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The Performance of Osteoporosis Self-assessment Tool for Asians (OSTA) in Identifying the Risk of Osteoporosis Among Malaysian Population Aged 40 years and Above

Overview
Journal Arch Osteoporos
Publisher Springer
Date 2019 Nov 30
PMID 31781876
Citations 17
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Abstract

Purpose: Osteoporosis self-assessment tool for Asians (OSTA) is a convenient screening algorithm used widely to identify patients at risk of osteoporosis. Currently, the number of studies validating OSTA in Malaysian population is limited. This study aimed to validate the performance of OSTA in identifying subjects with osteoporosis determined with DXA.

Methods: This cross-sectional study recruited 786 Malaysians in Klang Valley, Malaysia. Their bone health status was assessed by DXA and OSTA. The association and agreement between OSTA and bone mineral density assessment by DXA were determined by Pearson's correlation and Cohen's kappa, respectively. Receiver operating characteristics (ROC) curves were used to determine the sensitivity, specificity, and area under the curve (AUC) for OSTA.

Results: OSTA and DXA showed a fair association in the study (r = 0.382, κ = 0.159, p < 0.001). OSTA (cutoff < - 1) revealed a sensitivity of 32.3%, specificity of 92.3%, and AUC of 0.618 in identifying subjects with suboptimal bone health. The sensitivity of OSTA (cutoff < - 4) in determining subjects at risk of osteoporosis was better among women (sensitivity = 20%) than men (sensitivity = 0%). Modified OSTA cutoff values improved the sensitivity of OSTA in identifying subjects with suboptimal bone health (men = 81.0% at cutoff 3.4, women = 82.8% at cutoff 2.0) and osteoporosis (men = 81.8% at cutoff 1.8, women = 81.3% at cutoff 0.8).

Conclusion: OSTA with its original cutoff values is ineffective in identifying individuals at risk for osteoporosis. Adjusting the cutoff values significantly increases the sensitivity of OSTA, thus highlighting the need to validate this instrument among the local population before using it for osteoporosis screening clinically.

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