Development of a clinical prediction algorithm for knee osteoarthritis structural progression in a cohort study: value of adding measurement of subchondral bone density

Arthritis Research & Therapy
Michael P LavalleyTimothy E McAlindon

Abstract

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. Participants 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). Five 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,...Continue Reading

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Nov 28, 2018·Scientific Reports·Paul O BolcosRami K Korhonen
Oct 17, 2017·Current Opinion in Rheumatology·Cristina Ruiz-RomeroFrancisco J Blanco
Dec 31, 2020·Clinical and Translational Medicine·Liang GaoHenning Madry
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Nov 26, 2021·Journal of Orthopaedic Research : Official Publication of the Orthopaedic Research Society·Paul O BolcosRami K Korhonen

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