Fracture risk prediction and the decision to treat low bone density

Stuckey, Bronwyn; Magraith, Karen; Opie, Nicole; Zhu, Kun

doi:10.31128/ajgp-04-20-5363

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…With the growth of the global population and the aging problem, the incidence of osteoporosis among the elderly population has become a global public health issue. Fragility fractures caused by osteoporosis, especially vertebral fractures, are associated with high mortality and disability rates [3]. However, the majority of osteoporosis patients are asymptomatic at an early stage, so early diagnosis and interventions through medical imaging examinations are critical to prevent the occurrence of complications [4].…”

Section: Introductionmentioning

confidence: 99%

Diagnostic Accuracy of Dual-Energy CT Material Decomposition Technique for Assessing Bone Status Compared with Quantitative Computed Tomography

Tong

et al. 2023

Diagnostics

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Purpose: The purpose of this study was to evaluate the diagnostic accuracy when using various base material pairs (BMPs) in dual-energy computed tomography (DECT), and to establish corresponding diagnostic standards for assessing bone status through comparison with quantitative computed tomography (QCT). Methods: This prospective study enrolled a total of 469 patients who underwent both non-enhanced chest CT scans under conventional kVp and abdominal DECT. The bone densities of hydroxyapatite (water), hydroxyapatite (fat), hydroxyapatite (blood), calcium (water), and calcium (fat) (DHAP (water), DHAP (fat), DHAP (blood), DCa (water), and DCa (fat)) in the trabecular bone of vertebral bodies (T11–L1) were measured, along with bone mineral density (BMD) via QCT. Intraclass correlation coefficient (ICC) analysis was used to assess the agreement of the measurements. Spearman’s correlation test was performed to analyze the relationship between the DECT- and QCT-derived BMD. Receiver operator characteristic (ROC) curves were generated to determine the optimal diagnostic thresholds of various BMPs for diagnosing osteopenia and osteoporosis. Results: A total of 1371 vertebral bodies were measured, and QCT identified 393 with osteoporosis and 442 with osteopenia. Strong correlations were observed between DHAP (water), DHAP (fat), DHAP (blood), DCa (water), and DCa (fat) and the QCT-derived BMD. DHAP (water) showed the best predictive capability for osteopenia and osteoporosis. The area under the ROC curve, sensitivity, and specificity for identifying osteopenia were 0.956, 86.88%, and 88.91% with DHAP (water) ≤ 107.4 mg/cm3, respectively. The corresponding values for identifying osteoporosis were 0.999, 99.24%, and 99.53% with DHAP (water) ≤ 89.62 mg/cm3, respectively. Conclusions: Bone density measurement using various BMPs in DECT enables the quantification of vertebral BMD and the diagnosis of osteoporosis, with DHAP (water) having the highest diagnostic accuracy.

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Section: Introductionmentioning

confidence: 99%

Diagnostic Accuracy of Dual-Energy CT Material Decomposition Technique for Assessing Bone Status Compared with Quantitative Computed Tomography

Tong

et al. 2023

Diagnostics

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“…However, the Garvan model's overestimation has no negative clinical impact since high-risk individuals would be recommended for treatment regardless. There is evidence suggesting that the Garvan model's predicted risk is consistent with the clinical decision-making [ 30 , 31 ].…”

Section: Discussionmentioning

confidence: 99%

BONEcheck: A digital tool for personalized bone health assessment

Nguyen,

Ho-Le,

Pham

et al. 2023

Osteoporosis and Sarcopenia

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Section: Discussionmentioning

confidence: 99%

BONEcheck: a digital tool for personalized bone health assessment

Nguyen,

Ho-Le,

Pham

et al. 2023

Preprint

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Background and Aim: Osteoporotic fracture is a significant public health burden associated with increased mortality risk and substantial healthcare costs. Accurate and early identification of high-risk individuals and mitigation of their risks is a core part of the treatment and prevention of fractures. We aimed to introduce a digital tool called 'BONEcheck' for personalized bone health assessment. Methods: The development of BONEcheck primarily utilized data from the prospective population-based Dubbo Osteoporosis Epidemiology Study and the Danish Nationwide Registry. BONEcheck has 3 modules: input data, risk estimates, and risk context. Input variables include age, gender, prior fracture, fall incidence, bone mineral density (BMD), comorbidities, and genetic variants associated with BMD. By utilizing published methodologies, BONEcheck generates output related to the likelihood of fracture and its associated outcomes. The vocabulary utilized to convey risk estimation and management is tailored to individuals with a reading proficiency at level 8 or above. Results: The tool is designed for men and women aged 50 years and older who either have or have not sustained a fracture. Based on the input variables, BONEcheck estimates the probability of any fragility and hip fracture within 5 years, skeletal age, subsequent fracture, genetic risk score, and recommended interval for repeating BMD. The probability of fracture is shown in both numeric and human icon array formats. The risk is also presented in the context of treatment and management options based on Australian guidelines. Skeletal age was estimated as the sum of chronological age and years of life lost due to a fracture or exposure to risk factors that elevate mortality risk. In its entirety, BONEcheck is a system of algorithms translated into a single platform for personalized osteoporosis and fracture risk assessment. Conclusions: BONEcheck is a new system of algorithms that aims to offer not only fracture risk probability but also contextualize the efficacy of anti-fracture measures concerning the survival benefits. The tool can enable doctors and patients to engage in well-informed discussions and make decisions based on the patient's risk profile. Public access to BONEcheck is available via https://bonecheck.org and in Apple Store (iOS) and Google Play (Android).

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Fracture risk prediction and the decision to treat low bone density

Cited by 6 publications

References 13 publications

Diagnostic Accuracy of Dual-Energy CT Material Decomposition Technique for Assessing Bone Status Compared with Quantitative Computed Tomography

Diagnostic Accuracy of Dual-Energy CT Material Decomposition Technique for Assessing Bone Status Compared with Quantitative Computed Tomography

BONEcheck: A digital tool for personalized bone health assessment

BONEcheck: a digital tool for personalized bone health assessment

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