, Volume 21, Issue 7, pp 1161-1169
Date: 28 Aug 2009

Assessing forearm fracture risk in postmenopausal women

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Abstract

Summary

A diverse array of bone density, structure, and strength parameters were significantly associated with distal forearm fractures in postmenopausal women, but most of them were also correlated with femoral neck areal bone mineral density (aBMD), which provides an adequate measure of bone fragility at the wrist for routine clinical purposes.

Introduction

This study seeks to test the clinical utility of approaches for assessing forearm fracture risk.

Methods

Among 100 postmenopausal women with a distal forearm fracture (cases) and 105 with no osteoporotic fracture (controls), we measured aBMD and assessed radius volumetric bone mineral density, geometry, and microstructure; ultradistal radius failure load was evaluated in microfinite element (μFE) models.

Results

Fracture cases had inferior bone density, geometry, microstructure, and strength. The most significant determinant of fracture in five categories were bone density (femoral neck aBMD; odds ratio (OR) per standard deviation (SD), 2.0; 95% confidence interval (CI), 1.4–2.8), geometry (cortical thickness; OR, 1.5; 95% CI, 1.1–2.1), microstructure (structure model index (SMI); OR, 0.5; 95% CI, 0.4–0.7), and strength (µFE failure load; OR, 1.8; 95% CI, 1.3–2.5); the factor-of-risk (applied load in a forward fall ÷ μFE failure load) was 15% worse in cases (OR, 1.9; 95% CI, 1.4–2.6). Areas under receiver operating characteristic curves (AUC) ranged from 0.62 to 0.68. The predictors of forearm fracture risk that entered a multivariable model were femoral neck aBMD and SMI (combined AUC, 0.71).

Conclusions

Detailed bone structure and strength measurements provide insight into forearm fracture pathogenesis, but femoral neck aBMD performs adequately for routine clinical risk assessment.

This work was supported by research grants R01-AR027065 and UL1-RR024150 (Center for Translational Science Activities) from the National Institutes of Health, U.S. Public Health Service. Supercomputer time was granted by the Swiss National Supercomputing Centre.