Predicting imminent fractures in patients with a recent fracture or starting oral bisphosphonate therapy: development and international validation of prognostic models
Predicting imminent fractures in patients with a recent fracture or starting oral bisphosphonate therapy: development and international validation of prognostic models
The availability of anti-osteoporosis medications with rapid onset and high potency requires tools to identify patients at high imminent fracture risk (IFR). There are few tools that predict a patient's IFR. We aimed to develop and validate tools for patients with a recent fracture and for patients initiating oral bisphosphonate therapy. Models for two separate cohorts, those with incident fragility fracture (IFx) and with incident oral bisphosphonate prescription (OBP), were developed in primary care records from Spain (SIDIAP database), UK (Clinical Practice Research Datalink GOLD), and Denmark (Danish Health Registries). Separate models were developed for hip, major, and any fracture outcomes. Only variables present in all databases were included in Lasso regression models for the development and logistic regression models for external validation. Discrimination was tested using area under curve (AUC) and calibration was assessed using observed versus predicted risk plots stratified by age, sex, and previous fracture history. The development analyses included 35,526 individuals in the IFx and 41,401 in the OBP cohorts, with 671,094 in IFx and 330,256 in OBP for the validation analyses. Both the IFx and OBP models demonstrated similarly good performance for hip fracture at 1 year (with AUCs of 0.79 [95% CI 0.75 to 0.82] and 0.87 [0.83 to 0.91] in Spain, 0.71 [0.71 to 0.72] and 0.73 [0.72 to 0.74] in the UK, and 0.70 [0.70 to 0.70] and 0.69 [0.68 to 0.70] in Denmark), and lower discrimination for major osteoporotic and any fracture sites. Calibration was good across all three countries. Discrimination and calibration for the 2-year models was similar. The proposed IFR prediction models could be used to identify more precisely patients at high imminent risk of fracture and inform anti-osteoporosis treatment selection. The freely available model parameters permit local validation and implementation.
ANTIRESORPTIVE, FRACTURE PREVENTION, FRACTURE RISK ASSESSMENT, OSTEOPOROSIS, PROGNOSTIC MODEL
2162-2176
Khalid, Sara
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Moncusi, Marta Pineda
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El-Hussein, Leena
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Delmestri, Antonella
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Ernst, Martin
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Smith, Christopher
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Libanati, Cesar
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Toth, Emese
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Javaid, Muhammad K.
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Cooper, Cyrus
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Abrahamsen, Bo
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Prieto-Alhambra, Daniel
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November 2021
Khalid, Sara
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Moncusi, Marta Pineda
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El-Hussein, Leena
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Delmestri, Antonella
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Ernst, Martin
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Smith, Christopher
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Libanati, Cesar
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Toth, Emese
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Javaid, Muhammad K.
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Cooper, Cyrus
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Abrahamsen, Bo
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Prieto-Alhambra, Daniel
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Khalid, Sara, Moncusi, Marta Pineda, El-Hussein, Leena, Delmestri, Antonella, Ernst, Martin, Smith, Christopher, Libanati, Cesar, Toth, Emese, Javaid, Muhammad K., Cooper, Cyrus, Abrahamsen, Bo and Prieto-Alhambra, Daniel
(2021)
Predicting imminent fractures in patients with a recent fracture or starting oral bisphosphonate therapy: development and international validation of prognostic models.
Journal of Bone and Mineral Research, 36 (11), .
(doi:10.1002/jbmr.4414).
Abstract
The availability of anti-osteoporosis medications with rapid onset and high potency requires tools to identify patients at high imminent fracture risk (IFR). There are few tools that predict a patient's IFR. We aimed to develop and validate tools for patients with a recent fracture and for patients initiating oral bisphosphonate therapy. Models for two separate cohorts, those with incident fragility fracture (IFx) and with incident oral bisphosphonate prescription (OBP), were developed in primary care records from Spain (SIDIAP database), UK (Clinical Practice Research Datalink GOLD), and Denmark (Danish Health Registries). Separate models were developed for hip, major, and any fracture outcomes. Only variables present in all databases were included in Lasso regression models for the development and logistic regression models for external validation. Discrimination was tested using area under curve (AUC) and calibration was assessed using observed versus predicted risk plots stratified by age, sex, and previous fracture history. The development analyses included 35,526 individuals in the IFx and 41,401 in the OBP cohorts, with 671,094 in IFx and 330,256 in OBP for the validation analyses. Both the IFx and OBP models demonstrated similarly good performance for hip fracture at 1 year (with AUCs of 0.79 [95% CI 0.75 to 0.82] and 0.87 [0.83 to 0.91] in Spain, 0.71 [0.71 to 0.72] and 0.73 [0.72 to 0.74] in the UK, and 0.70 [0.70 to 0.70] and 0.69 [0.68 to 0.70] in Denmark), and lower discrimination for major osteoporotic and any fracture sites. Calibration was good across all three countries. Discrimination and calibration for the 2-year models was similar. The proposed IFR prediction models could be used to identify more precisely patients at high imminent risk of fracture and inform anti-osteoporosis treatment selection. The freely available model parameters permit local validation and implementation.
Text
Khalid JBMR
- Accepted Manuscript
More information
Accepted/In Press date: 1 August 2021
Published date: November 2021
Additional Information:
Funding Information:
SK, MPM, LE, AD, and CS have no conflicts to declare. ME reports institutional grants from UCB during the conduct of the study. CL reports being employed by UCB Pharma. ET is an employee of UCB Pharma, who sponsored the study. MKJ reports personal fees from Amgen, Consilient Health, Kyowa Kirin Hakin, UCB, and Abbvie and grant support from Kyowa Kirin Hakin and Amgen outside the submitted work. CC reports personal fees from Alliance for Better Bone Health, Amgen, Eli Lilly, GSK, Medtronic, Merck, Novartis, Pfizer, Roche, Servier, Takeda, and UCB. BA reports grants from UCB during the conduct of the study and personal fees from UCB, personal fees from Amgen, grants from Novartis, personal fees from Eli Lilly, personal fees from Kyowa Kirin, grants from Kyowa Kirin, and personal fees from Pharmacosmos, outside the submitted work. DPA reports grants and other from AMGEN; grants, non‐financial support, and other from UCB Biopharma; and grants from Les Laboratoires Servier, outside the submitted work. In addition, Janssen, on behalf of IMI‐funded EHDEN and EMIF consortiums, and Synapse Management Partners have supported training programs organized by DPA's department and open for external participants.
Funding Information:
The authors acknowledge Paloma O'Dogherty for project management; CPRD, SIDIAP, and Statistics Denmark for their support; and UCB Pharma for funding this study. The study was sponsored by UCB Pharma.
Publisher Copyright:
© 2021 American Society for Bone and Mineral Research (ASBMR).
Keywords:
ANTIRESORPTIVE, FRACTURE PREVENTION, FRACTURE RISK ASSESSMENT, OSTEOPOROSIS, PROGNOSTIC MODEL
Identifiers
Local EPrints ID: 450790
URI: http://eprints.soton.ac.uk/id/eprint/450790
ISSN: 0884-0431
PURE UUID: e6eb7b0a-9f42-4944-b8f4-6e5baf346ea7
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Date deposited: 11 Aug 2021 16:32
Last modified: 18 Mar 2024 05:03
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Contributors
Author:
Sara Khalid
Author:
Marta Pineda Moncusi
Author:
Leena El-Hussein
Author:
Antonella Delmestri
Author:
Martin Ernst
Author:
Christopher Smith
Author:
Cesar Libanati
Author:
Emese Toth
Author:
Muhammad K. Javaid
Author:
Bo Abrahamsen
Author:
Daniel Prieto-Alhambra
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