The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

Predicting incident radiographic knee osteoarthritis in middle-aged women within 4 years: the importance of knee-level prognostic factors

Predicting incident radiographic knee osteoarthritis in middle-aged women within 4 years: the importance of knee-level prognostic factors
Predicting incident radiographic knee osteoarthritis in middle-aged women within 4 years: the importance of knee-level prognostic factors

Objective

Develop and internally validate risk models and a clinical risk score tool to predict incident radiographic knee osteoarthritis (RKOA) in middle‐aged women.

Methods

We analysed 649 women in the Chingford 1000 Women study. The outcome was incident RKOA, defined as Kellgren/Lawrence grade 0‐1 at baseline and ≥2 at year 5. We estimated predictors' effects on the outcome using logistic regression models. Two models were generated. The clinical model considered patient characteristics, medication, biomarkers, and knee symptoms. The radiographic model considered the same factors, plus radiographic factors (e.g., angle between the acetabular roof and ilium's vertical cortex (hip α‐angle)). The models were internally validated. Model performance was assessed using calibration and discrimination (area under the receiver characteristic curve, AUC).

Results

The clinical model contained age, quadriceps circumference, and a cartilage degradation marker (CTX‐II) as predictors (AUC = 0.692). The radiographic model contained older age, greater quadriceps circumference, knee pain, knee baseline Kellgren/Lawrence grade 1 (versus 0), greater hip α‐angle, greater spinal bone mineral density, and contralateral RKOA at baseline as predictors (AUC = 0.797). Calibration tests showed good agreement between the observed and predicted incident RKOA. A clinical risk score tool was developed from the clinical model.

Conclusion

Two models predicting incident RKOA within 4 years were developed; including radiographic variables improved model performance. First‐time predictor hip α‐angle and contralateral RKOA suggest osteoarthritis origins beyond the knee. The clinical tool has the potential to help physicians identify patients at risk of RKOA in routine practice, but should be externally validated.
0893-7524
88-97
Garriga, Cesar
5403565c-65fd-448f-904f-e41df634c888
Sanchez-Santos, Maria T.
04817dfd-fc86-4801-88f4-e3d54319fe39
Judge, Andrew
c6a83964-1d7c-4aa8-b2bf-9c264d1e487d
Hart, Deborah
1d1f15cd-05f4-488d-abdc-a5466eb55195
Spector, Tim
1fd13fc5-08aa-44c9-b920-c41e925e79d6
Cooper, Cyrus
e05f5612-b493-4273-9b71-9e0ce32bdad6
Arden, Nigel
23af958d-835c-4d79-be54-4bbe4c68077f
Garriga, Cesar
5403565c-65fd-448f-904f-e41df634c888
Sanchez-Santos, Maria T.
04817dfd-fc86-4801-88f4-e3d54319fe39
Judge, Andrew
c6a83964-1d7c-4aa8-b2bf-9c264d1e487d
Hart, Deborah
1d1f15cd-05f4-488d-abdc-a5466eb55195
Spector, Tim
1fd13fc5-08aa-44c9-b920-c41e925e79d6
Cooper, Cyrus
e05f5612-b493-4273-9b71-9e0ce32bdad6
Arden, Nigel
23af958d-835c-4d79-be54-4bbe4c68077f

Garriga, Cesar, Sanchez-Santos, Maria T., Judge, Andrew, Hart, Deborah, Spector, Tim, Cooper, Cyrus and Arden, Nigel (2020) Predicting incident radiographic knee osteoarthritis in middle-aged women within 4 years: the importance of knee-level prognostic factors. Arthritis Care & Research, 72 (1), 88-97. (doi:10.1002/acr.23932).

Record type: Article

Abstract


Objective

Develop and internally validate risk models and a clinical risk score tool to predict incident radiographic knee osteoarthritis (RKOA) in middle‐aged women.

Methods

We analysed 649 women in the Chingford 1000 Women study. The outcome was incident RKOA, defined as Kellgren/Lawrence grade 0‐1 at baseline and ≥2 at year 5. We estimated predictors' effects on the outcome using logistic regression models. Two models were generated. The clinical model considered patient characteristics, medication, biomarkers, and knee symptoms. The radiographic model considered the same factors, plus radiographic factors (e.g., angle between the acetabular roof and ilium's vertical cortex (hip α‐angle)). The models were internally validated. Model performance was assessed using calibration and discrimination (area under the receiver characteristic curve, AUC).

Results

The clinical model contained age, quadriceps circumference, and a cartilage degradation marker (CTX‐II) as predictors (AUC = 0.692). The radiographic model contained older age, greater quadriceps circumference, knee pain, knee baseline Kellgren/Lawrence grade 1 (versus 0), greater hip α‐angle, greater spinal bone mineral density, and contralateral RKOA at baseline as predictors (AUC = 0.797). Calibration tests showed good agreement between the observed and predicted incident RKOA. A clinical risk score tool was developed from the clinical model.

Conclusion

Two models predicting incident RKOA within 4 years were developed; including radiographic variables improved model performance. First‐time predictor hip α‐angle and contralateral RKOA suggest osteoarthritis origins beyond the knee. The clinical tool has the potential to help physicians identify patients at risk of RKOA in routine practice, but should be externally validated.

Text
Manuscript ACR reviewed clean 2 - Accepted Manuscript
Download (179kB)
Text
Figure 1 flowchart
Restricted to Repository staff only
Request a copy
Text
Figure 2 cal_dis_Mar 1 2019
Restricted to Repository staff only
Request a copy
Text
Supplementary Text S1 clean
Restricted to Repository staff only
Request a copy
Text
Supplementary Tables ACR cg
Restricted to Repository staff only
Request a copy

Show all 5 downloads.

More information

Accepted/In Press date: 21 May 2019
e-pub ahead of print date: 25 May 2019
Published date: January 2020

Identifiers

Local EPrints ID: 432438
URI: http://eprints.soton.ac.uk/id/eprint/432438
ISSN: 0893-7524
PURE UUID: 50210fb1-ad52-48c7-a317-f38071e5c98a
ORCID for Cyrus Cooper: ORCID iD orcid.org/0000-0003-3510-0709

Catalogue record

Date deposited: 12 Jul 2019 16:31
Last modified: 26 Nov 2021 05:52

Export record

Altmetrics

Contributors

Author: Cesar Garriga
Author: Maria T. Sanchez-Santos
Author: Andrew Judge
Author: Deborah Hart
Author: Tim Spector
Author: Cyrus Cooper ORCID iD
Author: Nigel Arden

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×