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Multivariable logistic regression models were built using 3 different stepwise selection methods (complex models versus parsimonious models).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among baseline biomarkers, the number of locations affected by osteophytes (semiquantitative), quantitative central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and semiquantitative Hoffa\u2010synovitis predicted OA progression in most models (C statistic 0.641\u20130.671). In most models, 24\u2010month changes in semiquantitative MRI markers (effusion\u2010synovitis, meniscal morphologic changes, and cartilage damage), quantitative central medial femoral cartilage thickness, quantitative medial tibial cartilage volume, quantitative lateral patellofemoral bone area, horizontal TBT (intercept term), and urine N\u2010telopeptide of type I collagen predicted OA progression (C statistic 0.680\u20130.724). A different combination of imaging and biochemical biomarkers (baseline and 24\u2010month change) predicted radiographic progression only, which had a higher C statistic of 0.716\u20130.832.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The present study highlights the combination of biomarkers with potential prognostic utility in OA disease\u2010modifying trials. 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