External Validation of a Prognostic Model for Predicting Nonresponse Following Knee Arthroplasty.

Published

Journal Article

BACKGROUND: Instruments designed to predict the extent of pain and function following knee arthroplasty (KA) recovery has strong potential to guide patients and clinicians in shared decision making. Our purpose was to test the external validity of a recently developed prognostic instrument designed to estimate the probability of nonresponse following KA. METHODS: We used data from the Osteoarthritis Initiative (OAI), a 9-year multisite National Institutes of Health study designed to examine the natural history of knee osteoarthritis in 4796 subjects. A total of 427 subjects underwent KA over the study period. Dowsey et al examined the prognostic role of obesity, general mental health, pain and function, and Kellgren and Lawrence knee osteoarthritis grades. Calibration of the prognostic model was determined using a calibration curve. The c-statistic was used to indicate discrimination of the model. RESULTS: In the primary analysis, 63 (19.3%) of 326 subjects in OAI were classified as nonresponders. The calibration curve generated from OAI data indicated poor calibration relative to the recently developed instrument. Discrimination as measured by the c-statistic was 0.76. CONCLUSION: The external validity of the prognostic instrument was partially supported. While discrimination of the model was very similar to the recently developed instrument, calibration was poor indicating poor agreement between actual vs predicted probabilities of nonresponse. Western Ontario and McMaster Universities Arthritis Index and Kellgren and Lawrence grades show strong potential for use in future prognostic model development. Measurements of general mental health and obesity were not prognostic for nonresponse.

Full Text

Duke Authors

Cited Authors

  • Riddle, DL; Golladay, GJ; Jiranek, WA; Perera, RA

Published Date

  • April 2017

Published In

Volume / Issue

  • 32 / 4

Start / End Page

  • 1153 - 1158.e1

PubMed ID

  • 27919582

Pubmed Central ID

  • 27919582

Electronic International Standard Serial Number (EISSN)

  • 1532-8406

Digital Object Identifier (DOI)

  • 10.1016/j.arth.2016.11.007

Language

  • eng

Conference Location

  • United States