Weighted cumulative exposure models helped identify an association between early knee-pain consultations and future knee OA diagnosis

Abstract

Objective
To establish the association between prior knee-pain consultations and early diagnosis of knee osteoarthritis (OA) by weighted cumulative exposure (WCE) models.

Study Design and Setting
Data were from an electronic health care record (EHR) database (Consultations in Primary Care Archive). WCE functions for modeling the cumulative effect of time-varying knee-pain consultations weighted by recency were derived as a predictive tool in a population-based case-control sample and validated in a prospective cohort sample. Two WCE functions ([i] weighting of the importance of past consultations determined a priori; [ii] flexible spline-based estimation) were comprehensively compared with two simpler models ([iii] time since most recent consultation; total number of past consultations) on model goodness of fit, discrimination, and calibration both in derivation and validation phases.

Results
People with the most recent and most frequent knee-pain consultations were more likely to have high WCE scores that were associated with increased risk of knee OA diagnosis both in derivation and validation phases. Better model goodness of fit, discrimination, and calibration were observed for flexible spline-based WCE models.

Conclusion
WCE functions can be used to model prediagnostic symptoms within routine EHR data and provide novel low-cost predictive tools contributing to early diagnosis.