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

Cesar Garriga, Maria T. Sanchez-Santos, Andrew Judge, Deborah Hart, Tim D Spector, Cyrus Cooper, Nigel Arden

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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 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.
Original languageEnglish
Number of pages34
JournalArthritis Care and Research
Early online date25 May 2019
DOIs
Publication statusE-pub ahead of print - 25 May 2019

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