Arden, NK

Cooper, C

Garriga-Fuentes, C

Hart, D

Javaid, K

Javaid, MK

Judge, A

Leyland, KM

Prieto-Alhambra, D

Sanchez-Santos, MT

Spector, T

Garriga-Fuentes, Cesar

Sanchez-Santos, Maria T

Judge, Andrew

Javaid, M Kassim

Leyland, Kirsten M

Prieto-Alhambra, Daniel

Arden, Nigel K

Oxford University Research Archive

2812FORECASTING INCIDENT RADIOGRAPHIC KNEE OSTEOARTHRITIS FOR WOMEN:THE RELEVANCE OF HIP MORPHOLOGY AND BONE MINERAL DENSITYC. Garriga1, M. T. Sanchez-Santos1,2, A. Judge1,3, K. Javaid1,3, K. M. Leyland1,2, D. Prieto-Alhambra1, D.Hart4, T. Spector4, C. Cooper1,3, N. K. Arden1,21Musculoskeletal epidemiology. Botnar Research Centre. Nuffield Department of Orthopaedics,Rheumatology and Musculoskeletal Sciences. University of Oxford, Oxford, United Kingdom, 2ArthritisResearch UK Centre for Sport, Exercise and Osteoarthritis. Nuffield Department of Orthopaedics,Rheumatology and Musculoskeletal Sciences. University of Oxford, Oxford, United Kingdom, 3MRCLifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton,United Kingdom, 4Department of Twin Research & Genetic Epidemiology, King's College London,London, United KingdomObjectiveTo develop and internally validate a clinical risk model to predict incident radiographic knee osteoarthritis(RKOA) in a population-based cohort of middle aged women.MethodsWe followed-up 649 women (1,662 knees) with x-ray at baseline (year 1) and year 5 using communitybased cohort of women in London, UK, 1988-1994. The outcome was incident RKOA defined as Kellgrenand Lawrence (K/L) grade 0-1 at baseline and ≥2 at year 5. Bootstrap backward logistic regression analysisidentified predictors of incident RKOA. Two models were generated: 1.a clinical model included patientmeasures, medication, wet biomarkers and knee symptoms; and 2.a model adding radiological variables.Models performance was assessed by calibration and discrimination.ResultsUnivariable analysis found 33 of 105 factors associated with incident RKOA (p<0.20). The clinical modelidentified age, quadriceps circumference and cartilage degradation markers (serum cross linked C-telopeptide of type II collagen) as predictors. After including radiological variables (radiological model),the predictors of outcome were older age, higher quadriceps circumference, knee pain, knee baseline K/Lgrade 1 (versus grade 0), higher hip α-angle, higher z-score bone mineral density (BMD) at the spineL1-L4, and contralateral RKOA at baseline. Calibration statistics showed high level of agreement. Thearea under the curve (AUC) for the clinical model was 0.692, reaching 0.797 in the radiological model.ConclusionsWe have developed and internally validated two models predicting incident osteoarthritis in short term (4years). The most powerful prediction is related to radiological variables including hip morphology andBMD as important predictors. This points to a RKOA origin beyond the knee area and are potentiallyuseful for clinical and epidemiological studies.Powered by TCPDF (www.tcpdf.org)

English

Forecasting incident radiographic knee osteoarthritis for women: the relevance of hip morphology and bone mineral density

Forecasting incident radiographic knee osteoarthritis for women: the relevance of hip morphology and bone mineral density

Abstract

Similar works

Full text

Available Versions

Oxford University Research Archive