Thoracic vertebral bone mineral density measured by quantitative computed tomography is associated with fracture risk in lung cancer screening populations: a prospective cohort study.
Chest low-dose computed tomography (LDCT) is extensively utilized for lung cancer screening, offering a concurrent opportunity to assess thoracic vertebral bone mineral density (BMD) using quantitative computed tomography (QCT). Nonetheless, the value of thoracic BMD (TBMD) in estimating the risk of fractures within this population remains underexplored.
We sought to assess the association between fractures and QCT-based TBMD derived from chest LDCT in a lung cancer screening population.
A prospective study was conducted involving 546 adults aged 40 to 74 years who were enrolled in a lung cancer screening program between 2017 and 2021. TBMD and lumbar BMD (LBMD) were assessed from chest LDCT scans using QCT. Self-reported incident fractures were recorded over a 3-year period, and vertebral fractures (VFs) were evaluated on follow-up CT. Binary logistic regression models and area under the curve (AUC) analyses were utilized to develop and compare the models incorporating TBMD, LBMD, and FRAX for estimating fracture risk.
Out of the total participants, 323 individuals (59.2%) were found to have VFs, while 16 individuals (2.9%) reported experiencing incident fractures over a period of three years. In unadjusted logistic regression analyses, TBMD was associated with CT-detected VFs (OR = 0.955; 95% CI: 0.947 - 0.963). After adjusting for age and current smoking, TBMD remained associated with CT-detected VFs (OR = 0.953; 95% CI: 0.944 - 0.962). The optimal TBMD threshold for CT-detected VFs was 124 mg/cm3, with a sensitivity of 79.3%, a specificity of 70.9% and AUC of 0.823. Notably, self-reported incident fractures were significantly associated with TBMD (OR = 0.982; 95% CI: 0.965-0.999), independent of adjustment for excessive alcohol consumption (OR = 0.982; 95% CI: 0.965-0.999). The optimal TBMD threshold for self-reported incident fractures was determined to be 94 mg/cm3, with a sensitivity of 62.5%, a specificity of 77.0%, and an AUC of 0.678.
QCT-based TBMD derived from LDCT scans might be a feasible and effective tool for identifying individuals with VFs and an elevated risk of incident fracture, without additional radiation exposure in lung cancer screening populations.
We sought to assess the association between fractures and QCT-based TBMD derived from chest LDCT in a lung cancer screening population.
A prospective study was conducted involving 546 adults aged 40 to 74 years who were enrolled in a lung cancer screening program between 2017 and 2021. TBMD and lumbar BMD (LBMD) were assessed from chest LDCT scans using QCT. Self-reported incident fractures were recorded over a 3-year period, and vertebral fractures (VFs) were evaluated on follow-up CT. Binary logistic regression models and area under the curve (AUC) analyses were utilized to develop and compare the models incorporating TBMD, LBMD, and FRAX for estimating fracture risk.
Out of the total participants, 323 individuals (59.2%) were found to have VFs, while 16 individuals (2.9%) reported experiencing incident fractures over a period of three years. In unadjusted logistic regression analyses, TBMD was associated with CT-detected VFs (OR = 0.955; 95% CI: 0.947 - 0.963). After adjusting for age and current smoking, TBMD remained associated with CT-detected VFs (OR = 0.953; 95% CI: 0.944 - 0.962). The optimal TBMD threshold for CT-detected VFs was 124 mg/cm3, with a sensitivity of 79.3%, a specificity of 70.9% and AUC of 0.823. Notably, self-reported incident fractures were significantly associated with TBMD (OR = 0.982; 95% CI: 0.965-0.999), independent of adjustment for excessive alcohol consumption (OR = 0.982; 95% CI: 0.965-0.999). The optimal TBMD threshold for self-reported incident fractures was determined to be 94 mg/cm3, with a sensitivity of 62.5%, a specificity of 77.0%, and an AUC of 0.678.
QCT-based TBMD derived from LDCT scans might be a feasible and effective tool for identifying individuals with VFs and an elevated risk of incident fracture, without additional radiation exposure in lung cancer screening populations.
Authors
Jiang Jiang, Huang Huang, Wu Wu, Liu Liu, Liang Liang, Li Li, Ye Ye, Wang Wang
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