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A quantitative approach to benefit‐risk assessment of medicines – part 1: the development of a new model using multi‐criteria decision analysis
Author(s) -
Mussen Filip,
Salek Sam,
Walker Stuart
Publication year - 2007
Publication title -
pharmacoepidemiology and drug safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.023
H-Index - 96
eISSN - 1099-1557
pISSN - 1053-8569
DOI - 10.1002/pds.1435
Subject(s) - multiple criteria decision analysis , risk analysis (engineering) , medicine , risk assessment , judgement , weighting , decision analysis , sophistication , actuarial science , management science , operations research , computer science , business , economics , social science , computer security , mathematical economics , sociology , law , political science , engineering , radiology
Purpose One of the most important uses of benefit‐risk assessment pertains to approval of new medicines by regulatory authorities and the subsequent review of these products during their life‐cycle when new safety and/or efficacy data becomes available. At present, there exist no validated, well‐accepted models for benefit‐risk assessment that have the appropriate degree of sophistication, and as a consequence no models are widely used by regulatory authorities or industry. The aim of the study was therefore to develop a new model for benefit‐risk assessment of medicines using multi‐criteria decision analysis (MCDA). Methods The MCDA methodology was used for a systematic approach to assess the benefit risk ratio of medicines. The reasons for adopting this approach were (1) taking multiple benefit and risk criteria into account, (2) making a judgement on the evidence and potential uncertainty because of the incompleteness of evidence, and (3) making trade‐offs of the benefits against risks. Results It was demonstrated through a seven‐step approach how MCDA is used to construct the model. Ten benefit and ten risk criteria were identified to form a value tree. Then fixed scales were established for all criteria and options on the criteria were scored. Weights were assigned for each criteria using swing‐weighting. Finally sensitivity analysis was carried. Conclusions This novel approach based on MCDA has the potential for being applied as a new tool for judging and deciding on the benefits and risks, thereby helping regulators and industry in the development and approval of new medicines and their adequate use. Copyright © 2007 John Wiley & Sons, Ltd.