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Development and validation of prediction models to estimate risk of primary total hip and knee replacements using data from the UK: two prospective open cohorts using the UK Clinical Practice Research Datalink

Yu, Dahai; Jordan, Kelvin P; Snell, Kym I E; Riley, Richard D; Bedson, John; James Edwards, John; Mallen, Christian D; Tan, Valerie; Ukachukwu, Vincent; Prieto-Alhambra, Daniel; Walker, Christine; Peat, George

Development and validation of prediction models to estimate risk of primary total hip and knee replacements using data from the UK: two prospective open cohorts using the UK Clinical Practice Research Datalink Thumbnail


Authors

Kym I E Snell

Richard D Riley

John Bedson

John James Edwards

Valerie Tan

Vincent Ukachukwu

Daniel Prieto-Alhambra

Christine Walker

George Peat



Abstract

Abstract
Objectives The ability to efficiently and accurately predict future risk of primary total hip and knee replacement (THR/TKR) in earlier stages of osteoarthritis (OA) has potentially important applications. We aimed to develop and validate two models to estimate an individual’s risk of primary THR and TKR in patients newly presenting to primary care.

Methods We identified two cohorts of patients aged =40 years newly consulting hip pain/OA and knee pain/OA in the Clinical Practice Research Datalink. Candidate predictors were identified by systematic review, novel hypothesis-free ‘Record-Wide Association Study’ with replication, and panel consensus. Cox proportional hazards models accounting for competing risk of death were applied to derive risk algorithms for THR and TKR. Internal–external cross-validation (IECV) was then applied over geographical regions to validate two models.

Results 45 predictors for THR and 53 for TKR were identified, reviewed and selected by the panel. 301 052 and 416 030 patients newly consulting between 1992 and 2015 were identified in the hip and knee cohorts, respectively (median follow-up 6 years). The resultant model C-statistics is 0.73 (0.72, 0.73) and 0.79 (0.78, 0.79) for THR (with 20 predictors) and TKR model (with 24 predictors), respectively. The IECV C-statistics ranged between 0.70–0.74 (THR model) and 0.76–0.82 (TKR model); the IECV calibration slope ranged between 0.93–1.07 (THR model) and 0.92–1.12 (TKR model).

Conclusions Two prediction models with good discrimination and calibration that estimate individuals’ risk of THR and TKR have been developed and validated in large-scale, nationally representative data, and are readily automated in electronic patient records.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made.

Acceptance Date Sep 15, 2018
Publication Date Oct 18, 2018
Publicly Available Date Jun 16, 2023
Journal Annals of the Rheumatic Diseases
Print ISSN 0003-4967
Publisher BMJ Publishing Group
DOI https://doi.org/10.1136/annrheumdis-2018-213894
Publisher URL https://doi.org/10.1136/annrheumdis-2018-213894

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