Quantitative Benefit-Risk Assessment in Medical Product Decision Making: A Good Practices Report of an ISPOR Task Force

Tommi Tervonen, Jorien Veldwijk, Katherine Payne, Xinyi Ng, Bennett Levitan, Leila G. Lackey, Kevin Marsh, Praveen Thokala, Francesco Pignatti, Anne Donnelly, Martin Ho

Research output: Contribution to journalArticlepeer-review

Abstract

Benefit-risk assessment is commonly conducted by drug and medical device developers and regulators, to evaluate and communicate issues around benefit-risk balance of medical products. Quantitative benefit-risk assessment (qBRA) is a set of techniques that incorporate explicit outcome weighting within a formal analysis to evaluate the benefit-risk balance. This report describes emerging good practices for the 5 main steps of developing qBRAs based on the multicriteria decision analysis process. First, research question formulation needs to identify the needs of decision makers and requirements for preference data and specify the role of external experts. Second, the formal analysis model should be developed by selecting benefit and safety endpoints while eliminating double counting and considering attribute value dependence. Third, preference elicitation method needs to be chosen, attributes framed appropriately within the elicitation instrument, and quality of the data should be evaluated. Fourth, analysis may need to normalize the preference weights, base-case and sensitivity analyses should be conducted, and the effect of preference heterogeneity analyzed. Finally, results should be communicated efficiently to decision makers and other stakeholders. In addition to detailed recommendations, we provide a checklist for reporting qBRAs developed through a Delphi process conducted with 34 experts.

Original languageEnglish
Pages (from-to)449-460
Number of pages12
JournalVALUE IN HEALTH
Volume26
Issue number4
Early online date31 Mar 2023
DOIs
Publication statusPublished - 1 Apr 2023

Keywords

  • benefit-risk assessment
  • discrete choice experiment
  • multicriteria decision analysis
  • patient preferences
  • stochastic multicriteria acceptability analysis
  • swing weighting
  • threshold technique

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