Najafzadeh, MehdiSchneeweiss, SebastianChoudhry, NiteeshBykov, KatsiarynaKahler, Kristijan H.Martin, Diane P.Gagne, Joshua2020-04-282015Najafzadeh, Mehdi, Sebastian Schneeweiss, Niteesh Choudhry, Katsiaryna Bykov, Kristijan H. Kahler, Diane P. Martin, and Joshua J. Gagne. 2015. “A Unified Framework for Classification of Methods for Benefit-Risk Assessment.” Value in Health 18 (2) (March): 250–259. doi:10.1016/j.jval.2014.11.001.1098-3015http://nrs.harvard.edu/urn-3:HUL.InstRepos:42661885BACKGROUND: Patients, physicians, and other decision makers make implicit but inevitable trade-offs among risks and benefits of treatments. Many methods have been proposed to promote transparent and rigorous benefit-risk analysis (BRA). OBJECTIVE: To propose a framework for classifying BRA methods on the basis of key factors that matter most for patients by using a common mathematical notation and compare their results using a hypothetical example. METHODS: We classified the available BRA methods into three categories: 1) unweighted metrics, which use only probabilities of benefits and risks; 2) metrics that incorporate preference weights and that account for the impact and duration of benefits and risks; and 3) metrics that incorporate weights based on decision makers' opinions. We used two hypothetical antiplatelet drugs (a and b) to compare the BRA methods within our proposed framework. RESULTS: Unweighted metrics include the number needed to treat and the number needed to harm. Metrics that incorporate preference weights include those that use maximum acceptable risk, those that use relative-value-adjusted life-years, and those that use quality-adjusted life-years. Metrics that use decision makers' weights include the multicriteria decision analysis, the benefit-less-risk analysis, Boers' 3 by 3 table, the Gail/NCI method, and the transparent uniform risk benefit overview. Most BRA methods can be derived as a special case of a generalized formula in which some are mathematically identical. Numerical comparison of methods highlights potential differences in BRA results and their interpretation. CONCLUSIONS: The proposed framework provides a unified, patient-centered approach to BRA methods classification based on the types of weights that are used across existing methods, a key differentiating feature.en-USJournal Article2015-10-132020-04-2810.1016/j.jval.2014.11.001