Predicting risk of osteoporotic fracture in men and women in England and Wales: prospective derivation and validation of QFractureScores.
Predicting risk of osteoporotic fracture in men and women in England and Wales: prospective derivation and validation of QFractureScores.
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DOI：
10.1136/bmj.b4229
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发表时间：
2009-11-19
期刊：
影响因子：
--
通讯作者：
Coupland C
中科院分区：
文献类型：
--
作者：
Hippisley-Cox J;Coupland C
目的开发和验证两种新的骨折风险算法（QFractureScores），用于估计10年内腰椎骨折或髋部骨折的个体风险。设计前瞻性开放队列研究，从357个一般实践中常规收集数据，以制定评分，并从178个实践中验证评分。在英格兰和威尔士设置一般做法。在推导队列中，年龄在30-85岁的女性1183663人和男性1174232人，分别贡献了7898208和8049306人年的观察。女性有24 350例和男性有7 934例腰椎骨折，女性有9 302例和男性有5 424例髋部骨折。主要观察指标：在全科医疗记录中记录的第一次（事件）诊断为骨质疏松性骨折（椎骨、桡骨远端或髋部）和偶发髋部骨折。结果激素替代疗法（HRT）的使用、年龄、体重指数（BMI）、吸烟状况、记录的饮酒情况、父母骨质疏松症史、类风湿性关节炎、心血管疾病、2型糖尿病、哮喘、三环类抗抑郁药、皮质类固醇、福尔斯史、更年期症状、慢性肝病、胃肠道吸收不良、和其他内分泌疾病与女性骨质疏松性骨折的风险显著且独立相关。一些变量与腰椎骨折的风险显著相关，但与髋部骨折的风险无关。男性骨质疏松症和髋部骨折的预测因素包括年龄、BMI、吸烟状况、饮酒记录、类风湿性关节炎、心血管疾病、2型糖尿病、哮喘、三环类抗抑郁药、皮质类固醇、福尔斯史和肝病。髋部骨折算法在男性和女性中的表现最好。它解释了女性变异的63.94%和男性变异的63.19%。女性髋部骨折和男性髋部骨折的D统计值最高，分别为2.73和2.68，是髋部骨折相应值的2倍以上。髋部骨折的ROC统计值也很高：女性为0.89，男性为0.86，而骨质疏松性骨折结局分别为0.79和0.69。这些算法经过很好的校准，预测的风险与观察到的风险密切匹配。与FRAX（骨折风险评估）算法相比，髋部骨折的QFractureScore也具有良好的区分和校准性能。结论：这些新算法可以预测骨折的风险在初级保健人群在英国没有实验室测量，因此适用于临床环境和自我评估（www.qfracture.org）。QFractureScores可用于识别骨折高风险患者，这些患者可能从干预措施中受益，以降低风险。
Objective To develop and validate two new fracture risk algorithms (QFractureScores) for estimating the individual risk of osteoporotic fracture or hip fracture over 10 years. Design Prospective open cohort study with routinely collected data from 357 general practices to develop the scores and from 178 practices to validate the scores. Setting General practices in England and Wales. Participants 1 183 663 women and 1 174 232 men aged 30-85 in the derivation cohort, who contributed 7 898 208 and 8 049 306 person years of observation, respectively. There were 24 350 incident diagnoses of osteoporotic fracture in women and 7934 in men, and 9302 incident diagnoses of hip fracture in women and 5424 in men. Main outcome measures First (incident) diagnosis of osteoporotic fracture (vertebral, distal radius, or hip) and incident hip fracture recorded in general practice records. Results Use of hormone replacement therapy (HRT), age, body mass index (BMI), smoking status, recorded alcohol use, parental history of osteoporosis, rheumatoid arthritis, cardiovascular disease, type 2 diabetes, asthma, tricyclic antidepressants, corticosteroids, history of falls, menopausal symptoms, chronic liver disease, gastrointestinal malabsorption, and other endocrine disorders were significantly and independently associated with risk of osteoporotic fracture in women. Some variables were significantly associated with risk of osteoporotic fracture but not with risk of hip fracture. The predictors for men for osteoporotic and hip fracture were age, BMI, smoking status, recorded alcohol use, rheumatoid arthritis, cardiovascular disease, type 2 diabetes, asthma, tricyclic antidepressants, corticosteroids, history of falls, and liver disease. The hip fracture algorithm had the best performance among men and women. It explained 63.94% of the variation in women and 63.19% of the variation in men. The D statistic values for discrimination were highest for hip fracture in women (2.73) and men (2.68) and were over twice the magnitude of the corresponding values for osteoporotic fracture. The ROC statistics for hip fracture were also high: 0.89 in women and 0.86 for men versus 0.79 and 0.69, respectively, for the osteoporotic fracture outcome. The algorithms were well calibrated with predicted risks closely matching observed risks. The QFractureScore for hip fracture also had good performance for discrimination and calibration compared with the FRAX (fracture risk assessment) algorithm. Conclusions These new algorithms can predict risk of fracture in primary care populations in the UK without laboratory measurements and are therefore suitable for use in both clinical settings and for self assessment (www.qfracture.org). QFractureScores could be used to identify patients at high risk of fracture who might benefit from interventions to reduce their risk.
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