Development and Validation of Prediction Models for the Risk of Knee Replacement Using Data from Multi-Center Cohort Studies

Abstract

Background: There is a paucity of prognostic prediction models for KR. We aimed to develop and validate predictive models for knee replacement (KR). Methods: We identified participants with recent knee pain in the Multicenter Osteoarthritis Study (MOST) and the Osteoarthritis Initiative (OAI). We developed two predictive models for the risk of KR over 60 months by fitting Cox proportional hazard models among participants in the MOST. The first model included socio-demographic and anthropometric factors, medical history and clinical measures (i.e., clinical model). The second model added radiographic findings into predictive model (i.e., radiographic model). We evaluated each model’s discrimination and calibration performance and assessed the incremental value of radiographic findings using both category-free net reclassification improvement (NRI) and integrated discrimination improvement (IDI). We externally validated both models among participants in the OAI. Findings: We included 2658 participants of the MOST (mean age=62·4 years, 61·9% women) and 4060 participants of the OAI (mean age=60·9 years, 58·6% women). The C statistic was 0·79 (95% CI: 0·76-0·81) for the clinical model and 0·87 (95% CI: 0·85-0·99) for the radiographic model. The calibration slope was 0·95 (95% CI: 0·86-1·05) and 0·96 (0·87-1·04), respectively. Adding radiograph findings significantly improved predictive performance with an NRI of 0·42 (95% CI: 0·34-0·48) and IDI of 0·13 (95% CI: 0·09-0·16). Both models showed a good predictive performance among participants in the OAI. Interpretation: Our study developed and externally validated two models that demonstrated good discrimination and calibration ability in predicting the risk of KR. Adding radiographic findings substantially improved the predictive ability. Funding: National Natural Science Foundation of China (81902247, 81672183) and Beijing Municipal Science & Technology Commission (D171100003217002, Z181100001618020). Declaration of Interest: None to declare. Ethical Approval: The institutional review board at each of the sites of the Multicenter Osteoarthritis Study and the Osteoarthritis Initiative approved the study, and informed consent was obtained from all participants.