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利用临床和影像学指标预测明显亨廷顿病:一项前瞻性观察研究。

Prediction of manifest Huntington's disease with clinical and imaging measures: a prospective observational study.

机构信息

Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Neurology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Psychology, University of Iowa, Iowa City, IA, USA.

Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, IA, USA.

出版信息

Lancet Neurol. 2014 Dec;13(12):1193-201. doi: 10.1016/S1474-4422(14)70238-8. Epub 2014 Nov 3.

Abstract

BACKGROUND

Although the association between cytosine-adenine-guanine (CAG) repeat length and age at onset of Huntington's disease is well known, improved prediction of onset would be advantageous for clinical trial design and prognostic counselling. We compared various measures for tracking progression and predicting conversion to manifest Huntington's disease.

METHODS

In this prospective observational study, we assessed the ability of 40 measures in five domains (motor, cognitive, psychiatric, functional, and imaging) to predict time to motor diagnosis of Huntington's disease, accounting for CAG repeat length, age, and the interaction of CAG repeat length and age. Eligible participants were individuals from the PREDICT-HD study (from 33 centres in six countries [USA, Canada, Germany, Australia, Spain, UK]) with the gene mutation for Huntington's disease but without a motor diagnosis (a rating below 4 on the diagnostic confidence level from the 15-item motor assessment of the Unified Huntington's Disease Rating Scale). Participants were followed up between September, 2002, and July, 2014. We used joint modelling of longitudinal and survival data to examine the extent to which baseline and change of measures analysed separately was predictive of CAG-adjusted age at motor diagnosis.

FINDINGS

1078 individuals with a CAG expansion were included in this analysis. Participants were followed up for a mean of 5·1 years (SD 3·3, range 0·0-12·0). 225 (21%) of these participants received a motor diagnosis of Huntington's disease during the study. 37 of 40 cross-sectional and longitudinal clinical and imaging measures were significant predictors of motor diagnosis beyond CAG repeat length and age. The strongest predictors were in the motor, imaging, and cognitive domains: an increase of one SD in total motor score (motor domain) increased the risk of a motor diagnosis by 3·07 times (95% CI 2·26-4·16), a reduction of one SD in putamen volume (imaging domain) increased risk by 3·32 times (2·37-4·65), and a reduction of one SD in Stroop word score (cognitive domain) increased risk by 2·32 times (1·88-2·87).

INTERPRETATION

Prediction of diagnosis of Huntington's disease can be improved beyond that obtained by CAG repeat length and age alone. Such knowledge about potential predictors of manifest Huntington's disease should inform discussions about guidelines for diagnosis, prognosis, and counselling, and might be useful in guiding the selection of participants and outcome measures for clinical trials.

FUNDING

US National Institutes of Health, US National Institute of Neurological Disorders and Stroke, and CHDI Foundation.

摘要

背景

尽管胞嘧啶-腺嘌呤-鸟嘌呤(CAG)重复序列长度与亨廷顿病发病年龄之间的关联是众所周知的,但更好地预测发病时间将有利于临床试验设计和预后咨询。我们比较了五种领域(运动、认知、精神、功能和影像学)中的 40 种指标来预测向明显亨廷顿病转化的时间,同时考虑了 CAG 重复序列长度、年龄以及 CAG 重复序列长度与年龄的相互作用。

方法

在这项前瞻性观察性研究中,我们评估了来自 33 个中心(来自美国、加拿大、德国、澳大利亚、西班牙和英国的 6 个国家)的 PREDICT-HD 研究中 40 种指标的能力,这些参与者均携带亨廷顿病基因突变,但没有运动诊断(统一亨廷顿病评定量表的 15 项运动评估中诊断置信水平评分低于 4 分)。参与者的随访时间为 2002 年 9 月至 2014 年 7 月。我们使用纵向和生存数据的联合模型来检验单独分析基线和变化的指标在多大程度上可以预测 CAG 调整后的运动诊断年龄。

结果

这项分析共纳入了 1078 名携带 CAG 扩展的个体。参与者的平均随访时间为 5.1 年(标准差 3.3,范围 0.0-12.0)。在研究期间,其中 225 名(21%)参与者被诊断为亨廷顿病。除 CAG 重复序列长度和年龄外,40 种横断面和纵向临床及影像学指标中有 37 种是运动诊断的显著预测指标。最强的预测指标存在于运动、影像学和认知领域:运动评分(运动领域)增加一个标准差会使运动诊断的风险增加 3.07 倍(95%CI 2.26-4.16),纹状体体积(影像学领域)减少一个标准差会使风险增加 3.32 倍(2.37-4.65),Stroop 单词评分(认知领域)减少一个标准差会使风险增加 2.32 倍(1.88-2.87)。

解释

除了 CAG 重复序列长度和年龄之外,还可以提高对亨廷顿病诊断的预测。这些关于明显亨廷顿病潜在预测因素的知识应该有助于讨论诊断、预后和咨询指南,并可能有助于指导临床试验的参与者选择和结果测量。

资金来源

美国国立卫生研究院、美国国立神经病学和中风研究所和 CHDI 基金会。

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