Literature DB >> 17680721

Structural determinants of vertebral fracture risk.

L Joseph Melton1, B Lawrence Riggs, Tony M Keaveny, Sara J Achenbach, Paul F Hoffmann, Jon J Camp, Peggy A Rouleau, Mary L Bouxsein, Shreyasee Amin, Elizabeth J Atkinson, Richard A Robb, Sundeep Khosla.   

Abstract

UNLABELLED: Vertebral fractures are more strongly associated with specific bone density, structure, and strength parameters than with areal BMD, but all of these variables are correlated.
INTRODUCTION: It is unclear whether the association of areal BMD (aBMD) with vertebral fracture risk depends on bone density per se, bone macro- or microstructure, overall bone strength, or spine load/bone strength ratios.
MATERIALS AND METHODS: From an age-stratified sample of Rochester, MN, women, we identified 40 with a clinically diagnosed vertebral fracture (confirmed semiquantitatively) caused by moderate trauma (cases; mean age, 78.6 +/- 9.0 yr) and compared them with 40 controls with no osteoporotic fracture (mean age, 70.9 +/- 6.8 yr). Lumbar spine volumetric BMD (vBMD) and geometry were assessed by central QCT, whereas microstructure was evaluated by high-resolution pQCT at the ultradistal radius. Vertebral failure load ( approximately strength) was estimated from voxel-based finite element models, and the factor-of-risk (phi) was determined as the ratio of applied spine loads to failure load.
RESULTS: Spine loading (axial compressive force on L3) was similar in vertebral fracture cases and controls (e.g., for 90 degrees forward flexion, 2639 versus 2706 N; age-adjusted p = 0.173). However, fracture cases had inferior values for most bone density and structure variables. Bone strength measures were also reduced, and the factor-of-risk (phi) was 35-37% greater (worse) among women with a vertebral fracture. By age-adjusted logistic regression, relative risks for the strongest fracture predictor in each of the five main variable categories were bone density (total lumbar spine vBMD: OR per SD change, 2.2; 95% CI, 1.1-4.3), bone geometry (vertebral apparent cortical thickness: OR, 2.1; 95% CI, 1.1-4.1), bone microstructure (none significant); bone strength ("cortical" [outer 2 mm] compressive strength: OR, 2.5; 95% CI, 1.3-4.8), and factor-of-risk (phi for 90 degrees forward flexion/overall vertebral compressive strength: OR, 3.2; 95% CI, 1.4-7.5). These variables were correlated with spine aBMD (partial r, -0.32 to 0.75), but each was a stronger predictor of fracture in the logistic regression analyses.
CONCLUSIONS: The association of aBMD with vertebral fracture risk is explained by its correlation with more specific bone density, structure, and strength parameters. These may allow deeper insights into fracture pathogenesis.

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Year:  2007        PMID: 17680721     DOI: 10.1359/jbmr.070728

Source DB:  PubMed          Journal:  J Bone Miner Res        ISSN: 0884-0431            Impact factor:   6.741


  81 in total

1.  Phantomless calibration of CT scans for measurement of BMD and bone strength-Inter-operator reanalysis precision.

Authors:  David C Lee; Paul F Hoffmann; David L Kopperdahl; Tony M Keaveny
Journal:  Bone       Date:  2017-08-01       Impact factor: 4.398

2.  QCT measures of bone strength at the thoracic and lumbar spine: the Framingham Study.

Authors:  Elizabeth J Samelson; Blaine A Christiansen; Serkalem Demissie; Kerry E Broe; Qiong Louie-Gao; L Adrienne Cupples; Benjamin J Roberts; Rajaram Manoharam; John D'Agostino; Thomas Lang; Douglas P Kiel; Mary L Bouxsein
Journal:  J Bone Miner Res       Date:  2012-03       Impact factor: 6.741

3.  Individual trabecula segmentation (ITS)-based morphological analyses and microfinite element analysis of HR-pQCT images discriminate postmenopausal fragility fractures independent of DXA measurements.

Authors:  X Sherry Liu; Emily M Stein; Bin Zhou; Chiyuan A Zhang; Thomas L Nickolas; Adi Cohen; Valerie Thomas; Donald J McMahon; Felicia Cosman; Jeri Nieves; Elizabeth Shane; X Edward Guo
Journal:  J Bone Miner Res       Date:  2012-02       Impact factor: 6.741

4.  Vertebral body bone strength: the contribution of individual trabecular element morphology.

Authors:  I H Parkinson; A Badiei; M Stauber; J Codrington; R Müller; N L Fazzalari
Journal:  Osteoporos Int       Date:  2011-11-16       Impact factor: 4.507

5.  Trabecular structure analysis using C-arm CT: comparison with MDCT and flat-panel volume CT.

Authors:  Catherine M Phan; Eric A Macklin; Miriam A Bredella; Monica Dadrich; Paul Flechsig; Albert J Yoo; Joshua A Hirsch; Rajiv Gupta
Journal:  Skeletal Radiol       Date:  2010-07-25       Impact factor: 2.199

Review 6.  Bone Imaging and Fracture Risk after Spinal Cord Injury.

Authors:  W Brent Edwards; Thomas J Schnitzer
Journal:  Curr Osteoporos Rep       Date:  2015-10       Impact factor: 5.096

Review 7.  Effects of bone matrix proteins on fracture and fragility in osteoporosis.

Authors:  Grażyna E Sroga; Deepak Vashishth
Journal:  Curr Osteoporos Rep       Date:  2012-06       Impact factor: 5.096

8.  Association of High-resolution Peripheral Quantitative Computed Tomography (HR-pQCT) bone microarchitectural parameters with previous clinical fracture in older men: The Osteoporotic Fractures in Men (MrOS) study.

Authors:  Howard A Fink; Lisa Langsetmo; Tien N Vo; Eric S Orwoll; John T Schousboe; Kristine E Ensrud
Journal:  Bone       Date:  2018-05-08       Impact factor: 4.398

9.  Rapid cortical bone loss in patients with chronic kidney disease.

Authors:  Thomas L Nickolas; Emily M Stein; Elzbieta Dworakowski; Kyle K Nishiyama; Mafo Komandah-Kosseh; Chiyuan A Zhang; Donald J McMahon; Xiaowei S Liu; Stephanie Boutroy; Serge Cremers; Elizabeth Shane
Journal:  J Bone Miner Res       Date:  2013-08       Impact factor: 6.741

10.  Functional and association analysis of frizzled 1 (FZD1) promoter haplotypes with femoral neck geometry.

Authors:  Yingze Zhang; Allison L Kuipers; Laura M Yerges-Armstrong; Cara S Nestlerode; Zhao Jin; Victor W Wheeler; Alan L Patrick; Clareann H Bunker; Joseph M Zmuda
Journal:  Bone       Date:  2010-01-04       Impact factor: 4.398

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