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Predictive Performance of Radiographic, MRI & Clinical Symptoms for Subsequent Knee Replacement Principal Investigator: C. Kent Kwoh, MD
Funding: EMD Serono,
Biopharmaceutical Division
of Merck KGaA, Darmstadt, Germany The knee is one of the joints most commonly affected by osteoarthritis (OA). Symptoms include pain, stiffness, a grating or grinding sensation when you move the joint and swellings. Treatment depends on how severe the patient’s pain is and ranges from simple painkillers to joint replacement surgery. With more than 600,000 procedures performed each year, the average U.S. cost of a total knee replacement is nearly $50,000.

The overall objective of this study is to evaluate the predictive performance of radiographic joint space width, quantitative and semi-quantitative MRI measures and clinical symptoms for subsequent knee replacement.

This project utilizes data from the Osteoarthritis Initiative (OAI) and the Pivotal OAI MRI Analyses (POMA), an ancillary proposal to the OAI. The OAI is a longitudinal observational cohort study that enrolled 4,800 participants with or at risk of developing knee osteoarthritis at four clinical centers (i.e., University of Pittsburgh, Ohio State University, University of Maryland and Memorial Hospital in Rhode Island). The OAI was designed to identify biomarkers for the development and progression of knee OA. POMA was designed to identify imaging biomarkers of the progression knee osteoarthritis to knee replacement

Investigators will assess how changes in imaging-based structure measurements predict clinical outcomes such as knee replacement in a sample of patients that met the eligibility criteria for enrollment into a clinical trial of a disease-modifying osteoarthritis drug (DMOAD) for knee osteoarthritis. The exposures of interest include quantitative measures of joint space width, quantitative MRI measures of cartilage morphology and semi-quantitative MRI measures of joint morphology. They will also examine various measures of knee symptoms.

The ultimate goal of this project is to better understand the progression of knee osteoarthritis and the factors that can discriminate between those patients who progress at a faster rate compared to a slower rate. These results will help to identify populations at higher risk of disease progression and target them for therapeutic interventions in knee OA.