Hunter, D J, Deveza, L A, Collins, J E, Losina, E, Nevitt, M C, Roemer, F W, Guermazi, A, Bowes, M A, Dam, E B, Eckstein, F, Lynch, J A, Katz, J N, Kwoh, C K, Hoffmann, S & Kraus, V B 2022, ' Multivariable modeling of biomarker data from the phase 1 Foundation for the NIH Osteoarthritis Biomarkers Consortium ', Arthritis Care & Research, vol. 74, no. 7, pp. 1142-1153 . https://doi.org/10.1002/acr.24557Test
سنة النشر:
2022
الوصف:
OBJECTIVE: To determine the optimal combination of imaging and biochemical biomarkers to predict knee osteoarthritis (OA) progression.METHODS: Nested case-control study from the FNIH OA Biomarkers Consortium of participants with Kellgren-Lawrence grade 1-3 and complete biomarker data (n=539 to 550). Cases were knees with radiographic and pain progression between 24-48 months from baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) with pRESULTS: Among baseline biomarkers, the number of locations affected by osteophytes (SQ), Q central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and SQ Hoffa-synovitis predicted progression in most models (C-statistics 0.641-0.671). 24-month changes in SQ MRI markers (effusion-synovitis, meniscal morphology, and cartilage damage), Q central medial femoral cartilage thickness, Q medial tibial cartilage volume, Q lateral patellofemoral bone area, horizontal TBT (intercept term), and urine NTX-I predicted progression in most models (C-statistics 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, with higher C-statistics (0.716-0.832).CONCLUSION: This study highlights the combination of biomarkers with potential prognostic utility in OA disease-modifying trials. Properly qualified, these biomarkers could be used to enrich future trials with participants likely to progress.
