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

Predicting fractures in an international cohort using risk factor algorithms without BMD
Predicting fractures in an international cohort using risk factor algorithms without BMD
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.
fracture, risk factors, postmenopausal women, prediction, models
0884-0431
2770-2777
Sambrook, Philip N.
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Flahive, Julie
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Hooven, Fred H.
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Boonen, Steven
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Chapurlat, Roland
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Lindsay, Robert
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Nguyen, Tuan V.
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Diez-Perez, Adolfo
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Pfeilschifter, Johannes
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Greenspan, Ssusan L.
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Hosmer, David
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Netelenbos, J. Coen
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Adachi, Jonathan D.
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Watts, Nelson B.
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Cooper, Cyrus
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Roux, Christian
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Rossini, Maurizio
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Siris, Ethel S.
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Silverman, Stuart
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Saag, Kenneth G.
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Compston, Juliet E.
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LaCroix, Andrea
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Gehlbach, Stephen
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Sambrook, Philip N.
eaf14f9b-45a0-4a24-8cb8-5def7ddf6f1a
Flahive, Julie
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Hooven, Fred H.
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Boonen, Steven
fbfd999d-e425-406c-b66e-ca1b8150497b
Chapurlat, Roland
d9410f8c-4e4a-465b-8fb6-67efaadaad4c
Lindsay, Robert
9508787f-a0b6-4155-95f7-33c57e4f56a0
Nguyen, Tuan V.
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Diez-Perez, Adolfo
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Pfeilschifter, Johannes
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Greenspan, Ssusan L.
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Hosmer, David
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Netelenbos, J. Coen
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Adachi, Jonathan D.
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Watts, Nelson B.
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Cooper, Cyrus
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Roux, Christian
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Rossini, Maurizio
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Siris, Ethel S.
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Silverman, Stuart
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Saag, Kenneth G.
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Compston, Juliet E.
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LaCroix, Andrea
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Gehlbach, Stephen
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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), 2770-2777. (doi:10.1002/jbmr.503). (PMID:21887705)

Record type: Article

Abstract

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.

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More information

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

Identifiers

Local EPrints ID: 201825
URI: http://eprints.soton.ac.uk/id/eprint/201825
ISSN: 0884-0431
PURE UUID: eb398d7f-5682-4597-ace7-cf3f1eacd81b
ORCID for Cyrus Cooper: ORCID iD orcid.org/0000-0003-3510-0709

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Date deposited: 01 Nov 2011 10:46
Last modified: 03 Dec 2019 01:58

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Contributors

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

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