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Novel algorithm generating strategy to identify high fracture risk population using a hybrid intervention threshold

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Abstract

Introduction

The aim of this study was to develop an algorithm to identify high-risk populations of fragility fractures in Taiwan.

Materials and methods

A total of 16,539 postmenopausal women and men (age ≥ 50 years) were identified from the Taiwan Osteoporosis Survey database. Using the Taiwan FRAX® tool, the 10-year probability of major osteoporotic fracture (MOF) and hip fracture (HF) and the individual intervention threshold (IIT) of each participant were calculated. Subjects with either a probability above the IIT or those with MOF ≥ 20% or HF ≥ 9% were included as group A. Subjects with a bone mineral density (BMD) T-score at femoral neck based on healthy subjects of ≤ − 2.5 were included in group B. We tested several cutoff points for MOF and HF so that the number of patients in group A and group B were similar. A novel country-specific hybrid intervention threshold along with an algorithm was generated to identify high fracture risk individuals.

Results

3173 (19.2%) and 3129 (18.9%) participants were categorized to groups A and B, respectively. Participants in group B had a significantly lower BMD (p < 0.001), but clinical characteristics, especially the 10-year probability of MOF (p < 0.001) or HF (p < 0.001), were significantly worse in group A. We found the algorithm generated from the hybrid intervention threshold is practical.

Conclusion

The strategy of generating an algorithm for fracture prevention by novel hybrid intervention threshold is more efficient as it identifies patients with a higher risk of fragility fracture and could be a template for other country-specific policies.

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Acknowledgements

We are indebted to the Taiwanese Osteoporosis Association for authorizing access to and managing the database. Further, we are grateful to the Merck Sharp & Dohme pharmaceutical company (Taiwan) for offering use of the mobile DXA machine during the recruitment period.

Funding

The author (TTC) received funding for this work through a grant (CMRPG8D0651) from Chang Gung Memorial Hospital (https://www.cgmh.org.tw/). This grant was responsible for data collection, input, and processing and for the associated publication fee of this article. The funder had no role in study design, data analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Division of Rheumatology, Allergy and Immunology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, No. 123, Ta-Pei Road, Kaohsiung, 833, Taiwan

    Chung-Yuan Hsu, Shan-Fu Yu, Yu-Jih Su, Wen-Chan Chiu, Ying-Chou Chen, Han-Ming Lai, Jia-Feng Chen, Chi-Hua Ko & Tien-Tsai Cheng

  2. Department of Family Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan

    Chih-Hsing Wu

  3. Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan

    Jung-Fu Chen

Authors
  1. Chung-Yuan Hsu
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  2. Chih-Hsing Wu
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  3. Shan-Fu Yu
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  11. Tien-Tsai Cheng
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Contributions

CYH and TTC conceptualised the study. CYH, SFY, and TTC initiated the study design. TTC is the grant holder. YJS modified the study design. CHW and WCC applied for access to the database and performed data mining. YCC and HML conducted the primary statistical analysis. CYH, JFC, CHK, and JFC discussed the final results and interpreted the data. JFC, CHK, and JFC drew the figures and tables. CYH wrote the manuscript. SFY and TTC revised the article critically. TTC supervised the research group. All the authors contributed to the refinement of the study protocol and approved the final manuscript.

Corresponding author

Correspondence to Tien-Tsai Cheng.

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Conflict of interest

All authors have no conflicts of interest.

Ethics approval

The local Institutional Review Board of Chang Gung Memorial Hospital approved the study (102-1878B).

Informed consent

All participants provided written informed consent before participation.

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Appendix

Appendix

See Table 2 and Fig. 4.

Fig. 4
figure 4

The distribution of 10-year probabilities of both major fractures and hip fractures among participants in the different age groups. X axis, age (years). Y axis, the percentage of individuals with the fracture risk listed in the title for each graph, within each specific age range (%)

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Hsu, CY., Wu, CH., Yu, SF. et al. Novel algorithm generating strategy to identify high fracture risk population using a hybrid intervention threshold. J Bone Miner Metab 38, 213–221 (2020). https://doi.org/10.1007/s00774-019-01046-4

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