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Multivariable Modeling of Biomarker Data From the Phase I Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

Authors :
Hunter, David J
Hunter, David J
Deveza, Leticia A
Collins, Jamie E
Losina, Elena
Katz, Jeffrey N
Nevitt, Michael C
Lynch, John A
Roemer, Frank W
Guermazi, Ali
Bowes, Michael A
Dam, Erik B
Eckstein, Felix
Kwoh, C Kent
Hoffmann, Steve
Kraus, Virginia B
Hunter, David J
Hunter, David J
Deveza, Leticia A
Collins, Jamie E
Losina, Elena
Katz, Jeffrey N
Nevitt, Michael C
Lynch, John A
Roemer, Frank W
Guermazi, Ali
Bowes, Michael A
Dam, Erik B
Eckstein, Felix
Kwoh, C Kent
Hoffmann, Steve
Kraus, Virginia B
Source :
Arthritis care & research; vol 74, iss 7, 1142-1153; 2151-464X
Publication Year :
2022

Abstract

ObjectiveTo determine the optimal combination of imaging and biochemical biomarkers for use in the prediction of knee osteoarthritis (OA) progression.MethodsThe present study was a nested case-control trial from the Foundation of the National Institutes of Health OA Biomarkers Consortium that assessed study participants with a Kellgren/Lawrence grade of 1-3 who had complete biomarker data available (n = 539 to 550). Cases were participants' knees that had radiographic and pain progression between 24 and 48 months compared to baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) that had a P value of <0.10 in univariate analysis were selected, including quantitative cartilage thickness and volume on magnetic resonance imaging (MRI), semiquantitative MRI markers, bone shape and area, quantitative meniscal volume, radiographic progression (trabecular bone texture [TBT]), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using 3 different stepwise selection methods (complex models versus parsimonious models).ResultsAmong 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-synovitis predicted OA progression in most models (C statistic 0.641-0.671). In most models, 24-month changes in semiquantitative MRI markers (effusion-synovitis, 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-telopeptide of type I collagen predicted OA progression (C statistic 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, whic

Details

Database :
OAIster
Journal :
Arthritis care & research; vol 74, iss 7, 1142-1153; 2151-464X
Notes :
application/pdf, Arthritis care & research vol 74, iss 7, 1142-1153 2151-464X
Publication Type :
Electronic Resource
Accession number :
edsoai.on1391586248
Document Type :
Electronic Resource