Skip to main content
Top
Published in: Arthritis Research & Therapy 1/2021

01-12-2021 | Knee Osteoarthritis | Research article

Diagnosis of early stage knee osteoarthritis based on early clinical course: data from the CHECK cohort

Authors: Qiuke Wang, Jos Runhaar, Margreet Kloppenburg, Maarten Boers, Johannes W. J. Bijlsma, Sita M. A. Bierma-Zeinstra, the CREDO expert group

Published in: Arthritis Research & Therapy | Issue 1/2021

Login to get access

Abstract

Background

Early diagnosis of knee osteoarthritis (OA) is important in managing this disease, but such an early diagnostic tool is still lacking in clinical practice. The purpose of this study was to develop diagnostic models for early stage knee OA based on the first 2-year clinical course after the patient’s initial presentation in primary care and to identify whether these course factors had additive discriminative value over baseline factors.

Methods

We extracted eligible patients’ clinical and radiographic data from the CHECK cohort and formed the first 2-year course factors according to the factors’ changes over the 2 years. Clinical expert consensus-based diagnosis, which was made via evaluating patients’ 5- to 10-year follow-up data, was used as the outcome factor. Four models were developed: model 1, included clinical course factors only; model 2, included clinical and radiographic course factors; model 3, clinical baseline factors + clinical course factors; and model 4, clinical and radiographic baseline factors + clinical and radiographic course factors. All the models were built by a generalized estimating equation with a backward selection method. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) were calculated for assessing model discrimination. Delong’s method compared AUCs.

Results

Seven hundred sixty-one patients with 1185 symptomatic knees were included in this study. Thirty-seven percent knees were diagnosed as OA at follow-up. Model 1 contained 6 clinical course factors; model 2: 6 clinical and 3 radiographic course factors; model 3: 6 baseline clinical factors combined with 5 clinical course factors; and model 4: 4 clinical and 1 radiographic baseline factors combined with 5 clinical and 3 radiographic course factors. Model discriminations are as follows: model 1, AUC 0.70 (95% CI 0.67–0.74); model 2, 0.74 (95% CI 0.71–0.77); model 3, 0.77 (95% CI 0.74–0.80); and model 4, 0.80 (95% CI 0.77–0.82). AUCs of model 3 and model 4 were slightly but significantly higher than corresponding baseline-factor models (model 3 0.77 vs 0.75, p = 0.031; model 4 0.80 vs 0.76, p = 0.003).

Conclusions

Four diagnostic models were developed with “fair” to “good” discriminations. First 2-year course factors had additive discriminative value over baseline factors.
Appendix
Available only for authorised users
Literature
8.
go back to reference van Oudenaarde K, Jobke B, Oostveen AC, Marijnissen AC, Wolterbeek R, Wesseling J, et al. Predictive value of MRI features for development of radiographic osteoarthritis in a cohort of participants with pre-radiographic knee osteoarthritis-the CHECK study. Rheumatology (Oxford). 2017;56(1):113–20. https://doi.org/10.1093/rheumatology/kew368.CrossRef van Oudenaarde K, Jobke B, Oostveen AC, Marijnissen AC, Wolterbeek R, Wesseling J, et al. Predictive value of MRI features for development of radiographic osteoarthritis in a cohort of participants with pre-radiographic knee osteoarthritis-the CHECK study. Rheumatology (Oxford). 2017;56(1):113–20. https://​doi.​org/​10.​1093/​rheumatology/​kew368.CrossRef
14.
go back to reference Kinds MB, Marijnissen AC, Vincken KL, Viergever MA, Drossaers-Bakker KW, Bijlsma JW, et al. Evaluation of separate quantitative radiographic features adds to the prediction of incident radiographic osteoarthritis in individuals with recent onset of knee pain: 5-year follow-up in the CHECK cohort. Osteoarthritis Cartilage. 2012;20(6):548–56. https://doi.org/10.1016/j.joca.2012.02.009.CrossRefPubMed Kinds MB, Marijnissen AC, Vincken KL, Viergever MA, Drossaers-Bakker KW, Bijlsma JW, et al. Evaluation of separate quantitative radiographic features adds to the prediction of incident radiographic osteoarthritis in individuals with recent onset of knee pain: 5-year follow-up in the CHECK cohort. Osteoarthritis Cartilage. 2012;20(6):548–56. https://​doi.​org/​10.​1016/​j.​joca.​2012.​02.​009.CrossRefPubMed
15.
go back to reference Runhaar J, Kloppenburg M, Boers M, Bijlsma JWJ, Bierma-Zeinstra SMA, the CREDO expert group. Towards developing diagnostic criteria for early knee osteoarthritis; data from the CHECK study. Rheumatology (Oxford). 2020;00:1–8. Runhaar J, Kloppenburg M, Boers M, Bijlsma JWJ, Bierma-Zeinstra SMA, the CREDO expert group. Towards developing diagnostic criteria for early knee osteoarthritis; data from the CHECK study. Rheumatology (Oxford). 2020;00:1–8.
17.
21.
go back to reference Bellamy N, Buchanan WW, Goldsmith CH, Campbell J, Stitt LW. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J Rheumatol. 1988;15(12):1833–40.PubMed Bellamy N, Buchanan WW, Goldsmith CH, Campbell J, Stitt LW. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J Rheumatol. 1988;15(12):1833–40.PubMed
27.
go back to reference Wang Q, Runhaar J, Kloppenburg M, Boers M, Bijlsma JWJ, Bierma-Zeinstra SMA, et al. The added value of radiographs in diagnosing knee osteoarthritis is similar for general practitioners and secondary care physicians; data from the check early osteoarthritis cohort. J Clin Med. 2020;9(10):3374. Wang Q, Runhaar J, Kloppenburg M, Boers M, Bijlsma JWJ, Bierma-Zeinstra SMA, et al. The added value of radiographs in diagnosing knee osteoarthritis is similar for general practitioners and secondary care physicians; data from the check early osteoarthritis cohort. J Clin Med. 2020;9(10):3374.
29.
34.
go back to reference Alba AC, Agoritsas T, Walsh M, Hanna S, Iorio A, Devereaux PJ, et al. Discrimination and calibration of clinical prediction models: users’ guides to the medical literature. JAMA. 2017;318:1377–84 doi:2656816.CrossRefPubMed Alba AC, Agoritsas T, Walsh M, Hanna S, Iorio A, Devereaux PJ, et al. Discrimination and calibration of clinical prediction models: users’ guides to the medical literature. JAMA. 2017;318:1377–84 doi:2656816.CrossRefPubMed
37.
go back to reference B OH, Gransar H, Callister T, Shaw LJ, Schulman-Marcus J, Stuijfzand WJ, et al. Development and validation of a simple-to-use nomogram for predicting 5-, 10-, and 15-year survival in asymptomatic adults undergoing coronary artery calcium scoring. JACC Cardiovasc Imaging. 2018;11:450–8.CrossRef B OH, Gransar H, Callister T, Shaw LJ, Schulman-Marcus J, Stuijfzand WJ, et al. Development and validation of a simple-to-use nomogram for predicting 5-, 10-, and 15-year survival in asymptomatic adults undergoing coronary artery calcium scoring. JACC Cardiovasc Imaging. 2018;11:450–8.CrossRef
40.
go back to reference Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, et al. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020;368:m441.CrossRefPubMed Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, et al. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020;368:m441.CrossRefPubMed
Metadata
Title
Diagnosis of early stage knee osteoarthritis based on early clinical course: data from the CHECK cohort
Authors
Qiuke Wang
Jos Runhaar
Margreet Kloppenburg
Maarten Boers
Johannes W. J. Bijlsma
Sita M. A. Bierma-Zeinstra
the CREDO expert group
Publication date
01-12-2021
Publisher
BioMed Central
Published in
Arthritis Research & Therapy / Issue 1/2021
Electronic ISSN: 1478-6362
DOI
https://doi.org/10.1186/s13075-021-02598-5

Other articles of this Issue 1/2021

Arthritis Research & Therapy 1/2021 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine