PDF(Pubmed)
Abstract：
In the longitudinal, retrospective study, the ability of the FRAX, Garvan, and POL-RISK algorithms to predict osteoporotic fractures was compared in a group of 457 women. Using the rigid threshold of 10% showed a significant discrepancy in sensitivity and specificity of all tools. New thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds allow for improving the diagnostic accuracy of all three calculators.
BACKGROUND: The aim of the longitudinal, retrospective study was to compare three tools designed to assess fracture risk: FRAX, Garvan, and POL-RISK in their prediction of fracture incidence.
METHODS: The study group consisted of 457 postmenopausal women with a mean age of 64.21 ± 5.94 years from the Gliwice Osteoporosis (GO) Study. Comprehensive data on clinical factors related to fractures were collected for all participants. Bone densitometry was performed at the proximal femur using the Prodigy device (GE, USA). Fracture risk was established using the FRAX, Garvan, and POL-RISK algorithms. Data on the incidence of osteoporotic fractures were collected over the last 10 years.
RESULTS: During the period of observation 72, osteoporotic fractures occurred in 63 subjects. For a preliminary comparison of the predictive value of analyzed diagnostic tools, the fracture risk threshold of 10% was used. For FRAX, the fracture probability exceeding 10% was observed only in 11 subjects who experienced fractures; thus, the fracture was properly predicted only in 22.9% of women. For Garvan, the respective value was 90.5%, and for POL-RISK, it was 98.4%. That gave a very low true positive value for FRAX and a very high false positive value for Garvan and POL-RISK. Based on ROC curves, new thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds improve the diagnostic accuracy of all compared fracture prediction tools.
CONCLUSIONS: The current study showed that different fracture risk assessment tools, although having similar clinical purposes, require different cut-off thresholds for making therapeutic decisions. Better identification of patients requiring therapy based on such an approach may help reduce the number of new fractures.
BACKGROUND: The aim of the longitudinal, retrospective study was to compare three tools designed to assess fracture risk: FRAX, Garvan, and POL-RISK in their prediction of fracture incidence.
METHODS: The study group consisted of 457 postmenopausal women with a mean age of 64.21 ± 5.94 years from the Gliwice Osteoporosis (GO) Study. Comprehensive data on clinical factors related to fractures were collected for all participants. Bone densitometry was performed at the proximal femur using the Prodigy device (GE, USA). Fracture risk was established using the FRAX, Garvan, and POL-RISK algorithms. Data on the incidence of osteoporotic fractures were collected over the last 10 years.
RESULTS: During the period of observation 72, osteoporotic fractures occurred in 63 subjects. For a preliminary comparison of the predictive value of analyzed diagnostic tools, the fracture risk threshold of 10% was used. For FRAX, the fracture probability exceeding 10% was observed only in 11 subjects who experienced fractures; thus, the fracture was properly predicted only in 22.9% of women. For Garvan, the respective value was 90.5%, and for POL-RISK, it was 98.4%. That gave a very low true positive value for FRAX and a very high false positive value for Garvan and POL-RISK. Based on ROC curves, new thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds improve the diagnostic accuracy of all compared fracture prediction tools.
CONCLUSIONS: The current study showed that different fracture risk assessment tools, although having similar clinical purposes, require different cut-off thresholds for making therapeutic decisions. Better identification of patients requiring therapy based on such an approach may help reduce the number of new fractures.
摘要：
在纵向，回顾性研究,FRAX的能力，Garvan,在一组457名女性中比较了预测骨质疏松性骨折的POL-RISK算法.使用10%的刚性阈值显示所有工具的灵敏度和特异性的显著差异。每个计算器分别建立了新的高骨折风险阈值：FRAX主要骨折为6.3％，20.0%对于Garvan任何骨折，和18.0%的POL-RISK任何骨折。这样的阈值允许提高所有三个计算器的诊断准确性。
背景：纵向的目标，回顾性研究是比较三种评估骨折风险的工具：FRAX，Garvan,和POL-RISK预测骨折发生率。
方法：研究组包括457名绝经后妇女，平均年龄为64.21±5.94岁。收集所有参与者与骨折相关的临床因素的综合数据。使用Prodigy装置（GE，美国）。使用FRAX确定骨折风险，Garvan,和POL-RISK算法。收集了过去10年中有关骨质疏松性骨折发生率的数据。
结果：在观察72期间，63名受试者发生了骨质疏松性骨折。为了初步比较分析诊断工具的预测价值，使用10%的骨折风险阈值.ForFRAX,仅在11名经历骨折的受试者中观察到骨折概率超过10%；因此，只有22.9%的女性正确预测了骨折。对于Garvan来说,各自的值为90.5%，对于POL-RISK,是98.4%。这对FRAX给出了非常低的真正值，对Garvan和POL-RISK给出了非常高的假正值。根据ROC曲线，分别为每个计算器建立了高骨折风险的新阈值：FRAX主要骨折的6.3％，20.0%对于Garvan任何骨折，和18.0%的POL-RISK任何骨折。这样的阈值提高了所有比较的断裂预测工具的诊断准确性。
结论：目前的研究表明，不同的骨折风险评估工具，虽然有相似的临床目的，需要不同的截止阈值来做出治疗决策。基于这种方法更好地识别需要治疗的患者可能有助于减少新骨折的数量。
背景：纵向的目标，回顾性研究是比较三种评估骨折风险的工具：FRAX，Garvan,和POL-RISK预测骨折发生率。
方法：研究组包括457名绝经后妇女，平均年龄为64.21±5.94岁。收集所有参与者与骨折相关的临床因素的综合数据。使用Prodigy装置（GE，美国）。使用FRAX确定骨折风险，Garvan,和POL-RISK算法。收集了过去10年中有关骨质疏松性骨折发生率的数据。
结果：在观察72期间，63名受试者发生了骨质疏松性骨折。为了初步比较分析诊断工具的预测价值，使用10%的骨折风险阈值.ForFRAX,仅在11名经历骨折的受试者中观察到骨折概率超过10%；因此，只有22.9%的女性正确预测了骨折。对于Garvan来说,各自的值为90.5%，对于POL-RISK,是98.4%。这对FRAX给出了非常低的真正值，对Garvan和POL-RISK给出了非常高的假正值。根据ROC曲线，分别为每个计算器建立了高骨折风险的新阈值：FRAX主要骨折的6.3％，20.0%对于Garvan任何骨折，和18.0%的POL-RISK任何骨折。这样的阈值提高了所有比较的断裂预测工具的诊断准确性。
结论：目前的研究表明，不同的骨折风险评估工具，虽然有相似的临床目的，需要不同的截止阈值来做出治疗决策。基于这种方法更好地识别需要治疗的患者可能有助于减少新骨折的数量。
