From the Stroke Research Group (A.A.A.O., H.S.M.), Clinical Neurosciences, University of Cambridge; MRC Biostatistics Unit (J.M.S.W.), Institute of Public Health, Cambridge; Institute of Health and Society (J.M.S.W.), Newcastle University, UK; Department of Neurology (A.M.T., E.M.C.v.L., F.-E.d.L.), Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Centre for Medical Neuroscience, Nijmegen, the Netherlands; Division of Neurogeriatrics (M.K., E.H., R.S.), Department of Neurology, Medical University of Graz; Institute for Medical Informatics (E.H.), Statistics and Documentation, Medical University of Graz, Austria; and Department of Psychology (R.G.M.), King's College, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Neurology. 2020 Mar 24;94(12):e1294-e1302. doi: 10.1212/WNL.0000000000009141. Epub 2020 Mar 2.
To determine whether a simple small vessel disease (SVD) score, which uses information available on rapid visual assessment of clinical MRI scans, predicts risk of cognitive decline and dementia, above that provided by simple clinical measures.
Three prospective longitudinal cohort studies (SCANS [St George's Cognition and Neuroimaging in Stroke], RUN DMC [Radboud University Nijmegen Diffusion Imaging and Magnetic Resonance Imaging Cohort], and the ASPS [Austrian Stroke Prevention Study]), which covered a range of SVD severity from mild and asymptomatic to severe and symptomatic, were included. In all studies, MRI was performed at baseline, cognitive tests repeated during follow-up, and progression to dementia recorded prospectively. Outcome measures were cognitive decline and onset of dementia during follow-up. We determined whether the SVD score predicted risk of cognitive decline and future dementia. We also determined whether using the score to select a group of patients with more severe disease would reduce sample sizes for clinical intervention trials.
In a pooled analysis of all 3 cohorts, the score improved prediction of dementia (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.81-0.89) compared with that from clinical risk factors alone (AUC, 0.76; 95% CI, 0.71-0.81). Predictive performance was higher in patients with more severe SVD. Power calculations showed selecting patients with a higher score reduced sample sizes required for hypothetical clinical trials by 40%-66% depending on the outcome measure used.
A simple SVD score, easily obtainable from clinical MRI scans and therefore applicable in routine clinical practice, aided prediction of future dementia risk.
确定一种简单的小血管疾病（SVD）评分，该评分使用快速临床 MRI 扫描的直观评估信息，是否能比简单的临床测量提供更好的认知能力下降和痴呆风险预测。
纳入了三项前瞻性纵向队列研究（SCANS[圣乔治中风认知和神经影像学]、RUN DMC[拉德堡德大学奈梅亨弥散成像和磁共振成像队列]和 ASPS[奥地利中风预防研究]），这些研究涵盖了从轻度无症状到重度有症状的一系列 SVD 严重程度。所有研究均在基线时进行 MRI 检查，在随访期间重复认知测试，并前瞻性记录进展为痴呆的情况。主要终点是随访期间的认知能力下降和痴呆发病。我们确定 SVD 评分是否可以预测认知能力下降和未来的痴呆风险。我们还确定了使用评分选择一组疾病更严重的患者是否会减少临床干预试验的样本量。
在对所有 3 项队列研究的汇总分析中，该评分提高了痴呆的预测准确性（曲线下面积 [AUC]，0.85；95%置信区间 [CI]，0.81-0.89），优于仅基于临床危险因素的预测（AUC，0.76；95% CI，0.71-0.81）。在 SVD 更严重的患者中，预测性能更高。根据使用的结局指标，计算显示选择评分较高的患者可以减少假设临床试验所需的样本量 40%-66%。
一种简单的 SVD 评分，可从临床 MRI 扫描中轻松获得，因此可应用于常规临床实践，有助于预测未来痴呆风险。
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