For both economic and ethical reasons, identification of the optimal treatment for each individual patient is a pressing concern, not only for the patients and their physician, but also health care payers and the pharmaceutical industry. In the field of osteoarthritis (OA) this is of particular relevance, due to the heterogeneity of the disease and the very large number of affected individuals. There is a need to pair the right patients with the right therapeutic modes of action. At present, the clinical trial failures in OA may be a consequence of both bona fide treatment failures and trial failures due to clinical design deficiencies. Tools are needed for characterization and segregation of patients with OA. Key lessons may be learned from advances with another form of arthritis, namely rheumatoid arthritis (RA). Personalized health care (PHC) may be more advantageous for a number of specific indications which are characterized by costly therapy, low response rates and significant problems associated with trial and error prescription, including the risk of serious side effects. We discuss the use of diagnostic practices guiding RA treatment, which may serve as a source of key insights for diagnostic practices in OA. We discuss the emerging concept of PHC, and outline the opportunities and current successes and failures across the RA field, as the OA field collects further data to support the hypothesis. We attempt to outline a possible path forward to assist patients, physicians, payers and the pharmaceutical industry in assuring the 'right' patients are treated with the 'right drug' in OA. Finally we highlight methods for possible segregation of OA patients that would allow identification of patient subtypes, such as OA driven by inflammation that may be ideally suited for PHC and for targeted therapies.
Keywords: Biomarkers; Osteoarthritis; Personalized health care; Treatment.
Copyright © 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.