title: A unified framework for classification of methods for benefit-risk assessment.
abstract: BACKGROUND
  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.
authors.affiliation: Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: mnajafzadeh@partners.org.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Najafzadeh
authors.affiliation: Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Schneeweiss
authors.affiliation: Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
authors.forename: Niteesh
authors.initials: N
authors.lastname: Choudhry
authors.affiliation: Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
authors.forename: Katsiaryna
authors.initials: K
authors.lastname: Bykov
authors.affiliation: Novartis Pharmaceutical Corporation, East Hanover, NJ, USA.
authors.forename: Kristijan H
authors.initials: KH
authors.lastname: Kahler
authors.affiliation: Novartis Pharmaceutical Corporation, East Hanover, NJ, USA.
authors.forename: Diane P
authors.initials: DP
authors.lastname: Martin
authors.affiliation: Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
authors.forename: Joshua J
authors.initials: JJ
authors.lastname: Gagne
mesh_terms: D003661:Decision Support Techniques; D006801:Humans; D008962:Models, Theoretical; D019057:Quality-Adjusted Life Years; D018570:Risk Assessment
keywords: benefit-risk analysis; harm-benefit analysis