Abstract

BackgroundRisk prediction algorithms increase understanding of which patients are at greatest risk of a harmful outcome. Our goal was to create a clinically useful prediction algorithm for structural progression of knee osteoarthritis (OA), using medial joint space loss as a proxy; and to quantify the benefit of including periarticular bone mineral density (BMD) in the algorithm.MethodsParticipants were from the Osteoarthritis Initiative (OAI) Progression Cohort, with X-ray readings of medial joint space at 36- and 48-month visits, and a 30- or 36-month medial-to-lateral tibial BMD ratio (M:L BMD ratio) value. Loss of medial joint space was the outcome and clinically available factors associated with OA progression were employed in the base prediction algorithm, with M:L BMD ratio added to an enhanced prediction algorithm. The benefit of adding M:L BMD ratio was evaluated by change in area under the ROC curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).ResultsFive hundred thirty-three participants were included; 51 (14%) had medial joint space loss; 47% were female; the mean (SD) age was 64.6 (9.2) years and BMI was 29.6 (4.8) kg/m2. The base algorithm model included age, BMI, gender, recent injury, knee pain, and hand OA as predictors and had an AUC value of 0.65. The algorithm adding M:L BMD ratio had an AUC value of 0.73, and the AUC, NRI and IDI were all significantly improved (p ≤ 0.002).ConclusionsThis clinical prediction algorithm predicts structural progression in individuals with OA using only clinically available predictors supplemented by the M:L BMD ratio, a biomarker that could be made available at clinical sites.

Highlights

  • Risk prediction algorithms increase understanding of which patients are at greatest risk of a harmful outcome

  • A different potential biomarker for knee OA structural progression is the medial-to-lateral tibial plateau bone mineral density ratio (M:L BMD ratio). This ratio can be acquired from dual-energy X-ray absorptiometry (DXA) scanners which are currently available for clinical imaging at many sites

  • The M:L BMD ratio is predictive of knee OA severity [11, 13] and is highly correlated with compartment-specific joint space narrowing (JSN), osteophytes and sclerosis [16]

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Summary

Introduction

Risk prediction algorithms increase understanding of which patients are at greatest risk of a harmful outcome. Our goal was to create a clinically useful prediction algorithm for structural progression of knee osteoarthritis (OA), using medial joint space loss as a proxy; and to quantify the benefit of including periarticular bone mineral density (BMD) in the algorithm. A different potential biomarker for knee OA structural progression is the medial-to-lateral tibial plateau bone mineral density ratio (M:L BMD ratio). This ratio can be acquired from dual-energy X-ray absorptiometry (DXA) scanners which are currently available for clinical imaging at many sites. Two small longitudinal studies showed that unloading a knee is associated with a reduction of the M:L BMD ratio, suggesting that it is responsive to changes in knee loading [11, 17]

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