Development of A Model for Predicting The 4-Year Risk of Systematic Knee Osteoarthritis in China: A Longitudinal Cohort Study

Abstract

Objectives: We aimed to develop a model for predicting the 4-year risk of knee osteoarthritis (KOA) based on survey data obtained via a random, nationwide sample of Chinese individuals.Methods: We analyzed data from 8,193 middle-aged and older adults included in the China Health and Retirement Longitudinal Study (CHARLS). The incident of systematic KOA was defined as participants were free of systematic KOA at baseline (CHARLS2011) and were diagnosed with systematic KOA at the 4-year follow-up (CHARLS2015). We estimated the effects of potential predictors on the incident of KOA using logistic regression models and validated the final model internally. Model performance was assessed based on discrimination (area under the receiver operating characteristic curve, AUC) and calibration. Results: A total of 815 incident cases of KOA were identified at the four-year follow-up, resulting in a cumulative incidence of approximately 9.95%. The final multivariate model included age, sex, waist circumference, residential area, difficulty with activities of daily living (ADLs)/instrumental activities of daily living (IADLs), history of hip fracture, depressive symptoms, number of chronic comorbidities, self-rated health status, and level of moderate physical activity (MPA). The bias-corrected AUC for this model was 0.704. The calibration curve revealed satisfactory agreement between the observed and predicted incidence of systematic KOA. A simple clinical score model was developed for easily quantifying the risk of KOA based on these factors.Conclusion: Our prediction model may aid in the early identification of individuals at the greatest risk of developing KOA within 4 years.