Literature DB >> 11883408

Improving risk assessment: hip geometry, bone mineral distribution and bone strength in hip fracture cases and controls. The EPOS study. European Prospective Osteoporosis Study.

N J Crabtree1, H Kroger, A Martin, H A P Pols, R Lorenc, J Nijs, J J Stepan, J A Falch, T Miazgowski, S Grazio, P Raptou, J Adams, A Collings, K T Khaw, N Rushton, M Lunt, A K Dixon, J Reeve.   

Abstract

Hip geometry and bone mineral density (BMD) have previously been shown to relate independently to hip fracture risk. Our objective was to determine by how much hip geometric data improved the identification of hip fracture. Lunar pencil beam scans of the proximal femur were obtained. Geometric and densitometric values from 800 female controls aged 60 years or more (from population samples which were participants in the European Prospective Osteoporosis Study, EPOS) were compared with data from 68 female hip fracture patients aged over 60 years who were scanned within 4 weeks of a contralateral hip fracture. We used Lunar DPX 'beta' versions of hip strength analysis (HSA) and hip axis length (HAL) applied to DPX(L) data. Compressive stress (Cstress), calculated by the HSA software to occur as a result of a typical fall on the greater trochanter, HAL, body mass index (BMI: weight/(height)2) and age were considered alongside femoral neck BMD (FN-BMD, g/cm2) as potential predictors of fracture. Logistic regression was used to generate predictors of fracture initially from FN-BMD. Next age, Cstress (as the most discriminating HSA-derived parameter), HAL and BMI were added to the model as potentially independent predictors. It was not necessary to include both HAL and Cstress in the logistic models, so the entire data set was examined without excluding the subjects missing HAL measurements. Cstress combined with age and BMI provided significantly better prediction of fracture than FN-BMD used alone as is current practice, judged by comparing areas under receiver operating characteristic (ROC) curves (p<0.001, deLong's test). At a specificity of 80%, sensitivity in identification was improved from 66% to 81%. Identifying women at high risk of hip fracture is thus likely to be substantially enhanced by combining bone density with age, simple anthropometry and data on the structural geometry of the hip. HSA might prove to be a valuable enhancement of DXA densitometry in clinical practice and its use could justify a more proactive approach to identifying women at high risk of hip fracture in the community.

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Year:  2002        PMID: 11883408     DOI: 10.1007/s198-002-8337-y

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


  42 in total

1.  Evidence for bone formation on the external "periosteal" surface of the femoral neck: a comparison of intracapsular hip fracture cases and controls.

Authors:  J Power; N Loveridge; N Rushton; M Parker; J Reeve
Journal:  Osteoporos Int       Date:  2003-02-18       Impact factor: 4.507

2.  Combination of bone mineral density and upper femur geometry improves the prediction of hip fracture.

Authors:  Pasi Pulkkinen; Juha Partanen; Pekka Jalovaara; Timo Jämsä
Journal:  Osteoporos Int       Date:  2004-02-03       Impact factor: 4.507

Review 3.  Bone quality: where do we go from here?

Authors:  Mary L Bouxsein
Journal:  Osteoporos Int       Date:  2003-08-29       Impact factor: 4.507

Review 4.  How pleiotropic genetics of the musculoskeletal system can inform genomics and phenomics of aging.

Authors:  David Karasik
Journal:  Age (Dordr)       Date:  2010-07-02

Review 5.  Bone geometry and skeletal fragility.

Authors:  Mary L Bouxsein; David Karasik
Journal:  Curr Osteoporos Rep       Date:  2006-06       Impact factor: 5.096

6.  Age-related factors affecting the postyield energy dissipation of human cortical bone.

Authors:  Jeffry S Nyman; Anuradha Roy; Jerrod H Tyler; Rae L Acuna; Heather J Gayle; Xiaodu Wang
Journal:  J Orthop Res       Date:  2007-05       Impact factor: 3.494

7.  Establishment of peak bone mineral density in Southern Chinese males and its comparisons with other males from different regions of China.

Authors:  Li-Jun Tan; Shu-Feng Lei; Xiang-Ding Chen; Man-Yuan Liu; Yan-Fang Guo; Hong Xu; Xiao Sun; Cheng Jiang; Su-Mei Xiao; Jing-Jing Guo; Yan-Jun Yang; Fei-Yan Deng; Yan-Bo Wang; Yuan-Neng Li; Xue-Zhen Zhu; Hong-Wen Deng
Journal:  J Bone Miner Metab       Date:  2007-02-26       Impact factor: 2.626

8.  Age trends in proximal femur geometry in men: variation by race and ethnicity.

Authors:  T G Travison; T J Beck; G R Esche; A B Araujo; J B McKinlay
Journal:  Osteoporos Int       Date:  2007-11-24       Impact factor: 4.507

9.  Development of a parametric finite element model of the proximal femur using statistical shape and density modelling.

Authors:  Daniel P Nicolella; Todd L Bredbenner
Journal:  Comput Methods Biomech Biomed Engin       Date:  2011-06-01       Impact factor: 1.763

Review 10.  Role of cortical bone in hip fracture.

Authors:  Jonathan Reeve
Journal:  Bonekey Rep       Date:  2017-01-13
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