Can We Identify Patients with High Risk of Osteoarthritis Progression Who Will Respond to Treatment? A Focus on Biomarkers and Frailty

Nigel Arden, Pascal Richette, Cyrus Cooper, Olivier Bruyère, Eric Abadie, Jaime Branco, Maria Luisa Brandi, Francis Berenbaum, Cécile Clerc, Elaine Dennison, Jean-Pierre Devogelaer, Marc Hochberg, Pieter D’Hooghe, Gabriel Herrero-Beaumont, John A. Kanis, Andrea Laslop, Véronique Leblanc, Stefania Maggi, Giuseppe Mautone, Jean-Pierre Pelletier, Florence Petit-Dop, Susanne Reiter-Niesert, René Rizzoli, Lucio Rovati, Eleonora Tajana Messi, Yannis Tsouderos, Johanne Martel-Pelletier, Jean-Yves Reginster

Osteoarthritis (OA), a disease affecting different patient phenotypes, appears as an optimal candidate for personalized healthcare. The aim of the discussions of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) working group was to explore the value of markers of different sources in defining different phenotypes of patients with OA. The ESCEO organized a series of meetings to explore the possibility of identifying patients who would most benefit from treatment for OA, on the basis of recent data and expert opinion. In the first meeting, patient phenotypes were identified according to the number of affected joints, biomechanical factors, and the presence of lesions in the subchondral bone. In the second meeting, summarized in the present article, the working group explored other markers involved in OA. Profiles of patients may be defined according to their level of pain, functional limitation, and presence of coexistent chronic conditions including frailty status. A considerable amount of data suggests that magnetic resonance imaging may also assist in delineating different phenotypes of patients with OA. Among multiple biochemical biomarkers identified, none is sufficiently validated and recognized to identify patients who should be treated. Considerable efforts are also being made to identify genetic and epigenetic factors involved in OA, but results are still limited. The many potential biomarkers that could be used as potential stratifiers are promising, but more research is needed to characterize and qualify the existing biomarkers and to identify new candidates.