Novel nomogram for predicting the progression of osteoarthritis based on 3D-MRI bone shape: data from the FNIH OA biomarkers consortium

Author:

Sun Yingwei,Deng Chunbo,Zhang Zhan,Ma Xun,Zhou Fenghua,Liu Xueyong

Abstract

Abstract Background Osteoarthritis(OA) is a major source of pain, disability, and socioeconomic cost in worldwide. However, there is no effective means for the early diagnosis of OA, nor can it accurately predict the progress of OA. To develop and validate a novel nomogram to predict the radiographic progression of mild to moderate OA based on three-dimensional(3D)-MRI bone shape and bone shape change during 24 months. Method Analysis of publicly available data from the Foundation for the National Institutes of Health (FNIH) OA Biomarkers Consortium. Radiographic progression was defined as minimum radiographic narrowing of the medial tibiofemoral joint space of ≥ 0.7 mm from baseline at 24, 36, or 48 months. There were 297 knees with radiographic progression and 303 without. The bone shapes of the tibia, femur, and patella were evaluated by 3D-MRI at the baseline and at 24 months. Two nomograms were separately established by multivariate logistic regression analysis using clinical risk factors, bone shape at baseline (nomogram 0), or bone shape change at 24 months (nomogram Δ24). The discrimination, calibration, and usefulness were selected to evaluate the nomograms. Results There were significant differences between groups in baseline Kellgren-Lawrence (KL) grade, gender, age, and tibia, femur, and patella shape. The areas under the curve (AUC) of nomogram 0 and nomogram Δ24 were 0.66 and 0.75 (p < 0.05), with accuracy of 0.62 and 0.69, respectively. Both nomograms had good calibration. The decision curve analysis ( DCA) showed that nomogram Δ24 had greater clinical usefulness than nomogram 0 when the risk threshold ranged from 0.04 to 0.86. Conclusions Nomograms based on 3D-MRI bone shape change were useful for predicting the radiographic progression of mild to moderate OA.

Funder

Natural Science Foundation of Liaoning Province of China

The Joint Program of Key Research and Development of Liaoning Province of China

Publisher

Springer Science and Business Media LLC

Subject

Orthopedics and Sports Medicine,Rheumatology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3