骨质疏松症危险评价工具在成都地区绝经后妇女中的效果评价

目的 评价骨质疏松症危险评价工具(SCORE、OSTA、ORAI、OSIRIS)在成都地区绝经后妇女的筛检效果.方法 采用诊断性研究,比较腰椎(L<,1>-L<,4>)DXA BMD值及上述各险评价工具危险评分,分别计算各量表的敏感度(Sens)、特异度(Spee)、准确度(Accu).结果 当r≤-2.5,SCORE的Sens、Spec、Accu分别为81.3%、65.5%、70.3%;OSTA的Sens、Spec、Accu分别为81.6%、75%、80.5%;ORAI的Sens、Spec、Accu分别为93.8%、36.8%、32.2%;OSIRIS的Sens、Spee、Accu分别为80.5%、71.9%、80.5%.结论 这些危险评价工具均有一定的筛检效果,在成都地区OSTA及OSIRIS均具有较好的筛检效果,能够较准确的识别大部分骨质疏松症病人,实际操作中,OSTA更简单.     

妇女骨质疏松症筛检工具应用效果探讨

目的比较与评价国内外骨质疏松症筛检工具在妇女人群中的筛检效果,对建立我国骨质疏松症适宜筛检工具提供依据。方法检索MEDLINE、PubMed及中国生物医学文献数据库1966~2006年相关中英文文献,同时手工检索参考文献中的相关文献。对入选文献按事先确定的入选与剔除标准用筛检工具进行筛选,确认所有入选文献符合入选标准。结果常用筛检工具SCORE、OST/OSTA、ORAI和OSIRIS均具有较高敏感性,但特异性尚不高,而且不同研究之间特异性相差较大。SCORE的敏感性在90%~98%之间,但特异性平均为20%左右。ORAI敏感性与SCORE近似,特异性略高于SCORE。这4种危险评价工具中OST/OSTA效果最好,其仅使用2个危险因素,其特异性高于SCORE。OSIRIS的筛检效果与ORAI,OST/OSTA类似。其他筛检工具效果尚难肯定。结论常用筛检工具具有一定的筛检效果,工具的效果验证研究尚有待于深入。筛检工具的应用为临床医生筛选可疑患者、确定那些患者最可能从骨密度测量中受益提供了快捷、可行的手段,是合理利用卫生资源,控制与减轻骨质疏松症危害的必要措施。     

绝经后女性中医症候群骨质疏松风险预测工具构建

目的 构建中医证候的绝经后女性的骨质疏松(osteoporosis,OP)风险预测工具。方法 问卷调查,收集研究对象一般资料、病史和中医症状,并进行骨密度检测。Logistic回归方法构建模型,并通过与常用预测工具OSTA指数比较及外部验证,分析其预测效能。结果 年龄、体重、驼背和精神不振是OP危险因素,结合OP主要中医证候——肾虚证典型症状腰膝酸软、下肢抽筋、夜尿频多和耳鸣构建COPT模型。其ROC曲线下面积AUC=0.765,高于OSTA指数AUC;最优判断界值为>-0.79,灵敏度为69.43,特异性为72.60。外部数据验证灵敏度为68.85,特异性为75.00。结论 中医证候表现在OP风险预测中具有一定作用,在本研究中,COPT模型预测效能优于OSTA指数,外部数据验证结果进一步支持COPT具有良好预测效能。     

OSTA指数与体重指数对于绝经后妇女骨质疏松的预测效果评价

目的 评估亚洲骨质疏松自我评估工具(OSTA)和体重指数(BMI)预测社区绝经后妇女骨质疏松症的效果。方法 利用双能X线吸收仪测定320例绝经期女性的骨密度,计算OSTA指数和体重指数,并评价他们对于骨质疏松症的预测效果。结果 腰椎和股骨颈骨质疏松检出率分别为25. 9%和35. 9%,OSTA指数和BMI都和骨密度有明显的相关性。以OSTA≤- 1作为临界点,预测腰椎、股骨颈骨质疏松症的灵敏度和特异度分别为75. 3%和69. 1%。如果按照BMI >23. 0相应的指标为 67.0%和55.6%。结论 OSTA指数和BMI对于绝经后妇女骨质疏松症都有一定的预测价值,但是灵敏度都特别低。相比而言,OSTA指数更为简单方便,也有更好的评价效果。     

OSTA指数对江苏镇江地区健康中老年人群骨质疏松的筛选价值

目的分析亚洲人骨质疏松自我筛查工具(OSTA)对江苏镇江地区中老年群体骨质疏松(OP)的筛选价值。方法收集961例中老年人群骨密度(BMD)信息。将OSTA指数与BMD进行相关分析、Kappa检验及ROC分析。结果 OSTA指数对于年龄≥45岁的女性人群和男性人群OP诊断准确性都可达中等(AUC:女性0.773,男性0.759)。但灵敏度上女性明显高于男性(女性74.7%,男性55.9%);通过双因素分析,对于老年男性,当诊断截点为-3.66时,OSTA指数灵敏度可达91.7%,较其他分类人群明显提高。其他筛选价值较高的人群有准老年高BMI者(85.2%)、正常BMI女性(80.6%)。筛选价值较低的人群为低BMI男性(33.3%)、中年低BMI者(25.0%)、准老年低BMI者(50.0%)。结论 OSTA指数对不同中老年人群OP筛选效果不同。     

OSTA在中国各级医疗机构骨质疏松筛查中的应用进展

中国人口老龄化日益严重,骨质疏松症的发生率愈来愈高,其防治费用给患者家庭和社会经济造成了沉重的负担。随着国家分级诊疗制度建设的深入,各级医疗机构就诊人数越来越多,其中大部分对于骨质疏松症的认识程度较低。在此背景下,骨质疏松症初筛工具的应用显得尤为重要。亚洲人骨质疏松自我筛查工具(osteoporosis self-assessment tool for Asians,OSTA)是针对亚洲绝经后女性制定的一套工具,只参考年龄和体重两个因素。虽然在使用过程中仍存在一定的局限性,但具有操作简单方便,灵敏度相对较高的特点,特别是在缺乏检测手段的基层医疗机构中进行骨质疏松筛查应用方面前景广阔。本文将近年来利用OSTA在中国各级医疗机构进行骨质疏松筛查的相关研究进行综述,旨在探讨OSTA在此方面的适用性,以期为骨质疏松症的初筛、管理、分级诊疗等方面提供新视角。     

骨质疏松性骨折风险预测方法的研究进展

骨质疏松性骨折(Osteoporosis fracture,OF)是一种随着年龄增加而增加的疾病,其预后不佳。因此,及早进行骨质疏松骨折风险预测显得至关重要。骨质疏松骨折预测方法有以下几种：骨密度检查、FRAX工具、Garvan nomogram评估法、ORAI、OSTA、定量骨超声、骨代谢标志物等。研究表明,FRAX工具可预测个体10年内发生髋部骨折及任何重要的OF的概率,优于其他方法。     

3253例围绝经及绝经后女性骨质疏松风险评估工具的应用

目的 比较分析FRAX(不含BMD模型)、BMD、BMI、OSTA指标对北京南郊地区围绝经期及绝经后女性骨质疏松风险的预测评估价值。方法 选取2017年1月至2022年6月在大兴区中西医结合医院行骨密度检查的围绝经期及绝经后女性3 253例，收集患者年龄、身高、体重、骨密度T值等数据，分析FRAX(不含BMD模型)、BMD、BMI和OSTA 4种指标在各年龄层和不同骨量之间的差异，绘制不同指标诊断骨量减少或骨质疏松的ROC曲线，比较各指标预测的准确性。结果 随着年龄增加，BMD、OSTA减低，FRAX-MOF、FRAX-HF增加；(2)骨量越小，BMD、OSTA越低，FRAX-MOF、FRAX-HF越高；(3)FRAX-MOF、FRAX-HF诊断骨质疏松的AUC值分别为0.811和0.810,较OSTA(AUC=0.799)有更好的诊断效能(P<0.001);(4);FRAX-MOF、FRAX-HF诊断骨量减少的AUC值分别为0.770和0.767,较OSTA(AUC=0.748)有更好的诊断效能(P<0.001),OSTA指数特异性较高(83.0%),临界值为0.10。结...     

两种骨质疏松筛选方法在绝经后饽芰骨质疏松妇女中的应用比较

目的 分别评估亚洲骨质疏松筛查工具(OSTA)及上海市绝经后妇女低骨量简易筛选方法(STLBMS)与上海市绝经后妇女骨密度及椎体骨折的关系,并比较两种筛选方法对骨质疏松和椎体骨折发生的预测能力.方法 共入选988例绝经后妇女,有或无脊椎压缩性骨折各494例.两组均用双能X线吸收仪检测腰椎和股骨近端骨密度,并计算OSTA与STLBMS指数.结果 两种筛选法均显示骨折组风险指数更高(P<0.001);在两组中分别比较两种筛选法,均显示STLBMS法的风险指数更高(P<0.001).OSTA与STLBMS指数与骨密度均正相关(r=0.336～0.562和r=0.383～0.570,P均<0.001);而两种筛选指数间呈显著正相关(r=0.974,P<0.001).以OSTA <-1和STLBMS>5为分界点,OSTA与STLBMS法诊断骨质疏松的工作曲线,曲线下面积(AUC)分别为0.73和0.74;在预测椎体骨折方面,OSTA与STLBMS法的AUC分别为0.55和0.57.结论 OSTA和STLBMS筛选法均与骨密度呈显著正相关,也有助于椎体骨折的发现,两种方法对骨质疏松和椎体骨折发生的预测能力没有统计学差异,是理想的骨质疏松筛选工具.     

骨折风险评估工具（FRAX® )在评价绝经后女性骨密度的临床意义

目的探讨骨折风险评估工具(FRAX)在评价绝经后女性骨密度变化中的作用。方法 2014年12月至2015年12月完成双能X线骨密度测定的绝经后女性166例,问卷采集信息,应用FRAX计算代入或不代入股骨颈骨密度时各研究对象10年内骨质疏松性骨折概率,并结合骨密度测定结果、OSTA及IOF 1 min测试题进行统计学分析。结果 1骨量异常组年龄较高、体重较轻、BMI较低、身高变化较多、绝经年限较长,两组间具有既往骨折史的人数差异有统计学意义。2有或无BMD时,骨量异常组10年内骨质疏松性骨折概率均显著高于骨量正常组。3有或无股骨颈BMD时,FRAX预测值与股骨颈骨密度T值之间均呈显著负相关,而有和无股骨颈BMD的FRAX预测值之间呈显著正相关。4随着年龄或骨质疏松风险的增长,骨量异常发生率逐渐上升,10年内骨质疏松性骨折概率显著升高。5不代入BMD时,10年内主要骨质疏松性骨折概率识别骨量异常的ROC曲线的AUC为0.705(P0.001),cutoff值为3.75%,准确度为中等;10年内髋骨骨折概率识别骨量异常的ROC曲线的AUC为0.743(P0.001),cutoff值为1.75%,准确度中等。结论 FRAX能够反映机体骨密度变化,全面评估骨折风险,并可作为一项基本的筛检工具,应用于识别绝经后女性骨质疏松的高危人群。     

Evaluation of Different Screening Tools for Predicting Femoral Neck Osteoporosis in Rural South Indian Postmenopausal Women

The measurement of bone mineral density by dual-energy X-ray absorptiometry scan is the “gold standard” for the diagnosis of osteoporosis, which has limited availability in many parts of India. This study was done to assess the diagnostic performance of 6 internationally validated tools (Simple Calculated Osteoporosis Risk Estimation [SCORE], age, bulk, one or never estrogen [ABONE], Osteoporosis Risk Assessment Instrument [ORAI] and Osteoporosis Self-Assessment Tool for Asians [OSTA], Fracture Risk Assessment Tool [FRAX®], and calcaneal quantitative ultrasound [QUS]) for the diagnosis of osteoporosis at the femoral neck (FN). This was a cross-sectional study conducted in 2108 ambulatory South Indian rural postmenopausal women who were assessed with SCORE, ABONE, ORAI, OSTA, and FRAX® tools. QUS was performed in 850 subjects. Bone mineral density was estimated by dual-energy X-ray absorptiometry scan at the FN, and sensitivity and specificity were calculated for all tools for predicting FN osteoporosis. The receiver operating characteristic curve was constructed for each tool and the area under the curve (AUC) was calculated. FN osteoporosis was seen in 27%. The sensitivities of SCORE, ABONE, OSTA, ORAI, FRAX®, and QUS were 91.3%, 91.0%, 88.5%, 81.0%, 72.7%, and 81.9%, and the specificities were 36.0%, 33.5%, 41.7%, 52.0%, 60.5%, and 50.3%, respectively, for the FN osteoporosis. When the receiver operating characteristics were constructed, the AUC was good only for SCORE (0.806), and the performance of the rest was under fair category (0.713–0.766). In our large cohort of rural postmenopausal women, the SCORE screening tool was found to be useful with good sensitivity and good AUC for predicting FN osteoporosis. Thus, this tool may be used in resource-limited countries to screen the population at risk and to enable treating physicians to make appropriate management decisions.     

Validation of various osteoporosis risk indices in elderly Chinese females in Singapore

Introduction This study aimed to compare the sensitivity and specificity of various published indices for identifying elderly Chinese females at risk of osteoporosis in Singapore.Methods The indices considered were the Simple Calculated Osteoporosis Risk Estimation (SCORE), the Osteoporosis Risk Assessment Instrument (ORAI), the Age Bulk One or Never Estrogens (ABONE), body weight (WEIGHT), and the Osteoporosis Self-Assessment Tool for Asians (OSTA). Altogether, 135 postmenopausal Chinese female subjects aged 55 years and older participated in the study, and their bone mineral density (BMD) was measured with dual-energy x-ray absorptiometry. Subjects were classified as osteoporotic if their femoral neck BMD T-score was −2.5 or lower. Receiver operating characteristic (ROC) curves were generated to determine the indices’ cut-off points, sensitivity, and specificity.Results OSTA had the highest discriminatory power, with an estimated area under the ROC curve of 0.82. This was followed by SCORE (0.80), WEIGHT (0.78), ORAI (0.76), and ABONE (0.70). At the cut-off point of −2, OSTA achieved sensitivity and specificity of 91% and 59%, respectively.Conclusion The study showed that OSTA is an effective index for identifying postmenopausal women at risk for osteoporosis.     

Clinical performance of osteoporosis risk assessment tools in women aged 67 years and older

SUMMARY: Clinical performance of osteoporosis risk assessment tools was studied in women aged 67 years and older. Weight was as accurate as two of the tools to detect low bone density. Discriminatory ability was slightly better for the OST risk tool, which is based only on age and weight. INTRODUCTION: Screening performance of osteoporosis risk assessment tools has not been tested in a large, population-based US cohort. METHODS: We conducted a diagnostic accuracy analysis of the Osteoporosis Self-assessment Tool (OST), Osteoporosis Risk Assessment Instrument (ORAI), Simple Calculated Osteoporosis Risk Estimation (SCORE), and individual risk factors (age, weight or prior fracture) to identify low central (hip and lumbar spine) bone mineral density (BMD) in 7779 US women aged 67 years and older participating in the Study of Osteoporotic Fractures. RESULTS: The OST had the greatest area under the receiver operating characteristic curve (AUC 0.76, 95% CI 0.74, 0.77). Weight had an AUC of 0.73 (95% CI 0.72, 0.75), which was >or=AUC values for the ORAI, SCORE, age or prior fracture. Using cut points from the development papers, the risk tools had sensitivities >or=85% and specificities 相似文献   

Prescreening tools to determine who needs DXA

Clinical decision rules (CDRs) are designed to help physicians practice better. A number of CDRs to assist in identifying women with low bone mass have been developed since the mid 1990s, including SCORE, OST (OSTA), OSIRIS, SOFSURF, NOF, ABONE, pBW, ORAI, and weight-only-EPIDOS (which we have termed WO-E). This review discusses these CDRs in terms of development and validation cohorts and their sensitivity and specificity. The sensitivities of the available CDRs exceed 80% and specificities are about 50%. After much analysis, it appears that most experts prefer OST for its simplicity and SCORE for its flexibility, but there is no consensus on what risk factors to use in the CDRs and what regions of interest (spine, total hip, femoral neck, or a combination) to test with dual-energy x-ray absorptiometry (DXA). Because of the lack of consensus, there are barriers to the clinical application of these CDRs. Agreement on a single CDR for worldwide use is required to optimally fulfill the objective of identifying low bone mass.     

Comparison of questionnaire and quantitative ultrasound techniques as screening tools for DXA

The aim of the study is to assess the sensitivity and specificity of different techniques and their ability to act as screening tools in relation to dual energy X-ray absorptiometry (DXA) in a group of 208 postmenopausal women. In this study we examined eight screening systems for the diagnosis of osteoporosis, the osteoporosis self-assessment tool (OST), the osteoporosis risk assessment instrument (ORAI), the osteoporosis index of risk (OSIRIS), a risk index derived using data from the study of osteoporotic fractures (SOFSURF), the simple calculated osteoporosis risk estimation (SCORE), patient body weight (pBW), along with two ultrasound based systems, the Sunlight Omnisense (Sunlight Medical, Rehovot, Israel) and the CUBA Clinical (McCue plc, Winchester, UK). The sensitivity and specificity of the different techniques in relation to DXA were plotted as receiver-operating characteristic (ROC) curves at three different levels (DXA T-score –2.5 osteoporosis, –2 and –1 osteopenia). The areas under the curves (AUC) were calculated and showed broadband ultrasound attenuation (BUA) at the calcaneus to provide consistently the highest AUC (0.77–0.81). The velocity of sound (VOS) of the calcaneus (AUC =0.72–0.76) was equally good, but was out-performed by some of the questionnaire systems (AUC =0.66–0.79). Both the questionnaire systems and the CUBA Clinical out-perform the Sunlight Omnisense (AUC =0.58–0.7), which showed comparable performance with body weight (AUC =0.66–0.69). The results show that QUS is capable of selecting patients with low bone density as measured by DXA. A patient displaying a low QUS value should be followed up with a DXA scan to confirm the diagnosis.     

Primary prevention of osteoporosis: mass screening scenario or prescreening with questionnaires? An economic perspective.

This study focuses on the controversy surrounding selective approaches to screen for osteoporosis. Seven screening approaches were compared in terms of cost-effectiveness and incremental cost-effectiveness ratios in a sample of 4035 postmenopausal women. Our results show that certain prescreening strategies are more efficient than DXA-based approaches. These results are of considerable value for health policy decision-makers and the scientific community. INTRODUCTION: There is no general consensus on the most efficient strategy to use bone densitometry for osteoporosis screening. Two distinct approaches have progressively emerged: mass screening using DXA and prescreening strategies using user-friendly risk indices. This study was designed to compare the efficiency of these approaches. MATERIALS AND METHODS: A database of 4035 medical records from postmenopausal women above 45 years was analyzed. In the first scenario, women were systematically referred to DXA if above 45, 50, or 65 years of age. The second scenario involved the validated prescreening tools SCORE, ORAI, OST, and OSIRIS and assessed two separate ways of handling their results (theoretical and pragmatic). The cost of a DXA test was set as the median Belgian value: 40.14 Euros. All strategies were compared in terms of cost exposed per osteoporotic patient detected and in terms of incremental cost-effectiveness ratios. RESULTS: In the systematic DXA strategies, the cost per patient detected ranged from 123 Euros when measuring all women >45 years of age to 91 Euros when focusing on women >65 years of age. The corresponding percentage of cases detected ranged from 100% (age > 45 years) to 50% (age > 65 years). When considering prescreening under the theoretical and pragmatic scenarios, the OSIRIS index provided the best efficiency, with costs of 74 Euros (theoretical) to 85 Euros (pragmatic) per case detected, followed by ORAI (75 Euros and 96 Euros), OST (84 Euros and 94 Euros), and SCORE (96 Euros and 103 Euros). The corresponding percentage of cases detected ranged from 89% (SCORE) to 75% (OSIRIS). The cost-effectiveness analysis showed that mass screening strategies over 50 and 65 years of age and using ORAI were best. CONCLUSIONS: Our study sets the grounds for considering, in a health economics perspective, prescreening tools as valuable, cost-effective, approaches to significantly reduce the economic burden of osteoporosis screening.     

Risk assessment instruments for screening bone mineral density in a Mediterranean population

AIM To evaluate the power of six osteoporosis-screening instruments in women in a Mediterranean country.METHODS Data concerning several osteoporosis risk factors were prospectively collected from 1000 postmenopausal women aged 42-87 years who underwent dual-energy X-ray absorptiometry(DEXA) screening. Six osteoporosis risk factor screening tools were applied to this sample to evaluate their performance and choose the most appropriate tool for the study population.RESULTS The most important screening tool for osteoporosis status was the Simple Calculated Osteoporosis Risk Estimation, which had an area under the curve(AUC)of 0.678, a sensitivity of 72%, and a specificity of 72%, with a cut-off point of 20.75. The most important screening tool for osteoporosis risk was the Osteoporosis Self-assessment Tool, which had an AUC of 0.643, a sensitivity of 77%, and a specificity of 46%,with a cut-off point of-2.9.CONCLUSION Some commonly used clinical risk instruments demonstrate high sensitivity for distinguishing individuals with DEXA-ascertained osteoporosis or reduced bone mineral density.     

Development and validation of osteoporosis risk-assessment model for Korean postmenopausal women

Currently, dual-energy X-ray absorptiometry (DXA) is the gold standard for detecting osteoporosis, but is not recommended for general population screening. Therefore, this study aims to develop an osteoporosis risk-assessment model to identify high-risk individuals among Korean postmenopausal women. Data from 1,209 and 1,046 postmenopausal women who participated in the 2009 and 2010 Korean National Health and Nutrition Examination Survey, respectively, were used for development and validation of an osteoporosis risk-assessment model. Osteoporosis was defined as T score less than or equal to ?2.5 at either the femoral neck or lumbar spine. Performance of the candidate models and the Osteoporosis Self assessment Tool for Asians (OSTA) were compared with respect to sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). To compare the developed Korean Osteoporosis Risk-Assessment Model (KORAM) with OSTA, a net reclassification improvement was further calculated. In the development dataset, the prevalence of osteoporosis was 33.9 %. KORAM, consisting of age, weight, and hormone therapy, had a sensitivity of 91.2 %, a specificity of 50.6 %, and an AUC of 0.709 with a specific cut-off score of ?9. Comparable results were shown in the validation dataset: sensitivity 84.8 %, specificity 51.6 %, and AUC 0.682. Additionally, risk categorization with KORAM showed improved reclassification over that of OSTA from 7.4 to 41.7 %. KORAM can be easily used as a pre-screening tool to identify candidates for DXA tests. Further studies investigating cost-effectiveness and replicability in other datasets are required to establish the clinical utility of KORAM.     

Osteoporosis Screening in Postmenopausal Women 50 to 64 Years Old: Comparison of US Preventive Services Task Force Strategy and Two Traditional Strategies in the Women's Health Initiative

The US Preventive Services Task Force (USPSTF) recommends osteoporosis screening for women younger than 65 years whose 10‐year predicted risk of major osteoporotic fracture is ≥9.3%. For identifying screening candidates among women aged 50 to 64 years, it is uncertain how the USPSTF strategy compares with the Osteoporosis Self‐Assessment Tool (OST) and the Simple Calculated Osteoporosis Risk Estimate (SCORE). We examined data (1994 to 2012) from 5165 Women's Health Initiative participants aged 50 to 64 years. For the USPSTF (Fracture Risk Assessment Tool [FRAX] major fracture risk ≥9.3% calculated without bone mineral density [BMD]), OST (score <2), and SCORE (score >7) strategies, we assessed sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) to discriminate between those with and without femoral neck (FN) T‐score ≤?2.5. Sensitivity, specificity, and AUC for identifying FN T‐score ≤?2.5 were 34.1%, 85.8%, and 0.60 for USPSTF (FRAX); 74.0%, 70.8%, and 0.72 for SCORE; and 79.8%, 66.3%, and 0.73 for OST. The USPSTF strategy identified about one‐third of women aged 50 to 64 years with FN T‐scores ≤?2.5. Among women aged 50 to 64 years, the USPSTF strategy was modestly better than chance alone and inferior to conventional SCORE and OST strategies in discriminating between women with and without FN T‐score ≤?2.5. © 2014 American Society for Bone and Mineral Research.     

Effects of Lifestyle and Risk Factors on Bone Mineral Density in a Cohort of Italian Women: Suggestion for a New Decision Rule

In this study the authors analyzed the role of risk factors in postmenopausal osteoporosis in a cohort of Italian women and evaluated predictive values of decision rules for early identification of osteoporotic women. Furthermore, the authors investigated the prevalence of secondary osteoporosis in this population. Women who underwent bone densitometry were asked to answer a questionnaire about the common risk factors for osteoporosis. Patients were classified as nonosteoporotic, nonosteopenic, and osteoporotic. Risk factors were compared among the groups by use of analysis of variance (ANOVA). National Osteoporosis Foundation (NOF) recommendation, Osteoporosis Risk Assessment Instruments (ORAIs), Osteoporosis Self-Assessment Tools (OST) score, and weight criterion were applied to this population. The authors proposed a new decision rule based on a new score. A total of 525 women received the questionnaire: 47.4% women were osteoporotic, 32.2% were osteopenic, and 20.4% nonosteoporotic. Risk factors that differed significantly between these groups were: age, age at menarche, postmenopausal period, and body mass index (BMI); the aforementioned risk factors appear to be significant predictors of bone density (BMD) in linear regression model. The incidence of secondary osteoporosis was 13%. In conclusion, the authors (1) confirmed the role played by nonmodifiable risk factors in determining BMD; (2) showed that the use of NOF guidelines, ORAI, OST score, and weight criterion is not satisfactory in our cohort; (3) suggested a new score, based upon the features that were significantly different between patients and controls; and (4) demonstrated the relatively high prevalence of secondary osteoporosis and suggest a primary screening for secondary osteoporosis in all patients with low BMD.