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Validation of Ten Osteoporosis Screening Tools in Rural Communities of Taiwan.
Calcified Tissue International 2024 August 18
Patients with osteoporosis are at risk of fractures, which can lead to immobility and reduced quality of life. Early diagnosis and treatment are crucial for preventing fractures, but many patients are not diagnosed until after a fracture has occurred. This study aimed to evaluate the performance of 10 osteoporosis screening tools (OSTs) in rural communities of Taiwan. In this prospective study, a total of 567 senior citizens from rural communities underwent bone mineral density (BMD) measurement using dual-energy X-ray absorptiometry (DXA) and ten OSTs were administered. Discrimination analysis was performed using the area under the receiver operating characteristic curve (AUROC). Primary outcomes included area under curve (AUC) value, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The DXA examination revealed that 63.0% of females and 22.4% of males had osteoporosis. Among females, Osteoporosis Index of Risk (OSIRIS) and Osteoporosis Self-Assessment Tool for Asians (OSTA) presented the best AUC value with 0.71 (0.66-0.76) and 0.70 (0.66-0.75), respectively. Among males, BWC had the best AUC value of 0.77 (0.67-0.86), followed by OSTA, Simple Calculated Osteoporosis Risk Estimation (SCORE), and OSIRIS. OSTA and OSIRIS showed acceptable performance in both genders. The specificity of Fracture Risk Assessment Tool (FRAX-H), SCORE, National Osteoporosis Foundation Score, OSIRIS, Osteoporosis Risk Assessment Instrument, Age, Bulk, One or Never Estrogen (ABONE), and Body weight criteria increased in both genders after applying the optimum cut-off. Considering it high AUC and simplicity of use, OSTA appeared to be the recommended tool for seniors of both genders among the ten OSTs. This study provides a viable reference for future development of OSTs in Taiwan. Further adjustment according to epidemiological data and risk factors is recommended while applying OSTs to different cohorts.
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