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Patient preferences for treatment attributes in osteoarthritis: protocol for a systematic review of stated preference
Min Liu1,2, Tara Officer3, Mickael Hiligsmann2,4
1Shanghai Normal University Tianhua College, Shanghai, China.
Introduction:
Osteoarthritis (OA) is a common chronic condition requiring long-term management, for which shared decision-making is increasingly recognised as an important component of care. Stated preference (SP) methods, including discrete choice experiments (DCE), conjoint analysis (CA) and best-worst scaling (BWS), are increasingly used to quantify patient preferences for treatment attributes and to inform clinical and policy decisions. However, evidence from SP studies in OA has not been comprehensively synthesised. This protocol describes a systematic review aiming to identify, appraise and synthesise evidence on the relative importance of treatment attributes for patients with OA.
Methods And Analysis:
A comprehensive search will be conducted in PubMed, Embase, CINAHL, Scopus, Dimensions and OpenAlex from database inception to January 2026. Eligible studies will include quantitative SP studies-encompassing DCE, CA and BWS-evaluating patient preferences for pharmacological, non-pharmacological or surgical treatments in OA. Two reviewers will independently screen studies, extract data using a standardised form and assess methodological quality using the Purpose, Respondents, Explanation, Findings and Significance (PREFS) checklist, the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for CA and DCE and the DIscrete choice experiment REporting ChecklisT (DIRECT) checklist for reporting quality. A structured narrative synthesis will summarise and categorise key treatment attributes (eg, efficacy, safety, cost and mode of administration). Where studies are sufficiently comparable in attributes and outcome reporting, a random-effects meta-analysis may be conducted to pool preference estimates, such as relative importance or willingness-to-pay values.
Ethics And Dissemination:
Ethical approval is not required, as this review will use published data only. Findings will be disseminated through peer-reviewed publication and conference presentations.
Prospero Registration Number:
CRD420251181273.
