Abstract
The objective of this study was to evaluate right proximal femur shape as a risk factor for incident hip fracture using active shape modeling (ASM). A nested case-control study of white women 65 years of age and older enrolled in the Study of Osteoporotic Fractures (SOF) was performed. Subjects (n = 168) were randomly selected from study participants who experienced hip fracture during the follow-up period (mean 8.3 years). Controls (n = 231) had no fracture during follow-up. Subjects with baseline radiographic hip osteoarthritis were excluded. ASM of digitized right hip radiographs generated 10 independent modes of variation in proximal femur shape that together accounted for 95% of the variance in proximal femur shape. The association of ASM modes with incident hip fracture was analyzed by logistic regression. Together, the 10 ASM modes demonstrated good discrimination of incident hip fracture. In models controlling for age and body mass index (BMI), the area under receiver operating characteristic (AUROC) curve for hip shape was 0.813, 95% confidence interval (CI) 0.771–0.854 compared with models containing femoral neck bone mineral density (AUROC = 0.675, 95% CI 0.620–0.730), intertrochanteric bone mineral density (AUROC = 0.645, 95% CI 0.589–0.701), femoral neck length (AUROC = 0.631, 95% CI 0.573–0.690), or femoral neck width (AUROC = 0.633, 95% CI 0.574–0.691). The accuracy of fracture discrimination was improved by combining ASM modes with femoral neck bone mineral density (AUROC = 0.835, 95% CI 0.795–0.875) or with intertrochanteric bone mineral density (AUROC = 0.834, 95% CI 0.794–0.875). Hips with positive standard deviations of ASM mode 4 had the highest risk of incident hip fracture (odds ratio = 2.48, 95% CI 1.68–3.31, p < .001). We conclude that variations in the relative size of the femoral head and neck are important determinants of incident hip fracture. The addition of hip shape to fracture-prediction tools may improve the risk assessment for osteoporotic hip fractures. © 2011 American Society for Bone and Mineral Research.
Highlights
Hip fracture is a major cause of morbidity and mortality for the elderly worldwide.[1]
It has been demonstrated that measurements of proximal femur shape improve prediction models of hip fracture.[4]. The shape of the proximal femur determines how mechanical forces are distributed during falls.[5]. In a pilot study (n 1⁄4 50), Gregory and colleagues found that the addition of proximal femur shape to bone mineral density (BMD) resulted in a 90% discriminatory accuracy of fracture prediction compared with 82% accuracy using BMD alone.[4]. In another study, Beck and colleagues[6] reported that the strength of the proximal femur was better predicted by bone geometry than by BMD, highlighting the importance of hip shape in determining fracture risk
In order to confirm these results, we repeated the analysis using 1:1 and 1:2 case-to-control ratios, and again, we observed no significant association between hip shape active shape modeling (ASM) modes and case or control status, suggesting that our findings in the original case-control sample were not spurious. In this community-based sample of postmenopausal white women, we found that hip shape as analyzed by ASM was a robust determinant of incident hip fractures
Summary
Hip fracture is a major cause of morbidity and mortality for the elderly worldwide.[1]. It has been demonstrated that measurements of proximal femur shape improve prediction models of hip fracture.[4] The shape of the proximal femur determines how mechanical forces are distributed during falls.[5] In a pilot study (n 1⁄4 50), Gregory and colleagues found that the addition of proximal femur shape to BMD resulted in a 90% discriminatory accuracy of fracture prediction compared with 82% accuracy using BMD alone.[4] In another study, Beck and colleagues[6] reported that the strength of the proximal femur was better predicted by bone geometry than by BMD, highlighting the importance of hip shape in determining fracture risk. ASM is a technique for statistical modeling of shape, providing an average shape for the object being examined as well as principal
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call