The University of Southampton
University of Southampton Institutional Repository

Predicting fractures in an international cohort using risk factor algorithms without BMD

Sambrook, Philip N., Flahive, Julie, Hooven, Fred H., Boonen, Steven, Chapurlat, Roland, Lindsay, Robert, Nguyen, Tuan V., Diez-Perez, Adolfo, Pfeilschifter, Johannes, Greenspan, Ssusan L., Hosmer, David, Netelenbos, J. Coen, Adachi, Jonathan D., Watts, Nelson B., Cooper, Cyrus, Roux, Christian, Rossini, Maurizio, Siris, Ethel S., Silverman, Stuart, Saag, Kenneth G., Compston, Juliet E., LaCroix, Andrea and Gehlbach, Stephen (2011) Predicting fractures in an international cohort using risk factor algorithms without BMD Journal of Bone and Mineral Research, 26, (11), pp. 2770-2777. (doi:10.1002/jbmr.503). (PMID:21887705).

Record type: Article


Clinical risk factors are associated with increased probability of fracture in postmenopausal women. We sought to compare prediction models using self-reported clinical risk factors, excluding BMD, to predict incident fracture among postmenopausal women. The GLOW study enrolled women aged 55 years or older from 723 primary-care practices in 10 countries. The population comprised 19,586 women aged 60 years or older who were not receiving antiosteoporosis medication and were followed annually for 2 years. Self-administered questionnaires were used to collect data on characteristics, fracture risk factors, previous fractures, and health status. The main outcome measure compares the C index for models using the WHO Fracture Risk (FRAX), the Garvan Fracture Risk Calculator (FRC), and a simple model using age and prior fracture. Over 2 years, 880 women reported incident fractures including 69 hip fractures, 468 “major fractures” (as defined by FRAX), and 583 “osteoporotic fractures” (as defined by FRC). Using baseline clinical risk factors, both FRAX and FRC showed a moderate ability to correctly order hip fracture times (C index for hip fracture 0.78 and 0.76, respectively). C indices for “major” and “osteoporotic” fractures showed lower values, at 0.61 and 0.64. Neither algorithm was better than the model based on age?+?fracture history alone (C index for hip fracture 0.78). In conclusion, estimation of fracture risk in an international primary-care population of postmenopausal women can be made using clinical risk factors alone without BMD. However, more sophisticated models incorporating multiple clinical risk factors including falls were not superior to more parsimonious models in predicting future fracture in this population.

Full text not available from this repository.

More information

Published date: November 2011
Keywords: fracture, risk factors, postmenopausal women, prediction, models
Organisations: Faculty of Medicine


Local EPrints ID: 201825
ISSN: 0884-0431
PURE UUID: eb398d7f-5682-4597-ace7-cf3f1eacd81b
ORCID for Cyrus Cooper: ORCID iD

Catalogue record

Date deposited: 01 Nov 2011 10:46
Last modified: 18 Jul 2017 11:12

Export record



Author: Philip N. Sambrook
Author: Julie Flahive
Author: Fred H. Hooven
Author: Steven Boonen
Author: Roland Chapurlat
Author: Robert Lindsay
Author: Tuan V. Nguyen
Author: Adolfo Diez-Perez
Author: Johannes Pfeilschifter
Author: Ssusan L. Greenspan
Author: David Hosmer
Author: J. Coen Netelenbos
Author: Jonathan D. Adachi
Author: Nelson B. Watts
Author: Cyrus Cooper ORCID iD
Author: Christian Roux
Author: Maurizio Rossini
Author: Ethel S. Siris
Author: Stuart Silverman
Author: Kenneth G. Saag
Author: Juliet E. Compston
Author: Andrea LaCroix
Author: Stephen Gehlbach

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.