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Major osteoporosis fracture prediction in type 2 diabetes: a derivation and comparison study

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Abstract

Summary

The widely recommended fracture prediction tool FRAX was developed based on and for the general population. Although several adjusted FRAX methods were suggested for type 2 diabetes (T2DM), they still need to be evaluated in T2DM cohort.

Introduction

This study was undertaken to develop a prediction model for Chinese diabetes fracture risk (CDFR) and compare its performance with those of FRAX.

Methods

In this retrospective cohort study, 1730 patients with T2DM were enrolled from 2009.08 to 2013.07. Major osteoporotic fractures (MOFs) during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Multivariate Cox regression with backward stepwise selection was used to fit the model. The performances of the CDFR model, FRAX, and adjusted FRAX were compared in the aspects of discrimination and calibration.

Results

6.3% of participants experienced MOF during a median follow-up of 10 years. The final model (CDFR) included 8 predictors: age, gender, previous fracture, insulin use, diabetic peripheral neuropathy (DPN), total cholesterol, triglycerides, and apolipoprotein A. This model had a C statistic of 0.803 (95%CI 0.761–0.844) and calibration χ2 of 4.63 (p = 0.86). The unadjusted FRAX underestimated the MOF risk (calibration χ2 134.5, p < 0.001; observed/predicted ratio 2.62, 95%CI 2.17–3.08), and there was still significant underestimation after diabetes adjustments. Comparing FRAX, the CDFR had a higher AUC, lower calibration χ2, and better reclassification of MOF.

Conclusion

The CDFR model has good performance in 10-year MOF risk prediction in T2DM, especially in patients with insulin use or DPN. Future work is needed to validate our model in external cohort(s).

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Data availability

Some or all data sets generated during and/or analyzed during the present study are not publicly available due to privacy or ethical restrictions but are available from the corresponding author on reasonable request.

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Acknowledgements

The authors thank all the study participants and Ruijin Hospital Computer Center.

Funding

This work was supported by diabetes mellitus research fund program from Shanghai Medical and Health development foundation (DMRFP_II_06 from SHMHDF) and the National Natural Science Foundation of China (No. 82070880).

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Author notes

  1. Xiao-ke Kong and Zhi-yun Zhao contributed equally to this work.

Authors and Affiliations

  1. Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Xiao-ke Kong, Zhi-yun Zhao, Deng Zhang, Rui Xie, Li-hao Sun, Hong-yan Zhao, Guang Ning, Wei-qing Wang, Jian-min Liu & Bei Tao

  2. Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Xiao-ke Kong, Zhi-yun Zhao, Deng Zhang, Rui Xie, Li-hao Sun, Hong-yan Zhao, Guang Ning, Wei-qing Wang, Jian-min Liu & Bei Tao

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  1. Xiao-ke Kong
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Contributions

W.W., B.T., and J.L. contributed to the study conception and design. X.K. and Z.Z. analyzed data and wrote the first manuscript. Material preparation and data collection were performed by X.K., D.Z., and R.X. All authors were involving in revising the manuscript and had final approval of the submitted and published versions. B.T. and J.L. were the guarantors of this work and, as such, had access to all data in this study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Corresponding authors

Correspondence to Wei-qing Wang, Jian-min Liu or Bei Tao.

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This study has been approved by the Ethics Committee of Ruijin Hospital affiliated with Shanghai Jiao-tong University School of Medicine and has been performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

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Kong, Xk., Zhao, Zy., Zhang, D. et al. Major osteoporosis fracture prediction in type 2 diabetes: a derivation and comparison study. Osteoporos Int 33, 1957–1967 (2022). https://doi.org/10.1007/s00198-022-06425-8

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