Structured benefit-risk evaluation for medicinal products: review of quantitative benefit-risk assessment findings in the literature

Abstract

A favorable benefit-risk profile remains an essential requirement for marketing authorization of medicinal drugs and devices. Furthermore, prior subjective, implicit and inconsistent ad hoc benefit-risk assessment methods have rightly evolved towards more systematic, explicit or "structured" approaches. Contemporary structured benefit-risk evaluation aims at providing an objective assessment of the benefit-risk profile of medicinal products and a higher transparency for decision making purposes. The use of a descriptive framework should be the preferred starting point for a structured benefit-risk assessment. In support of more precise assessments, quantitative and semi-quantitative methodologies have been developed and utilized to complement descriptive or qualitative frameworks in order to facilitate the structured evaluation of the benefit-risk profile of medicinal products. In addition, quantitative structured benefit-risk analysis allows integration of patient preference data. Collecting patient perspectives throughout the medical product development process has become increasingly important and key to the regulatory decision-making process. Both industry and regulatory authorities increasingly rely on descriptive structured benefit-risk evaluation and frameworks in drug, vaccine and device evaluation and comparison. Although varied qualitative methods are more commonplace, quantitative approaches have recently been emphasized. However, it is unclear how frequently these quantitative frameworks have been used by pharmaceutical companies to support submission dossiers for drug approvals or to respond to the health authorities' requests. The objective of this study has been to identify and review, for the first time, currently available, published, structured, quantitative benefit-risk evaluations which may have informed health care professionals and/or payor as well as contributed to decision making purposes in the regulatory setting for drug, vaccine and/or device approval.

Plain language summary: Quantitative evaluation of the benefit-risk balance for medicinal products The review of the benefits and the risks associated with a medicinal product is called benefit-risk assessment. One of the conditions for a medicinal product to receive marketing authorization is to demonstrate a positive benefit-risk balance in which the benefits outweigh the risks. In order to enhance the transparency and consistency in the assessment of benefit-risk balance, frameworks and quantitative methods have been developed for decision making purposes and regulatory approvals of medicinal products. This article considers published quantitative benefit-risk evaluations which may have informed health care professionals and/or payor as well as contributed to decision making purposes in the regulatory setting for drug, vaccine and/or device approval.

Keywords: benefit–risk; decision making; multi-criteria decision analysis; patient perspective; physician perspective; quantitative; regulation; regulatory perspective; structured.

Figure 1.

Algorithm to define the appropriate benefit–risk methodology (based on the PROTECT recommendations), extracted from Hughes et al. BR, benefit–risk; BRAT, Benefit–risk Action Team; ITC/MTC, indirect treatment comparison/mixed treatment comparison; MCDA, multi-criteria decision analysis; PrOACT-URL, problem, objectives, alternatives, consequences, trade-off, uncertainly, risk tolerance, and linked decisions; PROTECT, Pharmacoepidemiological Research on Outcomes of Therapeutics by a European Consortium; wNCB, weighted net clinical benefit.

Figure 2.

Overview of descriptive and quantitative frameworks from PROTECT, extracted from PROTECT website. AE-NNT: Adverse event adjusted number needed to treat; ASF, Ashby and Smith framework; BLRA, benefit-less-risk analysis; Beckmann: Beckmann model (aka evidence based-model); BRAFO, Benefit–risk analysis for foods; BR, benefit–risk ; BRAT, Benefit–risk Action Team; BRR, Benefit–risk ratio; CA, Conjoint analysis; CDS, Cross-design synthesis; CMR-CASS, Centre for Medicines Research Health Canada, Australia’s Therapeutic Goods Administration, SwissMedic and Singapore Health Science Authority; COBRA, Consortium On Benefit-Risk Assessment; CPM, Confidence profile method; CUI, Clinical Utility Index; CV, Contingent valuation; DAGs, Directed acyclic graphs; DALY, Disability-adjusted life years; DCE, Discrete choice experiment; DI, Desirability Index; FDA BRF, The US FDA Benefit-Risk Framework; GBR, Global benefit–risk; HALE, Health-adjusted life years; INHB, Incremental net health benefit; ITC, Indirect treatment comparison; MAR, Maximum acceptable risk; MCDA, Multi-Criteria Decision Analysis; MCE, Minimum clinical efficacy; MDP, Markov Decision Process; MTC: Mixed treatment comparison; NCB, Net Clinical Benefit; NEAR, Net efficacy adjusted for risk; NNH, number needed to harm; NNT, number needed to treat; OMERACT 3x3; Outcome measures in rheumatology 3 × 3; Principle of 3s: Principle of threes; PrOACT-URL, problem, objectives, alternatives, consequences, tradeoff, uncertainly, risk tolerance, and linked decisions; PROTECT, Pharmacoepidemiological Research on Outcomes of Therapeutics by a European Consortium; PSM, Probabilistic simulation method; QALY, Quality-adjusted life years; Q-TWIST, Quality-adjusted time without symptoms and Toxicity; RV-MCE, Relative value-adjusted minimum clinical efficacy; RV-NNH, Relative value-adjusted number needed to (treat to) harm; SABRE, Southeast Asia benefit–risk evaluation; SBRAM, Saracs’ Benefit-Risk Assessment Method; SMAA, Stochastic Multi-attribute Acceptability Analysis; SPM, Stated preference method; TURBO, Transparent uniform risk–benefit overview; UMBRA, Unified Methodology for Benefit-Risk Assessment; UT-NNT, Utility-adjusted and time-adjusted number needed to treat.