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Adjusting FRAX Estimates of Fracture Probability Based on a Positive Vertebral Fracture Assessment

Adjusting FRAX Estimates of Fracture Probability Based on a Positive Vertebral Fracture Assessment
Adjusting FRAX Estimates of Fracture Probability Based on a Positive Vertebral Fracture Assessment

IMPORTANCE: FRAX is the most widely used and validated fracture risk prediction tool worldwide. Vertebral fractures, which are an indicator of subsequent osteoporotic fractures, can be identified using dual-energy x-ray absorptiometry (DXA) vertebral fracture assessment (VFA).

OBJECTIVE: To assess the calibration of FRAX and develop a simple method for improving FRAX-predicted fracture probability in the presence of VFA-identified fracture.

DESIGN, SETTING, AND PARTICIPANTS: This prognostic study analyzed the DXA and VFA results of all individuals who underwent a VFA between March 31, 2010, and March 31, 2018, who were included in the Manitoba Bone Mineral Density Registry. These individuals were randomly assigned to either the development cohort or validation cohort. A modified algorithm-based qualitative approach was used by expert readers to code VFAs as positive (≥1 vertebral fractures detected) or negative (0 vertebral fracture detected). Statistical analysis was conducted from August 7, 2022, to May 22, 2023.

EXPOSURES: FRAX scores for major osteoporotic fracture (MOF) and hip fracture were calculated with or without VFA results.

MAIN OUTCOMES AND MEASURES: Incident fractures and death were ascertained using linked population-based health care provincial data. Cumulative incidence curves for MOF and hip fracture were constructed, including competing mortality, to predict the 10-year observed risk of fracture. The observed probability was compared with FRAX-predicted fracture probability with and without VFA results and recalibrated FRAX from derived multipliers.

RESULTS: The full cohort of 11 766 individuals was randomly allocated to the development cohort (n = 7854; 7349 females [93.6%]; mean [SD] age, 75.7 [6.8] years) or the validation cohort (n = 3912; 3713 females [94.9%]; mean [SD] age, 75.5 [6.9] years). Over a mean (SD) observation time of 3.8 (2.3) years, with the longest observation at 7.5 years, FRAX was well calibrated in subgroups with negative VFA results. For individuals without a prior clinical fracture but with a positive VFA result, the 10-year FRAX-predicted MOF probability was 16.3% (95% CI, 15.7%-16.8%) without VFA information and 23.4% (95% CI, 22.7%-24.1%) with VFA information. The observed 10-year probabilities were 26.9% (95% CI, 26.0%-27.8%) and 11.2% (95% CI, 10.3%-12.1%), respectively, resulting in recalibration multipliers of 1.15 (95% CI, 0.87-1.43) for MOF and 1.31 (95% CI, 0.75-1.87) for hip fracture. For individuals with a prior clinical fracture and a positive VFA result, the 10-year FRAX-predicted probabilities were 25.0% (95% CI, 24.2%-25.7%) for MOF and 9.3% (95% CI, 8.7%-10.0%) for hip fracture. The observed 10-year probabilities were 38.1% (95% CI, 37.0%-39.1%) for MOF and 16.4% (95% CI, 15.4%-17.4%) for hip fracture, resulting in a recalibration multiplier of 1.53 (95% CI, 1.10-1.96) for MOF and 1.76 (95% CI, 1.17-2.35) for hip fracture. Good calibration (>0.90) was confirmed using the derived multipliers in the validation cohort.

CONCLUSIONS AND RELEVANCE: Results of this prognostic study suggest that FRAX underestimated fracture risk in patients with VFA-identified fractures. Simple multipliers could recover FRAX calibration in individuals with VFA-identified fractures.

e2329253
Ye, Carrie
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Leslie, William D
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Morin, Suzanne N
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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 C
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Lorentzon, Mattias
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Kanis, John A
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Ye, Carrie
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Leslie, William D
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Morin, Suzanne N
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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 C
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Lorentzon, Mattias
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Kanis, John A
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Ye, Carrie, Leslie, William D, Morin, Suzanne N, Lix, Lisa M, McCloskey, Eugene V, Johansson, Helena, Harvey, Nicholas C, Lorentzon, Mattias and Kanis, John A (2023) Adjusting FRAX Estimates of Fracture Probability Based on a Positive Vertebral Fracture Assessment. JAMA Network Open, 6 (8), e2329253, [e2329253]. (doi:10.1001/jamanetworkopen.2023.29253).

Record type: Article

Abstract

IMPORTANCE: FRAX is the most widely used and validated fracture risk prediction tool worldwide. Vertebral fractures, which are an indicator of subsequent osteoporotic fractures, can be identified using dual-energy x-ray absorptiometry (DXA) vertebral fracture assessment (VFA).

OBJECTIVE: To assess the calibration of FRAX and develop a simple method for improving FRAX-predicted fracture probability in the presence of VFA-identified fracture.

DESIGN, SETTING, AND PARTICIPANTS: This prognostic study analyzed the DXA and VFA results of all individuals who underwent a VFA between March 31, 2010, and March 31, 2018, who were included in the Manitoba Bone Mineral Density Registry. These individuals were randomly assigned to either the development cohort or validation cohort. A modified algorithm-based qualitative approach was used by expert readers to code VFAs as positive (≥1 vertebral fractures detected) or negative (0 vertebral fracture detected). Statistical analysis was conducted from August 7, 2022, to May 22, 2023.

EXPOSURES: FRAX scores for major osteoporotic fracture (MOF) and hip fracture were calculated with or without VFA results.

MAIN OUTCOMES AND MEASURES: Incident fractures and death were ascertained using linked population-based health care provincial data. Cumulative incidence curves for MOF and hip fracture were constructed, including competing mortality, to predict the 10-year observed risk of fracture. The observed probability was compared with FRAX-predicted fracture probability with and without VFA results and recalibrated FRAX from derived multipliers.

RESULTS: The full cohort of 11 766 individuals was randomly allocated to the development cohort (n = 7854; 7349 females [93.6%]; mean [SD] age, 75.7 [6.8] years) or the validation cohort (n = 3912; 3713 females [94.9%]; mean [SD] age, 75.5 [6.9] years). Over a mean (SD) observation time of 3.8 (2.3) years, with the longest observation at 7.5 years, FRAX was well calibrated in subgroups with negative VFA results. For individuals without a prior clinical fracture but with a positive VFA result, the 10-year FRAX-predicted MOF probability was 16.3% (95% CI, 15.7%-16.8%) without VFA information and 23.4% (95% CI, 22.7%-24.1%) with VFA information. The observed 10-year probabilities were 26.9% (95% CI, 26.0%-27.8%) and 11.2% (95% CI, 10.3%-12.1%), respectively, resulting in recalibration multipliers of 1.15 (95% CI, 0.87-1.43) for MOF and 1.31 (95% CI, 0.75-1.87) for hip fracture. For individuals with a prior clinical fracture and a positive VFA result, the 10-year FRAX-predicted probabilities were 25.0% (95% CI, 24.2%-25.7%) for MOF and 9.3% (95% CI, 8.7%-10.0%) for hip fracture. The observed 10-year probabilities were 38.1% (95% CI, 37.0%-39.1%) for MOF and 16.4% (95% CI, 15.4%-17.4%) for hip fracture, resulting in a recalibration multiplier of 1.53 (95% CI, 1.10-1.96) for MOF and 1.76 (95% CI, 1.17-2.35) for hip fracture. Good calibration (>0.90) was confirmed using the derived multipliers in the validation cohort.

CONCLUSIONS AND RELEVANCE: Results of this prognostic study suggest that FRAX underestimated fracture risk in patients with VFA-identified fractures. Simple multipliers could recover FRAX calibration in individuals with VFA-identified fractures.

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Accepted/In Press date: 4 July 2023
e-pub ahead of print date: 17 August 2023
Published date: 17 August 2023
Additional Information: Publisher Copyright: © 2023 American Medical Association. All rights reserved.

Identifiers

Local EPrints ID: 481262
URI: http://eprints.soton.ac.uk/id/eprint/481262
PURE UUID: 1acdff24-f15c-4cb5-b176-df795dc4bb8b
ORCID for Nicholas C Harvey: ORCID iD orcid.org/0000-0002-8194-2512

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Date deposited: 21 Aug 2023 16:58
Last modified: 18 Mar 2024 02:59

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Contributors

Author: Carrie Ye
Author: William D Leslie
Author: Suzanne N Morin
Author: Lisa M Lix
Author: Eugene V McCloskey
Author: Helena Johansson
Author: Mattias Lorentzon
Author: John A Kanis

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