Abstract
BackgroundPain is the most troubling issue to patients with osteoarthritis (OA), yet current pharmacological treatments offer only small-to-moderate pain reduction. Current guidelines therefore emphasise the need to identify predictors of treatment response. In line with these recommendations, an individual patient data (IPD) meta-analysis will be conducted. The study aims to investigate the relative treatment effects of topical non-steroidal anti-inflammatory drugs (NSAIDs) and topical capsaicin in OA and to identify patient-level predictors of treatment response.MethodsIPD will be collected from randomised controlled trials (RCTs) of topical NSAIDs and capsaicin in OA. Multilevel regression modelling will be conducted to determine predictors for the specific and the overall treatment effect.DiscussionThrough the identification of treatment responders, this IPD meta-analysis may improve the current understanding of the pain mechanisms in OA and guide clinical decision-making. Identifying and prescribing the treatment most likely to be beneficial for an individual with OA will improve the efficiency of patient management.Systematic review registrationCRD42016035254Electronic supplementary materialThe online version of this article (doi:10.1186/s13643-016-0348-8) contains supplementary material, which is available to authorized users.
Highlights
Pain is the most troubling issue to patients with osteoarthritis (OA), yet current pharmacological treatments offer only small-to-moderate pain reduction
The primary aim for this study is to investigate the relative treatment effects of topical Non-steroidal anti-inflammatory drug (NSAID) and topical capsaicin in OA and to identify patient-level predictors of treatment response
An individual patient data (IPD) meta-analysis forms a part of precision medicine
Summary
An IPD meta-analysis forms a part of precision medicine It helps identify potential predictors of treatment response at a patient level, which is not possible with conventional meta-analyses. It is very difficult to acquire data for a specific question from all studies, especially data related to subgroup indicators This limits the IPD analysis to predictors that are available in the eligible studies. It may not be possible to contact original trial authors, authors may not be willing to collaborate, or they may not have access to the raw data required [45, 46] These difficulties, if not overcome, may introduce bias to the meta-analysis if the studies not included are systematically different from those included [45,46,47].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
