Sani Mahnaz Pejman, Fahimfar Noushin, Panahi Nekoo, Mansournia Mohammad Ali, Sanjari Mahnaz, Khalagi Kazem, Mansourzadeh Mohammad Javad, Nabipour Iraj, Shafiee Gita, Ostovar Afshin, Larijani Bagher
Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
J Diabetes Metab Disord. 2022 Sep 30;21(2):1609-1617. doi: 10.1007/s40200-022-01110-3. eCollection 2022 Dec.
This study aimed to evaluate the performance of valid risk assessment models developed for osteoporosis/ fracture screening to identify women in need of bone density measurement in a population of Iranian elderly women.
This study was performed using the data of Bushehr Elderly Health (BEH) program, a population-based cohort study of elderly population aged ≥ 60 years. Seven osteoporosis risk assessment tools, including Osteoporosis Risk Assessment Instrument (ORAI), Malaysian Osteoporosis Screening Tool (MOST), Osteoporosis Prescreening Risk Assessment (OPERA), Osteoporosis Prescreening Model for Iranian Postmenopausal women (OPMIP), Osteoporosis Index of Risk (OSIRIS), and Osteoporosis Self-Assessment Tool for Asians (OSTA), as well as Fracture Risk Assessment Tool (FRAX) were included in the study. By using osteoporosis definition based on BMD results, the performance measurement criteria of diagnostic tests such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Youden index for each model were calculated and the models were compared.
A total of 1237 female participants with the mean age of 69.1 ± 6.3 years were included. Overall, 733 (59%) participants had osteoporosis, and about 80% had no history of fracture. The sensitivity of the seven models ranged from 16.7% (OSIRIS) to 100% (ORAI and MOST) at their recommended cut-off points. Moreover,their specificity ranged from 0.0% (ORAI and MOST) to 78.9% (OSTA). The FRAX and OPERA had the optimal performance with the Youden index of 0.237 and 0.226, respectively. Moreover, after combining these models, the sensitivity of them increased to 85.4%.
We found that the FRAX (model with 11 simple variables) and OPERA (model with 5 simple variables) had the best performance. By combining the models, the performance of each was improved. Further studies are needed to adopt the model and to find the best cut-off point in the Iranian postmenopausal women.
本研究旨在评估为骨质疏松症/骨折筛查开发的有效风险评估模型在识别伊朗老年女性群体中需要进行骨密度测量的女性方面的性能。
本研究使用布什尔老年健康(BEH)项目的数据,该项目是一项针对年龄≥60岁老年人群的基于人群的队列研究。研究纳入了七种骨质疏松症风险评估工具,包括骨质疏松症风险评估工具(ORAI)、马来西亚骨质疏松症筛查工具(MOST)、骨质疏松症预筛查风险评估(OPERA)、伊朗绝经后女性骨质疏松症预筛查模型(OPMIP)、骨质疏松症风险指数(OSIRIS)、亚洲人骨质疏松症自我评估工具(OSTA)以及骨折风险评估工具(FRAX)。根据基于骨密度结果的骨质疏松症定义,计算每个模型的诊断测试性能测量标准,如敏感性、特异性、阳性预测值(PPV)、阴性预测值(NPV)和尤登指数,并对模型进行比较。
共纳入1237名女性参与者,平均年龄为69.1±6.3岁。总体而言,733名(59%)参与者患有骨质疏松症,约80%没有骨折史。七个模型在其推荐切点处的敏感性范围为16.7%(OSIRIS)至100%(ORAI和MOST)。此外,它们的特异性范围为0.0%(ORAI和MOST)至78.9%(OSTA)。FRAX和OPERA的性能最佳,尤登指数分别为0.237和0.226。此外,将这些模型组合后,它们的敏感性提高到了85.4%。
我们发现FRAX(具有11个简单变量的模型)和OPERA(具有5个简单变量的模型)性能最佳。通过组合模型,每个模型的性能都得到了改善。需要进一步研究以采用该模型并在伊朗绝经后女性中找到最佳切点。