Engelborghs Sebastiaan, De Vreese Karen, Van de Casteele Tom, Vanderstichele Hugo, Van Everbroeck Bart, Cras Patrick, Martin Jean-Jacques, Vanmechelen Eugeen, De Deyn Peter Paul
Department of Neurology and Memory Clinic, Middelheim General Hospital (ZNA), Lindendreef 1, 2020 Antwerp, Belgium.
Neurobiol Aging. 2008 Aug;29(8):1143-59. doi: 10.1016/j.neurobiolaging.2007.02.016. Epub 2007 Apr 10.
To establish diagnostic performance of the cerebrospinal fluid (CSF) biomarkers beta-amyloid peptide (Abeta(1-42)), total tau-protein (T-tau) and tau phosphorylated at threonine 181 (P-tau(181P)) compared to clinical diagnosis, biomarker levels were determined in CSF samples from 100 autopsy-confirmed dementia and 100 control subjects. As the control and dementia groups were not age-matched and given the significant associations of biomarker concentrations with age in controls, age-corrected biomarker concentrations were calculated. New models were constructed by means of logistic regression. Using all biomarkers, dementia could be discriminated from controls (sensitivity (S)=86%, specificity (Sp)=89%). T-tau and Abeta(1-42) optimally discriminated Alzheimer's disease (AD) from other dementias (NONAD) and controls (S=90%, Sp=89%). AD was optimally discriminated from NONAD using P-tau(181P) and Abeta(1-42) (S=80%, Sp=93%). Diagnostic accuracy of the latter model (82.7%) was comparable to clinical diagnostic accuracy (81.6%) that was based on a whole clinical work-up (including imaging). Using this model, in cases with clinically doubtful diagnoses, a correct diagnosis would have been established in 4/6 autopsy-confirmed AD and 3/3 autopsy-confirmed NONAD cases. The value of biomarkers in differential dementia diagnosis was shown, using pathological diagnosis as a reference. New models have been developed, achieving sensitivity, specificity and diagnostic accuracy levels, consistently exceeding 80%.
为了确定脑脊液（CSF）生物标志物β-淀粉样肽（Abeta(1-42)）、总tau蛋白（T-tau）和苏氨酸181位点磷酸化的tau蛋白（P-tau(181P)）相对于临床诊断的诊断性能，对100例尸检确诊的痴呆患者和100例对照受试者的脑脊液样本中的生物标志物水平进行了测定。由于对照组和痴呆组年龄不匹配，且考虑到对照组中生物标志物浓度与年龄存在显著关联，因此计算了年龄校正后的生物标志物浓度。通过逻辑回归构建了新模型。使用所有生物标志物，可将痴呆与对照区分开（敏感性（S）=86%，特异性（Sp）=89%）。T-tau和Abeta(1-42)能最佳地区分阿尔茨海默病（AD）与其他痴呆（NONAD）及对照（S=90%，Sp=89%）。使用P-tau(181P)和Abeta(1-42)能最佳地区分AD与NONAD（S=80%，Sp=93%）。后一种模型的诊断准确性（82.7%）与基于全面临床检查（包括影像学检查）的临床诊断准确性（81.6%）相当。使用该模型，在临床诊断存疑的病例中，4/6例尸检确诊的AD病例和3/3例尸检确诊的NONAD病例能够得到正确诊断。以病理诊断为参考，显示了生物标志物在痴呆鉴别诊断中的价值。已开发出新模型，其敏感性、特异性和诊断准确性水平始终超过80%。
