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65岁及以上人群广泛脑白质病变的先验风险模型的开发与验证:第戎MRI研究

Development and validation of a priori risk model for extensive white matter lesions in people age 65 years or older: the Dijon MRI study.

作者信息

Tully Phillip J, Qchiqach Sarah, Pereira Edwige, Debette Stephanie, Mazoyer Bernard, Tzourio Christophe

机构信息

Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, CHU Bordeaux, F-33000 Bordeaux, France.

UMR5293, Groupe d'Imagerie Neurofonctionnelle, University Bordeaux, Institut des Maladies Neurodégénératives, Bordeaux, France.

出版信息

BMJ Open. 2017 Dec 29;7(12):e018328. doi: 10.1136/bmjopen-2017-018328.

Abstract

OBJECTIVES

The objective was to develop and validate a risk model for the likelihood of extensive white matter lesions (extWML) to inform clinicians on whether to proceed with or forgo diagnostic MRI.

DESIGN

Population-based cohort study and multivariable prediction model.

SETTING

Two representative samples from France.

PARTICIPANTS

Persons aged 60-80 years without dementia or stroke. Derivation sample n=1714; validation sample n=789.

PRIMARY AND SECONDARY OUTCOME MEASURES

Volume of extWML (log cm) was obtained from T2-weighted images in a 1.5 T scanner. 20 candidate risk factors for extWML were evaluated with the C-statistic. Secondary outcomes in validation included incident stroke over 12 years follow-up.

RESULTS

The multivariable prediction model included six clinical risk factors (C-statistic=0.61). A cut-off of 7 points on the multivariable prediction model yielded the optimum balance in sensitivity 63.7% and specificity 54.0% and the negative predictive value was high (81.8%), but the positive predictive value was low (31.5%). In further validation, incident stroke risk was associated with continuous scores on the multivariable prediction model (HR 1.02; 95% CI 1.01 to 1.04, P=0.02) and dichotomised scores from the multivariable prediction model (HR 1.28; 95% CI 1.02 to 1.60, P=0.03).

CONCLUSIONS

A simple clinical risk equation for WML constituted by six variables can inform decisions whether to proceed with or forgo brain MRI. The high-negative predictive value demonstrates potential to reduce unnecessary MRI in the population aged 60-80 years.

摘要

目的

开发并验证一个用于预测广泛脑白质病变(extWML)可能性的风险模型,以便为临床医生提供信息,辅助其决定是否进行诊断性磁共振成像(MRI)检查。

设计

基于人群的队列研究及多变量预测模型。

设置

来自法国的两个代表性样本。

参与者

年龄在60 - 80岁之间、无痴呆或中风的人群。推导样本n = 1714;验证样本n = 789。

主要和次要结局指标

通过1.5T扫描仪的T2加权图像获取extWML的体积(log cm)。使用C统计量评估20个extWML的候选风险因素。验证中的次要结局包括12年随访期内的中风发生率。

结果

多变量预测模型包含六个临床风险因素(C统计量 = 0.61)。多变量预测模型中7分的截断值在敏感性(63.7%)和特异性(54.0%)之间产生了最佳平衡,阴性预测值较高(81.8%),但阳性预测值较低(31.5%)。在进一步验证中,中风发生风险与多变量预测模型的连续评分相关(风险比1.02;95%置信区间1.01至1.04,P = 0.02),也与多变量预测模型的二分评分相关(风险比1.28;95%置信区间1.02至1.60,P = 0.03)。

结论

一个由六个变量构成的简单的WML临床风险方程可为是否进行脑部MRI检查的决策提供参考。较高的阴性预测值表明该模型有潜力减少60 - 80岁人群中不必要的MRI检查。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b33b/5778304/04b66155acd4/bmjopen-2017-018328f01.jpg

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