Easily Acquired Data Can Predict Knee Osteoarthritis in High-Risk Patients

Among people with high risk for knee osteoarthritis (OA), easily assessable factors from data can be used to identify people at increased risk for incidence functional impairment, according to study results published in the Annals of the Rheumatic Diseases.

The study included patients at high risk for knee OA from the Osteoarthritis Initiative (derivation cohort, n=1870) and the Multicenter Osteoarthritis Study (validation cohort, n=1279). The primary outcome was incident slow gait over up to 10 years of follow-up. The researchers used derivation cohort classification and regression tree analysis to identify predictors from easily assessed variables and develop risk stratification models. They then applied those parameters to the validation cohort using logistic regression to compare risk group predictive values.

Within 10 years of follow-up, incidence slow gait speed occurred in 11% of patients (n=206) in the derivation cohort and 11.2% (n=143) of patients in the validation cohort.

Stratifying by age and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Function produced a 3-risk-group tree, which was the most parsimonious model. They also identified a 7-risk-group tree that included age, WOMAC Function, education, strenuous sport/recreational activity, obesity, and depressive symptoms. While the 7-risk-group, 9-risk-group, 11-risk-group, and the larger trees were within 1 standard error of the most parsimonious model, any tree with 11 or more risk groups became difficult to interpret.

The results indicated that outcome risk varied greatly depending on tree-based-risk group membership, with 0-29% in the derivation group and 2-23% in the validation group.

The area under the receiver operating characteristic curves (AUCs) were similar in the derivation and validation groups, with an AUC of 0.75 (95% CI, 0.72-0.78) for the derivation group and 0.72 (95% CI, 0.68-0.76) in the validation group for the 7-risk-group tree.

“These trees can inform an individual’s awareness, at an early stage, of risk for impaired function, and define eligibility for prevention trials,” the researchers concluded.

Reference

Sharma L, Kwoh K, Lee J, et al. Development and validation of risk stratification trees for incident slow gait speed in persons at high risk for knee osteoarthritis [published online June 26, 2019]. Ann Rheum Dis. doi:10.1136/annrheumdis-2019-215353