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

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.