Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study
Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study
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DOI：
10.1136/bmj.39261.471806.55
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发表时间：
2007-07-21
影响因子：
105.7
通讯作者：
Brindle, Peter
中科院分区：
文献类型：
--
作者：
Hippisley-Cox, Julia;Coupland, Carol;Brindle, Peter
目的：为英国推导一种新的心血管疾病风险评分（QRISK），并对照已确立的弗雷明汉心血管疾病算法以及新开发的苏格兰评分（ASSIGN）验证其性能。
设计：利用从全科医疗常规收集的数据进行前瞻性开放队列研究。
地点：为QRESEARCH数据库提供数据的英国医疗机构。
参与者：推导队列包括128万名年龄在35 - 74岁的患者，他们于1995年1月1日至2007年4月1日在318家医疗机构注册，且无糖尿病和现患心血管疾病。验证队列包括来自160家医疗机构的61万名患者。
主要结局指标：首次记录的心血管疾病诊断（1995年1月1日至2007年4月1日期间的发病诊断）：心肌梗死、冠心病、中风和短暂性脑缺血发作。风险因素包括年龄、性别、吸烟状况、收缩压、血清总胆固醇与高密度脂蛋白的比率、体重指数、一级亲属中年龄小于60岁的冠心病家族史、贫困地区衡量指标以及现有的降压治疗。
结果：在推导队列中开发了一种心血管疾病风险算法（QRISK）。在验证队列中，观察到女性10年心血管事件风险为6.60%（95%置信区间6.48% - 6.72%），男性为9.28%（9.14% - 9.43%）。总体而言，弗雷明汉算法在10年时高估心血管疾病风险35%，ASSIGN高估36%，QRISK高估0.4%。QRISK的判别指标往往高于弗雷明汉算法，并且相较于弗雷明汉或ASSIGN模型，它对英国人群的校准更好。使用QRISK，年龄在35 - 74岁的患者中有8.5%处于高风险（10年风险≥20%），而使用弗雷明汉算法时为13%，使用ASSIGN时为14%。使用QRISK，年龄在64 - 75岁的女性中有34%、男性中有73%处于高风险，而根据弗雷明汉算法分别为24%和86%。基于QRISK对2005年英国的估计，年龄在35 - 74岁的高风险患者有320万，弗雷明汉算法预测为470万，ASSIGN为510万。总体而言，在验证数据集中有53668名患者（占总数的9%）使用QRISK与使用弗雷明汉算法相比会从高风险重新分类为低风险或反之。
结论：QRISK在判别方面至少与弗雷明汉模型表现相当，并且相较于弗雷明汉模型或ASSIGN，对英国人群的校准更好。QRISK可能提供更合适的风险估计，以帮助根据年龄、性别和社会贫困状况识别高风险患者。因此，它可能是一种更公平的工具，用于为管理决策提供信息，并帮助确保治疗针对最有可能受益的人群。它包含了额外的变量，这些变量可改善有阳性家族史或正在接受降压治疗的患者的风险估计。然而，由于验证是在与推导算法的人群相似的人群中进行的，它可能具有“主场优势”。因此，需要在其他人群中进一步验证。
Objective To derive a new cardiovascular disease risk score (QRISK) for the United Kingdom and to validate its performance against the established Framingham cardiovascular disease algorithm and a newly developed Scottish score (ASSIGN).Design Prospective open cohort study using routinely collected data from general practice.Setting UK practices contributing to the QRESEARCH database.Participants The derivation cohort consisted of 1.28 million patients, aged 35-74 years, registered at 318 practices between 1 January 1995 and 1 April 2007 and who were free of diabetes and existing cardiovascular disease. The validation cohort consisted of 0.61 million patients from 160 practices.Main outcome measures First recorded diagnosis of cardiovascular disease (incident diagnosis between 1 January 1995 and 1 April 2007): myocardial infarction, coronary heart disease, stroke, and transient ischaemic attacks. Risk factors were age, sex, smoking status, systolic blood pressure, ratio of total serum cholesterol to high density lipoprotein, body mass index, family history of coronary heart disease in first degree relative aged less than 60, area measure of deprivation, and existing treatment with antihypertensive agent.Results A cardiovascular disease risk algorithm (QRISK) was developed in the derivation cohort. In the validation cohort the observed 10 year risk of a cardiovascular event was 6.60% (95% confidence interval 6.48% to 6.72%) in women and 9.28% (9.14% to 9.43%) in men. Overall the Framingham algorithm over-predicted cardiovascular disease risk at 10 years by 35%, ASSIGN by 36%, and QRISK by 0.4%. Measures of discrimination tended to be higher for QRISK than for the Framingham algorithm and it was better calibrated to the UK population than either the Framingham or ASSIGN models. With QRISK 8.5% of patients aged 35-74 are at high risk (>= 20% risk over 10 years) compared with 13% when using the Framingham algorithm and 14% when using ASSIGN. With QRISK 34% of women and 73% of men aged 64-75 would be at high risk compared with 24% and 86% according to the Framingham algorithm. UK estimates for 2005 based on QRISK give 3.2 million patients aged 35-74 at high risk, with the Framingham algorithm predicting 4.7 million and ASSIGN 5.1 million. Overall, 53 668 patients in the validation dataset (9% of the total) would be reclassified from high to low risk or vice versa using QRISK compared with the Framingham algorithm.Conclusion QRISK performed at least as well as the Framingham model for discrimination and was better calibrated to the UK population than either the Framingham model or ASSIGN. QRISK is likely to provide more appropriate risk estimates to help identify high risk patients on the basis of age, sex, and social deprivation. It is therefore likely to be a more equitable too[ to inform management decisions and help ensure treatments are directed towards those most likely to benefit. It includes additional variables which improve risk estimates for patients with a positive family history or those on antihypertensive treatment. However, since the validation was performed in a similar population to the population from which the algorithm was derived, it potentially has a "home advantage." Further validation in other populations is therefore required.