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

• Published in: Arthritis research & therapy 2017-05, Vol.19 (1), p.95-95, Article 95
• Main Authors: LaValley, Michael P, Lo, Grace H, Price, Lori Lyn, Driban, Jeffrey B, Eaton, Charles B, McAlindon, Timothy E
• Format: Article
• Language: English
• Subjects: Algorithms; Arthritis; Biomarkers; Bone density; Bone marrow; Calibration; Cohort analysis; Discrimination; Joint space loss; Joint surgery; Knee; Logistic regression; NMR; Nonsteroidal anti-inflammatory drugs; Nuclear magnetic resonance; Pain; Risk factors; ROC curve
• ISSN: 1478-6362; 1478-6354; 1478-6362
• DOI: 10.1186/s13075-017-1291-3

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/m . 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). This 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.