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Development of a model for identification of individuals with high risk of osteoporosis

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Abstract

Summary

Many developing countries, including Vietnam, lack DXA resources for the diagnosis of osteoporosis, which poses difficulties in the treatment and prevention of osteoporosis at the individual level. We have developed and validated a prediction model for individualized assessment of osteoporosis based on age and body weight for men and women.

Purpose

To estimate the prevalence of osteoporosis and to develop and validate a prediction model for estimating the absolute risk of osteoporosis in the Vietnamese population.

Methods

The study involved 1477 women and 669 men aged 50 years and older, who were recruited from the general population in Ho Chi Minh City (Vietnam). Bone mineral density (BMD) at the femoral neck, total hip, and lumbar spine was measured by DXA (Hologic Horizon). The diagnosis of osteoporosis was based on BMD T-score (T-score ≤ − 2.5) at the femoral neck or lumbar spine which was derived from a published reference range for the Vietnamese population. The logistic regression model was used to develop the prediction model for men and women separately. The bootstrap method was used to evaluate the model performance using 3 indices: the area under the receiver’s operating characteristic curve (AUC), Brier score, and R-squared values.

Results

The prevalence of osteoporosis at any site was 28.3% in women and 15.5% in men. The best predictors of osteoporosis risk were age and body weight. Using these indices, a cut-off of 0.195 for women yielded an AUC of 0.825, Brier score = 0.112, and it explained 33.8% of total variance in risk of osteoporosis between individuals. Similarly, in men, the internal validation with a cut-off of 0.09 yielded good accuracy, with AUC = 0.858, Brier score = 0.040, and R-squared = 30.3%.

Conclusion

We have developed and validated a prediction model for individualized assessment of osteoporosis. In settings without DXA, this model can serve as a useful screening tool to identify high-risk individuals for DXA scan.

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Data availability

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Acknowledgments

We sincerely thank MS Tran Thi Ngoc Trang and Fr Pham Ba Lam for coordinating the recruitment of participants. We also thank the doctors and medical students of the Pham Ngoc Thach University of Medicine for the data collection and clinical measurements.

Code availability

Not applicable.

Funding

This research is funded by Foundation for Science and Technology Development of Ton Duc Thang University (FOSTECT, http://fostect.tdt.edu.vn), Grant number FOSTECT.2014.BR.09, and a grant from the Department of Science and Technology of Ho Chi Minh City.

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Authors and Affiliations

  1. Bone and Muscle Research Group, Ton Duc Thang University, No. 19 Nguyen Huu Tho Street, Tan Phong Ward, District 7, Ho Chi Minh City, 700000, Vietnam

    Lan T. Ho-Pham, Minh C. Doan, Long H. Van & Tuan V. Nguyen

  2. Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Lan T. Ho-Pham & Long H. Van

  3. Department of Internal Medicine, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam

    Minh C. Doan

  4. School of Biomedical Engineering, University of Technology Sydney, Ultimo, Australia

    Tuan V. Nguyen

  5. Bone Biology Division, Garvan Institute of Medical Research, Sydney, Australia

    Tuan V. Nguyen

Authors
  1. Lan T. Ho-Pham
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  2. Minh C. Doan
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  3. Long H. Van
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  4. Tuan V. Nguyen
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Contributions

Conceived and designed the experiments: LHP, TVN. Performed the experiments and data collection: MCD, LHV, LHP. Analyzed the data: TVN, LHP. Wrote the paper and interpretation of data: TVN, LHP.

Corresponding author

Correspondence to Lan T. Ho-Pham.

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The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Ethics approval and consent to participate

The study was approved by the Ethics Committee of the People’s Hospital 115. The study was conducted according to the ethical principles of the Declaration of Helsinki, and all participants gave written informed consent.

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The manuscript does not contain any individual person’s data in any form.

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Ho-Pham, L.T., Doan, M.C., Van, L.H. et al. Development of a model for identification of individuals with high risk of osteoporosis. Arch Osteoporos 15, 111 (2020). https://doi.org/10.1007/s11657-020-00788-3

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