Objective: Demonstrate how benefit-risk profiles of systemic treatments for moderate-to-severe osteoarthritis (OA) can be compared using a quantitative approach accounting for patient preference.
Study Design And Setting: This study used a multimethod benefit-risk modelling approach to quantifiably compare treatments of moderate-to-severe OA. In total four treatments and placebo were compared. Comparisons were based on four attributes identified as most important to patients. Patient Global Assessment of Osteoarthritis was included as a favourable effect. Unfavourable effects, or risks, included opioid dependence, nonfatal myocardial infarction and rapidly progressive OA leading to total joint replacement. Clinical data from randomized clinical trials, a meta-analysis of opioid dependence and a long-term study of celecoxib were mapped into value functions and weighted with patient preferences from a discrete choice experiment.
Results: Lower-dose NGFi had the highest weighted net benefit-risk score (0.901), followed by higher-dose NGFi (0.889) and NSAIDs (0.852), and the lowest score was for opioids (0.762). Lower-dose NGFi was the highest-ranked treatment option even when assuming a low incidence (0.34% instead of 4.7%) of opioid dependence (ie, opioid benefit-risk score 808) and accounting for both the uncertainty in clinical effect estimates (first rank probability 46% vs 20% for NSAIDs) and imprecision in patient preference estimates (predicted choice probability 0.26, 95% confidence interval [CI] 0.25-0.28 vs 0.21, 95% CI 0.19-0.23 for NSAIDs).
Conclusion: The multimethod approach to quantitative benefit-risk modelling allowed the interpretation of clinical data from the patient perspective while accounting for uncertainties in the clinical effect estimates and imprecision in patient preferences.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543715 | PMC |
http://dx.doi.org/10.1111/bcp.15309 | DOI Listing |
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