Pragmatic Multicriteria Decision Analysis (MCDA) Combined With Advanced Pharmacoepidemiology for Benefit-Risk Assessments of Medicines Adapted to the Real-Life Constraints of Regulators: Development and Case Study

Abstract

Background: Multicriteria decision analysis (MCDA) represents a promising method for benefit-risk assessment. Our goal was to develop features of pragmatic MCDA (EVIDEM [Evidence and Value: Impact on DEcisionMaking]) addressing real-life regulatory decision-making needs, incorporate advanced pharmacoepidemiology, and test the resulting benefit-risk framework using a case study.

Methods: The Intervention Outcomes domain of EVIDEM was transformed into a generic benefit-risk framework including clinical efficacy, patient-reported outcomes, and adverse event (AE) criteria. The concept of relative benefit-risk balance (RBRB) was developed for comparability across products and therapeutic areas and over time. Evidence matrix was designed to include most relevant data from trials, observational studies, and models, including Bayesian and longitudinal modeling. The framework was tested with a panel of stakeholders using efalizumab for psoriasis as retrospective case study. Uncertainty was explored.

Results: The MCDA benefit-risk tree was adapted with psoriasis-specific subcriteria. Panelists assigned similar weights to benefits (0.48; SD, 0.20-0.70) and risks (0.52; SD, 0.10-0.60), with large variations reflecting diverse perspectives. Panelist scores reflected higher efficacy versus placebo, lower efficacy versus active comparators, and serious and fatal AEs identified postlicensing. Efalizumab's RBRB was positive at licensing in 2004 (0.29, scale -1 to +1) and ranged from -0.41 (vs active comparators) to 0.01 (vs placebo) in 2009, when its market authorization was withdrawn. Retesting indicated good reproducibility. Panelists acknowledged good face validity and the importance of criteria beyond benefit-risk in real-life assessments.

Conclusions: The approach allows quantification and visualization of benefit-risk over time and across comparators. Combination of pragmatic MCDA designed to integrate criteria beyond benefit-risk and advanced statistics supports application of MCDA to further accountable benefit-risk assessments for real-life decision making.

Keywords: Bayesian analysis; benefit-risk; longitudinal modeling; multicriteria decision making; regulatory decision making.