A stochastic multicriteria model for evidence‐based decision making in drug benefit‐risk analysis

Abstract

Drug benefit‐risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi‐criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi‐criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi‐criteria model for the therapeutic group of second‐generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade‐offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

Evidence-Based Prescribing

“…30,34 We then applied a structured benefit-risk model that allows evidence on multiple outcomes to be combined using qualitative preference statements. 25,30,35 This benefit-risk model took into account the probability distributions of all outcomes of interest and quantified the uncertainty around a decision, while keeping outcome measurements and value judgments clearly separated. 25 Specifically, we sampled from the posteriors for the absolute risk on each outcome, which were translated to a partial use between 0 and 1 (where 1 was best possible and 0 the worst possible value) for all alternative treatments and for all outcomes.…”

“…25,30,35 This benefit-risk model took into account the probability distributions of all outcomes of interest and quantified the uncertainty around a decision, while keeping outcome measurements and value judgments clearly separated. 25 Specifically, we sampled from the posteriors for the absolute risk on each outcome, which were translated to a partial use between 0 and 1 (where 1 was best possible and 0 the worst possible value) for all alternative treatments and for all outcomes. For each such sample, there was a corresponding set of criteria weights (preferences), which summed to 1.…”

“…A more formal approach is needed to help prescribers and patients in identifying a firstline drug among multiple alternatives. One such approach is multicriteria decision analysis, 25 which is a formal framework for analysis of complex decision problems involving trade-offs between multiple outcomes. 26 An attractive feature of multicriteria decision analysis is that it applies qualitative or quantitative preferences on different outcomes, allowing for a transparent judgment on their relative importance.…”

Ranking Turkish Cities and Regions for Air Quality Using a Multi-Criteria Decision-Making Method

“…SMAA-2 was found to be a suitable multi-criteria evaluation method to evaluate the performance of the modelling techniques. Tervonen et al used SMAA-2 in their study for decision making in drug benefit-risk analysis [29]. The data of a former study were used to execute the results with the new method.…”

Balancing benefit and risk of medicines: a systematic review and classification of available methodologies

“…Relative value-adjusted number needed to (treat to) harm Decision tree 82,101,102 Decision tree SABRE 54 Southeast Asia benefit-risk evaluation DI 27,84,85 desirability index SBRAM 52 Sarac's benefit-risk assessment FDA BRF 103,104 FDA benefit-risk framework SMAA [105][106][107] Stochastic multicriteria acceptability analysis GBR 16,108 Global benefit-risk SPM 97 Stated preference method HALE 30,31 Health-adjusted life years TURBO 5,49 Transparent uniform risk-benefit overview Impact numbers [109][110][111][112] Impact numbers UMBRA 54 Unified methodologies for benefit-risk assessment INHB 10,[113][114][115] Incremental net health benefit UT-NNT 116 Utility-adjusted and time-adjusted number needed to treat ITC 3,4,66 Indirect treatment comparison Estimation techniques include generic statistical techniques. They are not unique to benefit-risk assessment but are readily applicable in combination with other benefit-risk methods.…”