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Updated: Jul 11, 2025
Fracture Apparatus Design and Protocol Optimization for Closed-stabilized Fractures in Rodents
Published on: August 14, 2018
Optimal fracture prediction thresholds for therapy onset, established from FRAX and Garvan algorithms: a longitudinal
W Pluskiewicz1, A Werner2, M Bach2
1Department and Clinic of Internal Diseases, Diabetology, and Nephrology, Metabolic Bone Diseases Unit, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 3-Maja 13/15 Street, 41-800, Zabrze, Poland. wpluskiewicz@sum.edu.pl.
Abstract:
The study shows that the use of unified cutoff thresholds to identify high fracture risks by two popular calculators-FRAX and Garvan-leads to a significant discrepancy between the prediction of fractures and their actual prevalence over the period of 10 years. On the basis of the ROC analyses, a proposal of differentiated thresholds is presented. They were established at 6% for FRAX major fracture risk, 1.4% for FRAX hip fracture risk, 14.4% for Garvan any fracture risk, and 8.8% for Garvan hip fracture risk.
Purpose/Introduction:
The aim of the study was to verify how much were the tools, designed to predict fracture risks, precise vs. the actual fracture incidence values over a prospective observation.
Methods:
The study group consisted of a population-based postmenopausal sample from the RAC-OST-POL Study. At baseline, there were 978 subjects at the mean age of 66.4 ± 7.8 years and, after a 10-year follow-up, 640 women remained at the mean age of 75.0 ± 6.95 years. At baseline, the fracture risk was established by the FRAX and Garvan tools.
Results:
During the observation period, 190 osteoporotic fractures were identified in 129 subjects. When high-risk fracture cutoff thresholds (of 10% for major/any and 3% for hip fractures) were employed, only 19.59% of major fractures and 50% of hip fractures were identified in the high-risk group. For the Garvan tool, the percentage of correctly predicted fractures for any and hip fractures was 86.05% and 71.43%, respectively. Nevertheless, the fracture prediction by the Garvan tool was associated with the qualification of numerous subjects to the high-risk group, who subsequently did not experience a fracture in the 10-year follow-up period (false-positive prediction). Based on the ROC analyses, new high-risk thresholds were proposed individually for each calculator, improving the sensitivity, specificity, and diagnostic accuracy of these tools. They were established at 6% for FRAX major fracture risk, 1.4% for FRAX hip fracture risk, 14.4% for Garvan any fracture risk, and 8.8% for Garvan hip fracture risk.
Conclusions:
The current prospective study enabled to establish new, optimal thresholds for therapy initiation. Such a modified approach may enable a more accurate identification of treatment requiring patients and, in consequence, reduce the number of new fractures.
