A Fracture Risk Assessment Tool for High Resolution Peripheral Quantitative Computed Tomography.
BONE MICROARCHITECTURE
FRACTURE PREDICTION
HIGH RESOLUTION PERIPHERAL QUANTITATIVE COMPUTED TOMOGRAPHY
MACHINE LEARNING
OSTEOPOROSIS
RISK ASSESSMENT
Journal
Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
ISSN: 1523-4681
Titre abrégé: J Bone Miner Res
Pays: United States
ID NLM: 8610640
Informations de publication
Date de publication:
09 2023
09 2023
Historique:
revised:
10
02
2023
received:
13
04
2022
accepted:
21
03
2023
pmc-release:
01
09
2024
medline:
25
9
2023
pubmed:
3
5
2023
entrez:
3
5
2023
Statut:
ppublish
Résumé
Most fracture risk assessment tools use clinical risk factors combined with bone mineral density (BMD) to improve assessment of osteoporosis; however, stratifying fracture risk remains challenging. This study developed a fracture risk assessment tool that uses information about volumetric bone density and three-dimensional structure, obtained using high-resolution peripheral quantitative compute tomography (HR-pQCT), to provide an alternative approach for patient-specific assessment of fracture risk. Using an international prospective cohort of older adults (n = 6802) we developed a tool to predict osteoporotic fracture risk, called μFRAC. The model was constructed using random survival forests, and input predictors included HR-pQCT parameters summarizing BMD and microarchitecture alongside clinical risk factors (sex, age, height, weight, and prior adulthood fracture) and femoral neck areal BMD (FN aBMD). The performance of μFRAC was compared to the Fracture Risk Assessment Tool (FRAX) and a reference model built using FN aBMD and clinical covariates. μFRAC was predictive of osteoporotic fracture (c-index = 0.673, p < 0.001), modestly outperforming FRAX and FN aBMD models (c-index = 0.617 and 0.636, respectively). Removal of FN aBMD and all clinical risk factors, except age, from μFRAC did not significantly impact its performance when estimating 5-year and 10-year fracture risk. The performance of μFRAC improved when only major osteoporotic fractures were considered (c-index = 0.733, p < 0.001). We developed a personalized fracture risk assessment tool based on HR-pQCT that may provide an alternative approach to current clinical methods by leveraging direct measures of bone density and structure. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
Identifiants
pubmed: 37132542
doi: 10.1002/jbmr.4808
pmc: PMC10523935
mid: NIHMS1886053
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1234-1244Subventions
Organisme : NIAMS NIH HHS
ID : R01 AR027065
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01 HC025195
Pays : United States
Organisme : NHLBI NIH HHS
ID : N01HC25195
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR061445
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR041398
Pays : United States
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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