eds Rothstein, H. et al.) Ch. 6 (Wiley, 2005).
- [47]Egger M Smith GD Schneider M Minder C Bias in meta-analysis detected by a simple, graphical test Brit. Med. J. 1997 315 629 634 10.1136/bmj.315.7109.629 9310563 PMC2127453 · DOI · Paper page
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Self-citationBrauer, M., Roth, G. A., Aravkin, A. Y., Zheng, P., Abate, K. H., Abate, Y. H., Abbafati, C., Abbasgholizadeh, R., Abbasi, M. A., Abbasian, M., et al. (2024) · The Lancet · doi:10.1016/s0140-6736(24)00933-4 · Cited by 2,884 · see citing works
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Self-citationHealth effects associated with exposure to secondhand smoke: a Burden of Proof study
Flor, L. S., Anderson, J. A., Ahmad, N., Aravkin, A., Carr, S., Dai, X., Gil, G. F., Hay, S. I., Malloy, M. J., McLaughlin, S. A., et al. (2024) · Nature Medicine · doi:10.1038/s41591-023-02743-4 · Cited by 167 · see citing works
“…our study, which examines the relationship between SHS exposure and nine health outcomes using the BPRF framework developed by Zheng and colleagues 430 , reaffirms that SHS should be an area of priority for policymakers, physicians and public health advocates for strengthening tobacco-control…”
MethodSelf-citation
- Authors
- Zheng, P., Afshin, A., Biryukov, S., Bisignano, C., Brauer, M., Bryazka, D., Burkart, K., Cercy, K. M., Cornaby, L., Dai, X., Dirac, M. A., Estep, K., Fay, K. A., Feldman, R., Ferrari, A. J., Gakidou, E., Gil, G. F., Griswold, M., Hay, S. I., He, J., Irvine, C. M. S., Kassebaum, N. J., LeGrand, K. E., Lescinsky, H., Lim, S. S., Lo, J., Mullany, E. C., Ong, K. L., Rao, P. C., Razo, C., Reitsma, M. B., Roth, G. A., Santomauro, D. F., Sorensen, R. J. D., Srinivasan, V., Stanaway, J. D., Vollset, S. E., Vos, T., Wang, N., Welgan, C. A., Wozniak, S. S., Aravkin, A. Y., & Murray, C. J. L.
- Affiliations
- University of Washington (US)
- University of British Columbia (CA)
- The University of Queensland (AU)
- UNSW Sydney (AU)
- Corresponding author
- Murray, Christopher J. L.
- ORCID
- Afshin, Ashkan
- Brauer, Michael
- Bryazka, Dana
- Burkart, Katrin
- Dai, Xiaochen
- Fay, Kairsten A.
- Feldman, Rachel
- Ferrari, Alize J.
- Gakidou, Emmanuela
- Gil, Gabriela Fernanda
- Griswold, Max
- Hay, Simon I.
- He, Jiawei
- Irvine, Caleb M. S.
- Kassebaum, Nicholas J.
- LeGrand, Kate E.
- Lim, Stephen S.
- Lo, Justin
- Ong, Kanyin Liane
- Razo, Christian
- Reitsma, Marissa B.
- Roth, Gregory A.
- Santomauro, Damian F.
- Sorensen, Reed J. D.
- Srinivasan, Vinay
- Stanaway, Jeffrey D.
- Vos, Theo
- Wang, Nelson
- Welgan, Catherine A.
- Aravkin, Aleksandr Y.
- Murray, Christopher J. L.
- Venue
- Nature Medicine
- Published
- 2022-10
- Volume
- 28
- Issue
- 10
- Pages
- 2038-2044
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- PMC
- PMC9556298
- OpenAlex
- W4304084045
- Cited by
- 142
- References
- 4
- Citations by year
- 2026: 32 · 2025: 42 · 2024: 29 · 2023: 25 · 2022: 14
- FWCI
- 16.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Bill and Melinda Gates Foundation (OPP1152504)
- Bloomberg Family Foundation
- University of Melbourne
- Department of Health, Queensland
- Department of Health | National Health and Medical Research Council
- Public Health England
- St. Jude Children’s Research Hospital
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (R01MH110163)
- the Norwegian Institute of Public Health; the Cardiovascular Medical Research and Education Fund; the National Institute on Ageing of the NIH
- The funders for this study are listed in full under Christopher JL Murray
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- risk assessment, evidence synthesis, quality of evidence, risk communication, smoking and lung cancer, vegetable consumption, red meat consumption, ischemic heart disease, global burden of disease, GRADE, meta-analysis
- MeSH terms
- Humans, Risk Factors, Smoking, Myocardial Ischemia, Risk Assessment
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