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Externally validated models for first diagnosis and risk of progression of knee osteoarthritis.
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- Author(s): McCabe, Philippa Grace1 (AUTHOR) ; Lisboa, Paulo1 (AUTHOR); Baltzopoulos, Bill2 (AUTHOR); Olier, Ivan1 (AUTHOR)
- Source:
PLoS ONE. 7/1/2022, Vol. 17 Issue 7, p1-23. 23p.- Subject Terms:
- Source:
- Additional Information
- Abstract: Objective: We develop and externally validate two models for use with radiological knee osteoarthritis. They consist of a diagnostic model for KOA and a prognostic model of time to onset of KOA. Model development and optimisation used data from the Osteoarthritis initiative (OAI) and external validation for both models was by application to data from the Multicenter Osteoarthritis Study (MOST). Materials and methods: The diagnostic model at first presentation comprises subjects in the OAI with and without KOA (n = 2006), modelling with multivariate logistic regression. The prognostic sample involves 5-year follow-up of subjects presenting without clinical KOA (n = 1155), with modelling with Cox regression. In both instances the models used training data sets of n = 1353 and 1002 subjects and optimisation used test data sets of n = 1354 and 1003. The external validation data sets for the diagnostic and prognostic models comprised n = 2006 and n = 1155 subjects respectively. Results: The classification performance of the diagnostic model on the test data has an AUC of 0.748 (0.721–0.774) and 0.670 (0.631–0.708) in external validation. The survival model has concordance scores for the OAI test set of 0.74 (0.7325–0.7439) and in external validation 0.72 (0.7190–0.7373). The survival approach stratified the population into two risk cohorts. The separation between the cohorts remains when the model is applied to the validation data. Discussion: The models produced are interpretable with app interfaces that implement nomograms. The apps may be used for stratification and for patient education over the impact of modifiable risk factors. The externally validated results, by application to data from a substantial prospective observational study, show the robustness of models for likelihood of presenting with KOA at an initial assessment based on risk factors identified by the OAI protocol and stratification of risk for developing KOA in the next five years. Conclusion: Modelling clinical KOA from OAI data validates well for the MOST data set. Both risk models identified key factors for differentiation of the target population from commonly available variables. With this analysis there is potential to improve clinical management of patients. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of PLoS ONE is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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