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A benefit–risk assessment model for statins using multicriteria decision analysis based on a discrete choice experiment in Korean patients

Authors Byun J, Kwon S, Ha J, Lee E

Received 12 November 2015

Accepted for publication 9 April 2016

Published 13 June 2016 Volume 2016:12 Pages 965—974


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Garry Walsh

Ji-Hye Byun,1 Sun-Hong Kwon,1 Ji-Hye Ha,2 Eui-Kyung Lee1

1School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do, 2Ministry of Food and Drug Safety, Cheongju-si, Chungcheongbuk-do, South Korea

Purpose: The benefit–risk balance for drugs can alter post approval owing to additional data on efficacy or adverse events. This study developed a quantitative benefit–risk assessment (BRA) model for statins using multicriteria decision analysis with discrete choice experiments and compared a recent BRA with that at the time of approval.
Patients and methods: Following a systematic review of the literature, the benefit criteria within the statin BRA model were defined as a reduction in the plasma low-density lipoprotein cholesterol level and a reduction in myocardial infarction incidence; the risk criteria were hepatotoxicity (Liv) and fatal rhabdomyolysis (Rha). The scores for these criteria were estimated using mixed treatment comparison methods. Weighting was calculated from a discrete choice experiment involving 203 Korean patients. The scores and weights were integrated to produce an overall value representing the benefit–risk balance, and sensitivity analyses were conducted.
Results: In this BRA model, low-density lipoprotein (relative importance [RI]: 37.50%) was found to be a more important benefit criterion than myocardial infarction (RI: 35.43%), and Liv (RI: 16.28%) was a more important risk criterion than Rha (RI: 10.79%). Patients preferred atorvastatin, and the preference ranking of cerivastatin and simvastatin was switched post approval because of the emergence of additional risk information related to cerivastatin.
Conclusion: A quantitative statin BRA model confirmed that the preference ranking of statins changed post approval because of the identification of additional benefits or risks.

Keywords: multicriteria decision analysis, statin, quantitative benefit–risk assessment, discrete choice experiment

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