Psychological profiles in adults with knee osteoarthritis related pain: A replication study

Abstract

Psychological factors have been associated with knee osteoarthritis pain severity and treatment outcomes, yet their combined contribution to phenotypic heterogeneity is poorly understood. In particular, empirically-derived psychological profiles must be replicated before they can be targeted or considered for treatment studies. The objectives of this study were to (1) confirm previously identified psychological profiles using unsupervised clustering methods in persons with knee osteoarthritis pain, (2) determine the replicability of profiles using supervised machine learning in a different sample, and (3) examine associations with clinical pain. Participants with knee osteoarthritis pain were recruited for two multi-site studies: Study1 (n=270, mean age=56.8 ± 7.6, male=37%), and Study2 (n=164, mean age=57.73±7.8, male=36%). Similar psychological constructs (e.g. optimism, coping, somatization, affect, depression, and anxiety), sociodemographic and pain characteristics were assessed in both samples. Unsupervised hierarchical clustering analysis was first conducted on Study1 data to derive clusters, followed by a supervised linear discriminant analysis applied to Study2 data to assess replicability of psychological clusters. Associations among cluster membership and pain outcomes were examined using one-way analysis of covariance, controlling for race, age, sex, education, and study site in both datasets. Based on the psychological data in Study1, four distinct clusters emerged. These clusters showed strong associations with psychological variables (p's