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Fracture Risk Assessment: From Population to Individual


Fracture caused by osteoporosis remains a major public health burden on contemporary populations because fracture is associated with a substantial increase in the risk of mortality. Early identification of high-risk individuals for prevention is a priority in osteoporosis research. Over the past decade, few risk prediction models, including the Garvan Fracture Risk Calculator (Garvan) and FRAX(R), have been developed to provide absolute (individualized) risk of fracture. Recent validation studies suggested that the area under the receiver operating characteristic curve in fracture discrimination ranged from 0.61 to 0.83 for FRAX(R) and from 0.63 to 0.88 for Garvan, with hip fractures having a better discrimination than fragility fractures as a group. Although the prognostic performance of Garvan and FRAX(R) for fracture prediction is not perfect and there is room for further improvement, these predictive models can aid patients and doctors communicate about fracture risk in the medium term and to make rational decisions. However, the application of these predictive models in making decisions for an individual should take into account the individual's perception of the importance of fracture relative to other diseases.

Type Journal
ISBN 1094-6950 (Print) 1094-6950 (Linking)
Authors Nguyen, T. V.; Eisman, J. A.
Responsible Garvan Author Prof John Eisman
Published Date 2017-09-01
Published Volume 20
Published Issue 3
Published Pages 368-378
Status Published in-print
DOI 10.1016/j.jocd.2017.06.023
URL link to publisher's version