国外骨折风险评估工具FRAX的应用进展

骨质疏松性骨折是骨质疏松最严重的后果,世界卫生组织推荐使用简单易行的骨折风险预测工具FRAX评估患者的骨折风险,针对高风险人群进行及时干预,大大降低其危害。国外有关FRAX应用研究逐渐精细和深入,有关FRAX在不同疾病患者中的适用性,及结合、不结合股骨颈BMD对FRAX预测结果影响的研究逐渐增多。本文就FRAX在国外类风湿关节炎、绝经后女性和糖尿病患者中的应用现状进行综述,FRAX在不同病种的应用为临床医生及护士积极采取防治及护理措施提供决策和依据。     

应用FRAX工具评估类风湿关节炎患者骨折风险及其风险因素的相关性研究

目的探讨骨折风险评估工具(FRAX)预测类风湿关节炎(RA)患者骨质疏松性骨折的临床应用价值并对其骨折风险因素进行相关性分析。方法回顾性分析2015年1月至2016年2月期间经确诊的74例类风湿关节炎患者以及正常对照组76例的相关临床指标以及骨密度值;评估FRAX对类风湿关节炎患者的骨折风险预测值以及FRAX与类风湿临床风险因素之间的关系。结果类风湿组股骨颈、腰椎的骨密度值均低于对照组,而类风湿组中10年主要骨质疏松性骨折发生概率和10年髋部骨折发生概率均高于对照组。多重线性回归分析提示FRAX评分与易激动、口味偏淡、体重指数、S-CTX具有一定的相关性。结论 FRAX工具对临床评估RA患者骨质疏松性骨折风险、预后评价等方面具有良好的应用价值。     

FRAX评估江苏镇江地区中老年人群骨折风险的回顾性研究

目的评估FRAX■工具对江苏镇江地区中老年人骨质疏松性骨折的预测价值。方法对1070例江苏镇江地区中老年人群进行分组性研究,应用FRAX■工具计算未来10年主要骨质疏松性骨折(probability of major osteoporosis fracture,PMOF)和髋部骨折的概率(probability of hip fracture,PHF),分析年龄、体质量指数、有无骨质疏松性骨折史以及不同骨量对FRAX预测结果的影响。结果随着年龄的增长10年内PMOF和PHF同步增加;随着体重指数的增加,10年内PMOF和PHF同步下降;有骨质疏松性骨折史的人群10年内PMOF和PHF明显增加;随着骨量下降,10年内PMOF和PHF逐渐增加;不同骨量受人群在不同骨质疏松骨折风险组中的分布不同。在骨质疏松性骨折高风险人群中,骨质疏松者占78.1%,低骨量者占20.7%,正常骨量者占1.3%。结论FRAX■工具可用于江苏镇江地区中老年人群骨质疏松骨折风险的评估。FRAX■工具可能低估了低骨量人群的骨质疏松性骨折的风险,该工具对中老年低骨量人群的预测价值值得进一步研究。     

FRAX评估北京地区中老年人群骨折风险的回顾性研究

目的评价WHO发布的骨折风险评估工具FRAX对北京地区中老年人群的适用性,预测北京地区不同性别及年龄亚组中老年人群的骨折风险,讨论既往骨折病史对于FRAX的影响。方法对3021例北京地区中老年人群进行分组性研究。输入相关资料及FRAX工具中所包含的危险因素,计算未来10年内发生全身骨质疏松性骨折及髋部骨折的风险概率,比较既往骨折病史人群对FRAX预测结果影响。结果北京地区女性中老年人群未来10年内骨折风险远高于同年龄组男性;伴随年龄增大,未来10年内发生全身骨质疏松性骨折及髋部骨折的风险概率不分性别均同步增高。有既往骨折病史的老年人群10年内再发骨折风险远高于无骨折史人群。结论利用FRAX工具可以对北京地区中老年人群骨折风险做出有效评估,针对于不同性别、不同年龄亚组的人群,联合髋部BMD值后获取的FRAX预测在既往骨折或未骨折患者中均具有临床应用价值。FRAX评估工具在骨质疏松的诊断、治疗及预后评价等方面具有良好的临床应用价值。     

FRAX评分在中老年人骨质疏松性骨折风险评估中的研究进展

骨质疏松症(osteoporosis)是一种以骨密度降低、骨小梁及其他组织结构损坏,造成骨脆性以及骨折风险增加为特征的全身性骨病。FRAX评分是2008年世界卫生组织推荐的骨折风险预测简易诊断工具,可用于计算10年发生髋部骨折及任何重要的骨质疏松性骨折的发生概率。目前FRAX评分的应用才刚刚起步,评价标准还不完善,使用过程存在一定的局限性。但是长远来看,FRAX评分在骨质疏松性骨折预测方面应用前景广阔,将会成为预防骨质疏松性骨折的有力工具。本文将近年来FRAX评分的应用以及研究进展进行综述。以期在骨质疏松性骨折预防、管理、诊断和治疗方面提供新思路、新视角。     

上海市社区老年人骨质疏松性骨折的风险评估

目的应用FRAX工具评估上海市社区老年人骨质疏松性骨折的风险。方法收集1300例上海市社区老年人的临床资料并进行回顾性分析,应用FRAX工具计算10年内骨折发生风险,应用统计学分析不同危险因子与FRAX计算的骨折风险的相关性。结果研究对象10年内发生主要部位骨质疏松性骨折发生风险为(6.0±3.6)%,髋部骨折的发生风险为(2.8±2.4)%。主要部位骨质疏松性骨折风险及髋部骨折风险均随着年龄增长而增加。相关性研究结果显示,跌倒与10年主要部位和髋部骨折发生风险具有显著相关性(r=0.134,P0.01;r=0.124,P0.01)。结论 FRAX工具可用于评估上海市社区老年人骨质疏松性骨折的风险,建议在老年人健康体检时应用FRAX工具进行骨折风险评估。     

骨质疏松性骨折风险预测工具的研究现状

骨质疏松性骨折(osteoporotic fractures,OF)是骨质疏松(osteoporosis,OP)患者最严重的并发症,对生活质量影响极大且致死率高;骨密度结合临床风险因子的OF预测工具可以有效评估骨折发生的风险,有助于OF的早预防、早治疗。本文主要阐述目前使用最多的三种OF风险评估工具:FRAX、QFracture和Garvan nomogram,通过查阅近些年发表的文献收集相关数据,从风险因子、适用人群、预测能力等方面总结其优缺点,以便为临床医生工作和患者自我管理提供参考。     

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。     

BMD、OSTA与FRAX®预测绝经后女性骨质疏松性 骨折风险的比较研究

目的比较BMD、OSTA与FRAX(不含BMD模型)预测绝经后女性骨质疏松性骨折风险的准确性,为选择适合我国绝经后女性骨质疏松性骨折风险工具提供研究依据。方法 2011年1月至2011年12月,以首都医科大学附属北京友谊医院就诊并接受DXA骨密度检查的绝经后女性为研究对象,连续纳入1497例,建立队列。基于基线数据,以就诊时发生骨质疏松性骨折与否为参考标准,绘制ROC曲线,比较BMD、OSTA及FRAX评分预测骨质疏松骨折发生风险的准确性。结果发生骨折组(n=343)患者的BMD,OSTA评分与FRAX评分均低于未发生骨折组(n=1154),且差异均有统计学意义。BMD、OSTA及FRAX评分(不使用骨密度的主要部位FRAX评分)预测骨折风险的ROC曲线下面积分别为0.654(95%CI:0.621-0.687),0.629(95%CI:0.595-0.663)和0.907(95%CI:0.888-0.926),最佳诊断截点值分别为-1.25,-1.90和3.65%。结论不使用骨密度的主要部位FRAX评分可用于我国绝经后女性的骨质疏松性骨折风险评估,但诊断截点值为3.65%,远低于WHO推荐的20%,其原因需要进一步研究。     

应用FRAX筛查骨质疏松高危人群的方法研究

目的应用骨折风险评估工具(FRAX)预测不同骨质疏松性骨折危险因子及股骨颈骨密度(BMD)情况下10年骨折风险性的差异,探讨筛查骨质疏松高危人群的方法。方法应用FRAX的中国大陆子模型软件,综合年龄、性别、体重指数,计算单一危险因子或多重危险因子在联合或不联合BMD的条件下预测骨折风险性。结果随着BMD下降、骨折危险因子增多,10年骨质疏松性骨折风险增大。不同骨折危险因子和BMD配对时骨折风险性不同,当BMD未达骨质疏松诊断标准而合并部分危险因子时的骨折风险性大于BMD的T值达-2.5SD但无危险因子时的骨折风险性。结论 FRAX模型使原来单凭BMD转向综合各类危险因子评估长期骨质疏松性骨折风险性,在无条件行BMD检测地区可用以筛查骨质疏松高危人群。     

慢性肾脏病患者继发性骨质疏松症的管理

慢性肾脏病(CKD)继发骨质疏松症的患者骨折风险明显增加,严重影响患者的生活质量,使死亡率增加。规范管理CKD患者继发性骨质疏松症具有重要意义。肾小球滤过率下降带来的全身矿物质代谢异常是导致CKD患者骨质疏松的重要因素。临床诊断和评估CKD患者的骨质疏松,建议根据KDIGO指南进行生化指标的评估,定期检测骨密度,使用风险预测工具如亚洲人骨质疏松自我筛查工具(OSTA)和WHO骨折风险预测简易工具(FRAX)进行骨质疏松骨折风险预测。骨质疏松重在防范,治疗应个体化,除了基础治疗,必要时可采用药物治疗,如活性维生素D、双膦酸盐、降钙素等,但应严格掌握适应症,考虑其在CKD患者中的安全性问题,避免发生高钙血症、血管钙化等临床严重问题。     

The Utility and Limitations of FRAX: A US Perspective

The FRAX calculator is a major achievement in terms of our understanding of measuring fracture risk. Along with being an easily accessible web-based tool, it is the only model based on extensive data on multiple cohorts. FRAX will help clinicians identify individuals who need osteoporosis treatments, while also screening out those who do not require osteoporosis treatments. However, FRAX is limited by a number of factors. Although it is web based, few physicians have the means to access it. It also assumes that body mass index and mortality are constant across different racial and ethnic groups. FRAX is further limited by the exclusion of variables known to be associated with fracture risk, lack of dose-response relationships for variables, increased subsequent fracture risk after initial fracture, restriction to only one bone mineral density site, racial and ethnic differences that may influence fracture risk, and availability of racial and ethnic fracture risk data to be used in the FRAX calculator. Finally, the values obtained from FRAX should not take the place of good clinical judgment.     

FRAX®在女性骨质疏松症诊疗中的应用研究进展

骨质疏松症是常见的骨骼疾病，绝经后女性为骨质疏松症的高危人群。骨折风险评价工具（fracture risk assessment tool，FRAX?）是一款研究、应用广泛的骨折风险评估工具。近年来研究表明，虽然FRAX?尚不完美，但对女性人群的骨折具有合理的预测能力，结合其他骨折危险因素对该工具进行调整、改进的研究也多见报道。设立符合本国国情的FRAX?阈值有助于医生更好地使用该工具和进行临床决策。美国设立了固定的FRAX?阈值，英国则是按年龄分层的阈值。国内对FRAX?的研究尚处于初级阶段，暂无特异的干预阈值，这在一定程度上阻碍了该工具在我国的推广使用。笔者回顾了国内外FRAX?对女性骨质疏松性骨折的预测能力、骨量异常的诊断能力、在合并其他疾病的女性人群中的应用和干预阈值的研究等最新成果，为临床医生了解FRAX?的研究进展、探索针对我国人群干预阈值奠定基础。     

Variance in 10-Year Fracture Risk Calculated With and Without T-Scores in Select Subgroups of Normal and Osteoporotic Patients

The World Health Organization fracture risk assessment tool (FRAX) uses clinical risk factors to predict the patient's 10-yr probability of sustaining a hip or other major osteoporosis-related fracture. Inclusion of the femoral neck T-score is optional in the calculation. We evaluated the impact of including the T-score in the calculation of fracture risk and resultant treatment recommendation. We retrospectively reviewed charts of 180 white women scanned on a Hologic dual-energy X-ray absorptiometry (DXA). FRAX scores were calculated with T-scores (FRAX+) and without T-scores (FRAX?). We compared the National Osteoporosis Foundation (NOF) treatment recommendations (≥20% risk of a major osteoporotic fracture or ≥3% risk of hip fracture for osteopenic patients) between FRAX+ and FRAX? scores. Agreement between FRAX+ and FRAX? was 89.4%. Disagreement occurred in 2 distinct subgroups of patients (10.6% of cases), that is, FRAX+ scores exceeded the NOF recommended treatment thresholds and FRAX? scores did not, or vice versa. One subgroup comprised older patients with normal T-scores for whom FRAX? scores exceeded the treatment threshold. The second subgroup comprised younger patients with high body mass index (BMI) and low T-scores for whom FRAX? scores did not exceed the treatment threshold. FRAX scores generated without T-scores may lead to treatment recommendations for patients who have normal bone mineral density and no treatment recommendations for patients who have osteoporosis. T-scores should be used for optimal application of FRAX.     

Clinical Risk Factors for Osteoporosis in Ireland and the UK: A Comparison of FRAX and QFractureScores

Recently two algorithms have become available to estimate the 10-year probability of fracture in patients suspected to have osteoporosis on the basis of clinical risk factors: the FRAX algorithm and QFractureScores algorithm (QFracture). The aim of this study was to compare the performance of these algorithms in a study of fracture patients and controls recruited from six centers in the United Kingdom and Ireland. A total of 246 postmenopausal women aged 50–85 years who had recently suffered a low-trauma fracture were enrolled and their characteristics were compared with 338 female controls who had never suffered a fracture. Femoral bone mineral density was measured by dual-energy X-ray absorptiometry, and fracture risk was calculated using the FRAX and QFracture algorithms. The FRAX algorithm yielded higher scores for fracture risk than the QFracture algorithm. Accordingly, the risk of major fracture in the overall study group was 9.5% for QFracture compared with 15.2% for FRAX. For hip fracture risk the values were 2.9% and 4.7%, respectively. The correlation between FRAX and QFracture was R = 0.803 for major fracture and R = 0.857 for hip fracture (P ≤ 0.0001). Both algorithms yielded high specificity but poor sensitivity for prediction of osteoporosis. We conclude that the FRAX and QFracture algorithms yield similar results in the estimation of fracture risk. Both of these tools could be of value in primary care to identify patients in the community at risk of osteoporosis and fragility fractures for further investigation and therapeutic intervention.     

桂西地区骨质疏松患者FRAX评分与体质量指数及外周血中钙、磷指标的相关性分析

目的探讨桂西地区骨质疏松患者FRAX评分与体质量指数及外周血中钙、磷指标的相关性。方法随机选取右江民族医学院附属医院2015年1~6月住院患者221例,根据纳入标准筛选出69例。诊断为骨质疏松患者33例,男12例,女21例;诊断为非骨质疏松患者36例,男18例,女18例。随访并计算FRAX评分、收集相关临床电解质指标后采用独立样本t检验分别统计分析骨质疏松组和非疏松组整体人群相关患者钙、磷离子值。多重线性回归分析未来10年骨折风险概率/体质量指数(PMOF/BMI)、10年内髋部骨折概率/体质量指数(PHF/BMI)之间的关系。研究桂西地区患者FRAX评分及BMI与外周血中钙、磷指标是否存在相应关系。结果在骨质疏松组患者和整体人群中,外周血钙、磷及年龄等因素与PMOF和PHF之间均没有相关性(各项P值均>0.05)。在骨质疏松组中,BMI与PMOF和PHF之间没有相关性(P值均>0.05)。但是在整体人群中,BMI与PMOF和PHF之间有线性相关性(P<0.05),并且随着BMI增加,PMOF和PHF的数值越来越小。结论骨质疏松患者外周血钙、磷指标与骨质疏松骨折风险无明显相关性。依据本试验统计学分析,钙、磷指标在本算法中不能作为桂西地区诊断骨质疏松骨折风险的依据;在整体人群中,BMI与PMOF和PHF之间呈现负向相关性,提示低BMI人群容易发生骨折。     

Performance of FRAX in Women with Breast Cancer Initiating Aromatase Inhibitor Therapy: A Registry-Based Cohort Study

FRAX was developed to predict 10-year probability of major osteoporotic fracture (MOF) and hip fracture in the general population. Aromatase inhibitors (AI) used in breast cancer induce loss in bone mineral density (BMD) and are reported to increase fracture risk. AI exposure is not a direct input to FRAX but is captured under “secondary osteoporosis”. To inform use of FRAX in women treated with AI, we used a population-based registry for the Province of Manitoba, Canada, to identify women aged ≥40 years initiating AI for breast cancer with at least 12 months’ AI exposure (n = 1775), women with breast cancer not receiving AI (n = 1016), and women from the general population (n = 34,205). Among AI users, fracture probability estimated without BMD (AI use coded as secondary osteoporosis) significantly overestimated risk (10-year observed/predicted ratio 0.56, 95% confidence interval [CI] 0.45–0.68; 10-year hip fracture observed/predicted ratio 0.33, 95% CI 0.18–0.49). However, when BMD was included in the fracture probability, there was no significant difference between observed and predicted fracture risk. In Cox proportional hazards models, FRAX stratified risk of MOF, hip, and any fracture equally well in all subgroups (p-interaction >0.1). When adjusted for FRAX score without BMD, with AI use coded as secondary osteoporosis, AI users were at significantly lower risk for MOF (hazard ratio [HR] = 0.78, 95% CI 0.64–0.95), hip fracture (HR = 0.46, 95% CI 0.29–0.73) and any fracture (HR = 0.75, 95% CI 0.63–0.89). AI use was no longer significantly associated with fractures when AI use was not entered as secondary osteoporosis in FRAX without BMD or when BMD was included in the FRAX calculation. In conclusion, FRAX scores stratify fracture risk equally well in women receiving AI therapy as in non-users, but including secondary osteoporosis as a risk factor for AI users overestimates fracture risk. Our results call this practice into question. © 2019 American Society for Bone and Mineral Research.