Abstract
Objective. Treatment of OA by stratifying for commonly used and novel therapies will likely improve the range of effective therapy options and their rational deployment in this undertreated, chronic disease. In order to develop appropriate datasets for conducting post hoc analyses to inform approaches to stratification for OA, our aim was to develop recommendations on the minimum data that should be recorded at baseline in all future OA interventional and observational studies.Methods. An Arthritis Research UK study group comprised of 32 experts used a Delphi-style approach supported by a literature review of systematic reviews to come to a consensus on core data collection for OA studies.Results. Thirty-five systematic reviews were used as the basis for the consensus group discussion. For studies with a primary structural endpoint, core domains for collection were defined as BMI, age, gender, racial origin, comorbidities, baseline OA pain, pain in other joints and occupation. In addition to the items generalizable to all anatomical sites, joint-specific domains included radiographic measures, surgical history and anatomical factors, including alignment. To demonstrate clinical relevance for symptom studies, the collection of mental health score, self-efficacy and depression scales were advised in addition to the above.Conclusions. Currently it is not possible to stratify patients with OA into therapeutic groups. A list of core and optional data to be collected in all OA interventional and observational studies was developed, providing a basis for future analyses to identify predictors of progression or response to treatment.
Highlights
OA represents a considerable worldwide health and economic challenge [1]
Thirty-five systematic reviews were used as the basis for the consensus group discussion
A list of core and optional data to be collected in all OA interventional and observational studies was developed, providing a basis for future analyses to identify predictors of progression or response to treatment
Summary
OA represents a considerable worldwide health and economic challenge [1]. OA is a heterogeneous disease driven by a variety of pathophysiologic factors, current therapy selection is largely arbitrary. The development of a stratification strategy for OA requires knowledge of both predictors of disease progression to identify patients requiring treatment and predictors of the response to treatment, which together will allow the identification of subsets of patients within which treatments may have improved efficacy. Such data may be gathered prospectively in well-designed interventional and observational studies and retrospectively through post hoc analyses of single studies and linking or pooling of study data for meta-analyses. To ensure robust analyses and reliability of results, consistent data collection across studies is essential
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