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Comparison of three tools for predicting primary osteoporosis in an elderly male population in Beijing: a cross-sectional study

Authors Zhang X, Lin J, Yang Y, Wu H, Li Y, Yang X, Fei Q

Received 6 July 2017

Accepted for publication 8 December 2017

Published 2 February 2018 Volume 2018:13 Pages 201—209

DOI https://doi.org/10.2147/CIA.S145741

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Amy Norman

Peer reviewer comments 3

Editor who approved publication: Dr Wu


XiaoDong Zhang,1,* JiSheng Lin,1,* Yong Yang,1 Hao Wu,2 Yongjin Li,3 Xiuquan Yang,4 Qi Fei1,*

1Department of Orthopedics, Beijing Friendship Hospital, Capital Medical University, 2Fangzhuang Community Health Service Center, 3Tuanjiehu Community Health Service Center, 4Wangzuo Community Health Service Center, Beijing, People’s Republic of China

*These authors contributed equally to this work

Purpose: In this cross-sectional study, three clinical tools, the Osteoporosis Self-Assessment Tool for Asians (OSTA), Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD), and body mass index (BMI), for predicting primary osteoporosis (OP) were compared and ideal thresholds for omission of screening BMD were proposed in a community-dwelling elderly Han Beijing male population.
Patients and methods: A total of 1,349 community-dwelling elderly Han Beijing males aged ≥50 years were enrolled in this study. All subjects completed a questionnaire and measured BMD by dual-energy X-ray absorptiometry (DXA). Osteoporosis was defined as a T-score of -2.5 SD or lower than that of the average young adult in different diagnostic criteria (lumbar spine [L1–L4], femoral neck, total hip, worst hip, and World Health Organization [WHO]). FRAX without BMD, OSTA, and BMI were assessed for predicting OP by receiver operating characteristic (ROC) curves. Sensitivity, specificity, and areas under the ROC curves (AUCs) were determined. Ideal thresholds for omission of screening BMD were proposed.
Results: The prevalence of OP ranged from 1.8% to 12.8% according to different diagnostic criteria. This study showed that the BMI has highest discriminating ability. The AUC of FRAX without BMD ranged from 0.536 to 0.630, which suggested limiting predictive value for identifying OP in elderly Beijing male. The AUCs of BMI (0.801–0.880) were slightly better than OSTA (0.722–0.874) in predicting OP at all sites. The AUC of BMI to identify OP in worst hip was 0.824, yielding a sensitivity of 84.8% and a specificity of 64.4%. 40% of participants on BMD measurements saved only 0.1%–2.7% missed OP. Compared to OSTA and FRAX without BMD, the BMI got the best predictive value for OP.
Conclusion: BMI may be a simple and effective tool for identifying OP in the elderly male population in Beijing to omit BMD screening reasonably.

Keywords: male, osteoporosis, Osteoporosis Self-Assessment Tool for Asians, OSTA, Fracture Risk Assessment Tool, FRAX, body mass index, BMI

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