van Maurik Ingrid S, Zwan Marissa D, Tijms Betty M, Bouwman Femke H, Teunissen Charlotte E, Scheltens Philip, Wattjes Mike P, Barkhof Frederik, Berkhof Johannes, van der Flier Wiesje M
Department of Neurology and Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.
Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.
JAMA Neurol. 2017 Dec 1;74(12):1481-1491. doi: 10.1001/jamaneurol.2017.2712.
Biomarkers do not determine conversion to Alzheimer disease (AD) perfectly, and criteria do not specify how to take patient characteristics into account. Consequently, biomarker use may be challenging for clinicians, especially in patients with mild cognitive impairment (MCI).
To construct biomarker-based prognostic models that enable determination of future AD dementia in patients with MCI.
DESIGN, SETTING, AND PARTICIPANTS: This study is part of the Alzheimer's Biomarkers in Daily Practice (ABIDE) project. A total of 525 patients with MCI from the Amsterdam Dementia Cohort (longitudinal cohort, tertiary referral center) were studied. All patients had their baseline visit to a memory clinic from September 1, 1997, through August 31, 2014. Prognostic models were constructed by Cox proportional hazards regression with patient characteristics (age, sex, and Mini-Mental State Examination [MMSE] score), magnetic resonance imaging (MRI) biomarkers (hippocampal volume, normalized whole-brain volume), cerebrospinal fluid (CSF) biomarkers (amyloid-β1-42, tau), and combined biomarkers. Data were analyzed from November 1, 2015, to October 1, 2016.
Clinical end points were AD dementia and any type of dementia after 1 and 3 years.
Of the 525 patients, 210 (40.0%) were female, and the mean (SD) age was 67.3 (8.4) years. On the basis of age, sex, and MMSE score only, the 3-year progression risk to AD dementia ranged from 26% (95% CI, 19%-34%) in younger men with MMSE scores of 29 to 76% (95% CI, 65%-84%) in older women with MMSE scores of 24 (1-year risk: 6% [95% CI, 4%-9%] to 24% [95% CI, 18%-32%]). Three- and 1-year progression risks were 86% (95% CI, 71%-95%) and 27% (95% CI, 17%-41%) when MRI results were abnormal, 82% (95% CI, 73%-89%) and 26% (95% CI, 20%-33%) when CSF test results were abnormal, and 89% (95% CI, 79%-95%) and 26% (95% CI, 18%-36%) when the results of both tests were abnormal. Conversely, 3- and 1-year progression risks were 18% (95% CI, 13%-27%) and 3% (95% CI, 2%-5%) after normal MRI results, 6% (95% CI, 3%-9%) and 1% (95% CI, 0.5%-2%) after normal CSF test results, and 4% (95% CI, 2%-7%) and 0.5% (95% CI, 0.2%-1%) after combined normal MRI and CSF test results. The prognostic value of models determining any type of dementia were in the same order of magnitude although somewhat lower. External validation in Alzheimer's Disease Neuroimaging Initiative 2 showed that our models were highly robust.
This study provides biomarker-based prognostic models that may help determine AD dementia and any type of dementia in patients with MCI at the individual level. This finding supports clinical decision making and application of biomarkers in daily practice.
生物标志物并不能完美地确定是否会转化为阿尔茨海默病(AD),且相关标准未明确说明如何考虑患者特征。因此,生物标志物的应用对临床医生来说可能具有挑战性,尤其是对于轻度认知障碍(MCI)患者。
构建基于生物标志物的预后模型,以确定MCI患者未来是否会发展为AD痴呆。
设计、设置和参与者:本研究是日常实践中阿尔茨海默病生物标志物(ABIDE)项目的一部分。对来自阿姆斯特丹痴呆队列(纵向队列,三级转诊中心)的525例MCI患者进行了研究。所有患者在1997年9月1日至2014年8月31日期间到记忆诊所进行了基线检查。通过Cox比例风险回归构建预后模型,纳入患者特征(年龄、性别和简易精神状态检查表[MMSE]评分)、磁共振成像(MRI)生物标志物(海马体积、标准化全脑体积)、脑脊液(CSF)生物标志物(淀粉样β蛋白1-42、tau蛋白)以及联合生物标志物。数据于2015年11月1日至2016年10月1日进行分析。
临床终点为1年和3年后的AD痴呆以及任何类型的痴呆。
525例患者中,210例(40.0%)为女性,平均(标准差)年龄为67.3(8.4)岁。仅基于年龄、性别和MMSE评分,3年发展为AD痴呆的风险范围为:MMSE评分为29的年轻男性为26%(95%CI,19%-34%),至MMSE评分为24的老年女性为76%(95%CI,65%-84%)(1年风险:6%[95%CI,4%-9%]至24%[95%CI,1%-32%])。MRI结果异常时,3年和1年发展风险分别为86%(95%CI,71%-95%)和27%(95%CI,17%-41%);CSF检测结果异常时,分别为82%(95%CI,73%-89%)和26%(95%CI);两项检测结果均异常时,分别为89%(95%CI,79%-95%)和26%(95%CI,18%-36%)。相反,MRI结果正常后,3年和1年发展风险分别为18%(95%CI,13%-27%)和3%(95%CI,2%-5%);CSF检测结果正常后,分别为6%(95%CI,3%-9%)和1%(95%CI,0.5%-2%);MRI和CSF检测结果均正常后,分别为4%(95%CI,2%-7%)和0.5%(95%CI,0.2%-1%)。确定任何类型痴呆的模型的预后价值在相同数量级,尽管略低。阿尔茨海默病神经影像倡议2的外部验证表明我们的模型具有高度稳健性。
本研究提供了基于生物标志物的预后模型,可能有助于在个体水平上确定MCI患者的AD痴呆和任何类型的痴呆。这一发现支持临床决策以及生物标志物在日常实践中的应用。