Prediction of imminent fracture risk in Canadian women and men aged 45 years or older: External validation of the Fracture Risk Evaluation Model (FREM)
Prediction of imminent fracture risk in Canadian women and men aged 45 years or older: External validation of the Fracture Risk Evaluation Model (FREM)
Summary
The Fracture Risk Evaluation Model (FREM) identifies individuals at high imminent risk of major osteoporotic fractures. We validated FREM on 74,828 individuals from Manitoba, Canada, and found significant fracture risk stratification for all FREM scores. FREM performed better than age alone but not as well as FRAX® with BMD.
Introduction
The FREM is a tool developed from Danish public health registers (hospital diagnoses) to identify individuals over age 45 years at high imminent risk of major osteoporotic fractures (MOF) and hip fracture (HF). In this study, our aim was to examine the ability of FREM to identify individuals at high imminent fracture risk in women and men from Manitoba, Canada.
Methods
We used the population-based Manitoba Bone Mineral Density (BMD) Program registry, and identified women and men aged 45 years or older undergoing baseline BMD assessment with 2 years of follow-up data. From linked population-based data sources, we constructed FREM scores using up to 10 years of prior healthcare information.
Results
The study population comprised 74,828 subjects, and during the 2 years of observation, 1612 incident MOF and 299 incident HF occurred. We found significant fracture risk stratification for all FREM scores, with AUC estimates of 0.63–0.66 for MOF for both sexes and 0.84 for women and 0.65–0.67 for men for HF. FREM performed better than age alone but not as well as FRAX® with BMD. The inclusion of physician claims data gave slightly better performance than hospitalization data alone. Overall calibration for 1-year MOF prediction was reasonable, but HF prediction was overestimated.
Conclusion
In conclusion, the FREM algorithm shows significant fracture risk stratification when applied to an independent clinical population from Manitoba, Canada. Overall calibration for MOF prediction was good, but hip fracture risk was systematically overestimated indicating the need for recalibration.
Automated risk calculation, External validation, Osteoporotic fractures, Prediction models
Moller, Soren
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Skjodt, M.K.
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Yan, Lin
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Abrahamsen, Bo
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Lix, Lisa M.
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McCloskey, Eugene V.
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Johansson, Helena
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Harvey, Nicholas
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Kanis, John A.
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Rubin, Katrine Hass
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Leslie, William D.
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1 October 2021
Moller, Soren
6a098fd3-f9b6-4112-a0d9-34ffbf1ec970
Skjodt, M.K.
c57ef821-0d62-4d91-909b-4f32a9f9299d
Yan, Lin
4065ffb6-49ad-45b8-be72-72013cbc3d9b
Abrahamsen, Bo
ea627e06-482e-479f-8631-5b0f3aec5d13
Lix, Lisa M.
2fb61783-047d-4a4b-a45d-e09ac0763a7b
McCloskey, Eugene V.
2f057a16-3d4e-4597-80c7-6ce47f969c78
Johansson, Helena
04f12338-4dd1-437b-b9bc-e0884130c215
Harvey, Nicholas
ce487fb4-d360-4aac-9d17-9466d6cba145
Kanis, John A.
f1621d8d-8afb-4d97-9679-2165d88a344d
Rubin, Katrine Hass
a582f4b8-fcd8-4801-ab3d-bc4ed4e47bfb
Leslie, William D.
5b2dd5d6-4569-40a3-a9b1-95152d11e4f1
Moller, Soren, Skjodt, M.K., Yan, Lin, Abrahamsen, Bo, Lix, Lisa M., McCloskey, Eugene V., Johansson, Helena, Harvey, Nicholas, Kanis, John A., Rubin, Katrine Hass and Leslie, William D.
(2021)
Prediction of imminent fracture risk in Canadian women and men aged 45 years or older: External validation of the Fracture Risk Evaluation Model (FREM).
Osteoporosis International.
(doi:10.1007/s00198-021-06165-1).
Abstract
Summary
The Fracture Risk Evaluation Model (FREM) identifies individuals at high imminent risk of major osteoporotic fractures. We validated FREM on 74,828 individuals from Manitoba, Canada, and found significant fracture risk stratification for all FREM scores. FREM performed better than age alone but not as well as FRAX® with BMD.
Introduction
The FREM is a tool developed from Danish public health registers (hospital diagnoses) to identify individuals over age 45 years at high imminent risk of major osteoporotic fractures (MOF) and hip fracture (HF). In this study, our aim was to examine the ability of FREM to identify individuals at high imminent fracture risk in women and men from Manitoba, Canada.
Methods
We used the population-based Manitoba Bone Mineral Density (BMD) Program registry, and identified women and men aged 45 years or older undergoing baseline BMD assessment with 2 years of follow-up data. From linked population-based data sources, we constructed FREM scores using up to 10 years of prior healthcare information.
Results
The study population comprised 74,828 subjects, and during the 2 years of observation, 1612 incident MOF and 299 incident HF occurred. We found significant fracture risk stratification for all FREM scores, with AUC estimates of 0.63–0.66 for MOF for both sexes and 0.84 for women and 0.65–0.67 for men for HF. FREM performed better than age alone but not as well as FRAX® with BMD. The inclusion of physician claims data gave slightly better performance than hospitalization data alone. Overall calibration for 1-year MOF prediction was reasonable, but HF prediction was overestimated.
Conclusion
In conclusion, the FREM algorithm shows significant fracture risk stratification when applied to an independent clinical population from Manitoba, Canada. Overall calibration for MOF prediction was good, but hip fracture risk was systematically overestimated indicating the need for recalibration.
Text
FREM validation in Canada resubmission final
- Accepted Manuscript
More information
Accepted/In Press date: 17 September 2021
e-pub ahead of print date: 1 October 2021
Published date: 1 October 2021
Additional Information:
Funding Information:
LML is supported by a Tier I Canada Research Chair.
Funding Information:
Michael K. Skjødt: educational grant, UCB; institutional research grant, UCB/Amgen. Eugene McCloskey: nothing to declare for the context of this paper, but numerous ad hoc consultancies/speaking honoraria and/or research funding from Amgen, Bayer, General Electric, GSK, Fresenius Kabi, Hologic, Lilly, Merck Research Labs, Novartis, Novo Nordisk, Nycomed, Ono, Pfizer, ProStrakan, Roche, Sanofi-Aventis, Servier, Tethys, UCB, and Warner-Chilcott. Nicholas Harvey: nothing to declare for the context of this paper, but has received consultancy/lecture fees/honoraria/grant funding from the Alliance for Better Bone Health, Amgen, MSD, Eli Lilly, Servier, Shire, UCB, Consilient Healthcare, Radius Health, Kyowa Kirin, and Internis Pharma. Bo Abrahamsen: institutional research contracts with Novartis, UCB, Kyowa-Kirin. Fees or honoraria from UCB, Amgen, Pharmacosmos. John Kanis: Professor Kanis led the team that developed FRAX as director of the WHO Collaborating Centre for Metabolic Bone Diseases; he has no financial interest in FRAX. William Leslie, Lisa Lix, Lin Yan, Helena Johansson, Sören Möller, and Katrine Hass Rubin: No conflicts of interest.
Publisher Copyright:
© 2021, International Osteoporosis Foundation and National Osteoporosis Foundation.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Keywords:
Automated risk calculation, External validation, Osteoporotic fractures, Prediction models
Identifiers
Local EPrints ID: 451952
URI: http://eprints.soton.ac.uk/id/eprint/451952
ISSN: 0937-941X
PURE UUID: 8435ab15-8ecc-439e-bc5a-e42ed7849eb8
Catalogue record
Date deposited: 04 Nov 2021 17:32
Last modified: 17 Mar 2024 06:53
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Contributors
Author:
Soren Moller
Author:
M.K. Skjodt
Author:
Lin Yan
Author:
Bo Abrahamsen
Author:
Lisa M. Lix
Author:
Eugene V. McCloskey
Author:
Helena Johansson
Author:
John A. Kanis
Author:
Katrine Hass Rubin
Author:
William D. Leslie
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