Development of a clinical prediction algorithm for knee osteoarthritis structural progression in a cohort study: value of adding measurement of subchondral bone density.
Development of a clinical prediction algorithm for knee osteoarthritis structural progression in a cohort study: value of adding measurement of subchondral bone density.
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DOI：
10.1186/s13075-017-1291-3
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发表时间：
2017-05-16
影响因子：
4.9
通讯作者：
McAlindon TE
中科院分区：
文献类型：
--
作者：
LaValley MP;Lo GH;Price LL;Driban JB;Eaton CB;McAlindon TE
风险预测算法可以增加对哪些患者面临有害结果风险最大的了解。我们的目标是使用内侧关节间隙损失作为代表，创建一种临床上有用的膝骨关节炎 (OA) 结构进展预测算法；并量化算法中包含关节周围骨矿物质密度 (BMD) 的益处。参与者来自骨关节炎倡议 (OAI) 进展队列，在 36 和 48 个月就诊时获得内侧关节间隙的 X 射线读数，以及 30 或 36 个月内侧胫骨 BMD 比（M:L BMD 比）值。结果是内侧关节间隙丧失，并且在基本预测算法中采用了与 OA 进展相关的临床可用因素，并将 M:L BMD 比率添加到增强的预测算法中。通过 ROC 曲线下面积 (AUC) 的变化、净重分类改进 (NRI) 和综合辨别改进 (IDI) 来评估增加 M:L BMD 比率的益处。参与者有五百三十三人； 51 人（14%）有内侧关节间隙损失； 47%为女性；平均 (SD) 年龄为 64.6 (9.2) 岁，BMI 为 29.6 (4.8) kg/m2。基本算法模型包括年龄、BMI、性别、近期受伤情况、膝盖疼痛和手部 OA 作为预测因子，AUC 值为 0.65。添加M:L BMD比率的算法的AUC值为0.73，并且AUC、NRI和IDI均显着改善（p≤≤0.002）。该临床预测算法仅使用临床可用的预测因子并辅以 M:L BMD 比率（一种可在临床站点提供的生物标志物）来预测 OA 个体的结构进展。
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, 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.