Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia.
Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia.
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DOI：
10.1186/s13195-017-0301-7
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发表时间：
2017-10-10
期刊：
影响因子：
--
通讯作者：
Kornhuber J
中科院分区：
文献类型：
--
作者：
Frölich L;Peters O;Lewczuk P;Gruber O;Teipel SJ;Gertz HJ;Jahn H;Jessen F;Kurz A;Luckhaus C;Hüll M;Pantel J;Reischies FM;Schröder J;Wagner M;Rienhoff O;Wolf S;Bauer C;Schuchhardt J;Heuser I;Rüther E;Henn F;Maier W;Wiltfang J;Kornhuber J
轻度认知障碍（MCI）向阿尔茨海默病（AD）痴呆的进展可以通过认知、神经影像学和脑脊液（CSF）标志物来预测。由于大多数生物标记显示互补的信息，生物标记的组合可能会增加预测能力。我们研究了迷你精神状态检查（MMSE）、临床痴呆评分(CDR)-方框和、单词列表延迟自由回忆（CERAD）测试组、海马体积（HCV）、淀粉样蛋白- β - 42 （a β42）、淀粉样蛋白- β - 40 （a β40）水平、a β42/ a β40之比、脑脊液中磷酸化tau蛋白和总tau蛋白（t-Tau）水平哪种组合最能预测MCI向AD痴呆的短期转化。我们使用了115个来自“痴呆能力网络”的MCI患者的完整数据集，这是一项德国多中心队列研究，每年随访3年。MCI的广义定义包括健忘症和非健忘症。已知的预测MCI患者进展的变量是先验选择的。采用受试者工作特征（ROC）曲线分析对9个个体预测因子进行比较。通过对具有线性核的支持向量机进行自举包装，分析了五种最佳二参数、三参数和四参数组合的ROC曲线是否具有显著的优越性。在给定灵敏度为85%的情况下，通过比较不同分类器的特异性来检验组合的增量值是否具有统计学意义。在115名受试者中，28名（24.3%）MCI患者在平均25.5个月的随访期内进展为AD痴呆。基线时，MCI- ad患者与稳定型MCI患者在年龄和性别分布上没有差异，但受教育程度较低。两组在基线时所有单一生物标志物均有显著差异。各预测因子的ROC曲线下面积（AUC）在0.66 ~ 0.77之间，各预测因子均优于Aβ40。两参数组合的AUC范围为0.77 ~ 0.81。三参数组合的AUC范围为0.80 ~ 0.83，四参数组合的AUC范围为0.81 ~ 0.82。没有任何预测因子组合显著优于两个最佳的单一预测因子（HCV和t-Tau）。当通过将灵敏度固定在85%来最大化AUC差异时，2 - 4参数组合优于单独使用HCV。在识别最有可能进展为AD痴呆的MCI患者时，两种神经退行性疾病生物标志物（如HCV和t-Tau）的组合并不优于单一参数，尽管随着生物标志物组合的增加，统计指标逐渐增加。这可能对临床诊断和选择参与临床试验的受试者有影响。
The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. We used 115 complete datasets from MCI patients of the “Dementia Competence Network”, a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone. A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.
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影响因子：
4.2
作者：
Da, Xiao;Toledo, Jon B.;Zee, Jarcy;Wolk, David A.;Xie, Sharon X.;Ou, Yangming;Shacklett, Amanda;Parmpi, Paraskevi;Shaw, Leslie;Trojanowski, John Q.;Davatzikos, Christos
通讯作者：
Davatzikos, Christos
影响因子：
4.2
作者：
Ewers M;Walsh C;Trojanowski JQ;Shaw LM;Petersen RC;Jack CR Jr;Feldman HH;Bokde AL;Alexander GE;Scheltens P;Vellas B;Dubois B;Weiner M;Hampel H;North American Alzheimer's Disease Neuroimaging Initiative (ADNI)
通讯作者：
North American Alzheimer's Disease Neuroimaging Initiative (ADNI)
在早期发现阿尔茨海默氏病时，磁共振成像可改善脑脊液生物标志物。
DOI：
10.3233/jad-2009-0968
发表时间：
2009
期刊：
Journal of Alzheimer's disease : JAD
影响因子：
--
作者：
Brys M;Glodzik L;Mosconi L;Switalski R;De Santi S;Pirraglia E;Rich K;Kim BC;Mehta P;Zinkowski R;Pratico D;Wallin A;Zetterberg H;Tsui WH;Rusinek H;Blennow K;de Leon MJ
通讯作者：
de Leon MJ
影响因子：
--
作者：
Gomar, Jesus J.;Bobes-Bascaran, Maria T.;Goldberg, Terry E.
通讯作者：
Goldberg, Terry E.
影响因子：
14
作者：
Duits, Flora H.;Martinez-Lage, Pablo;Blennow, Kaj
通讯作者：
Blennow, Kaj