The approach consortium: a 2-year, European, cohort study to describe, validate, and predict phenotypes of knee osteoarthritis by use of clinical, imaging, and biochemical markers

Purpose: There is a major, unmet need for (combinations of) markers to improve the quality of clinical trials in the field of osteoarthritis (OA). Firstly, effective markers could be used as ‘prognostic’ markers for prospective identification of subjects that will show significant OA progression within a study period. Secondly, they could serve as ‘predictive’ markers and help identify different phenotypes of knee OA, that would potentially benefit from different therapies. Lastly, as ‘response’ markers, they could serve as more sensitive outcome measurements to study investigational therapies. Together, having more effective markers for OA would lead to an investigational and therapeutic approach based on different phenotypes of OA, rather than the current ‘one size fits all’ approach. The goal of the APPROACH study (Applied Public-Private Research enabling OsteoArthritis Clinical Headway), is to identify such prognostic, predictive and response knee OA markers, and with that, give the development of OA treatments a new impulse. Objectives of APPROACH are:1.To validate a prognostic model of sustained pain and decrease in minimum joint space width (mJSW) in knee OA patients.2.To develop and validate prognostic models for OA progression by use of conventional and novel clinical, imaging, and biochemical (bio)markers.3.To discover, define and predict novel OA phenotypes.4.To prospectively describe in detail the discovered phenotypes of patients with knee OA by use of conventional and novel clinical, imaging, and biochemical (bio)markers. Methods: Patients with predominant tibiofemoral knee OA, will be selected from five existing European OA cohorts according to a stepwise approach. First, for each cohort, a specific prognostic model using existing demographic, clinical and radiographic parameters will be used to identify patients who are most likely to have OA pain and/or structural progression in the next two years. Selected patients will be invited for a screening visit. During this visit, key ‘predictors’ will be collected and a uniform prediction model will be applied to refine the initial selection of patients. All prediction models have been derived using a machine-learning approach, trained on follow-up data from the Cohort Hip & Cohort Knee (CHECK) and the Osteoarthritis Initiative (OAI). Of all five cohorts, the 300 patients that are most likely to experience pain and/or structural progression over 2 years based on the refined model will be selected to participate in a prospective two-year study. If needed, additional patients will be recruited from outpatient departments and similar data will be run through the algorithm. During the two-year follow-up, at each study visit, a set of conventional and novel clinical, imaging, biochemical, and kinetic markers of the index knee and other joints will be obtained (Table 1). Potential, novel (bio)markers will be studied using epigenetic, transcriptomic, proteomic, lipidomic and metabolomic analyses, and using novel radiographic imaging, quantitative and qualitative MRI imaging, live imaging techniques for visualizing inflammation in hands, and motion analysis techniques. Results: Combinations of conventional and innovative markers at baseline and 6 months will predict the likelihood for OA progression at 12 and 24 months (either pain, structural, or both pain and structural) and identify different OA phenotypes. Conclusions: APPROACH will provide valuable insights into conventional and novel clinical, imaging and biochemical markers for OA. These markers will extend the ability to predict OA progression and distinguish between OA phenotypes. This will enable classification of each patient on a phenotype specific OA progression scale. Ultimately, this will form the basis for phenotype-specific treatments and will decrease the number of subjects and trial duration of potential DMOADs. Acknowledgements: The research leading to these results have received support from the Innovative Medicines Initiative Joint Undertaking under Grant Agreement n° 115770, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies' in kind contribution. See www.imi.europa.eu and www.approachproject.eu. Disclaimer: This communication reflects the views of the authors and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein.