Abrahantes José Cortiñas, Aerts Marc, van Everbroeck Bart, Saegerman Claude, Berkvens Dirk, Geys Helena, Mintiens Koen, Roels Stefan, Cras Patrick
Center for Statistics, Hasselt University, Agoralaan Gebouw D, Diepenbeek, Belgium.
Eur J Epidemiol. 2007;22(7):457-65. doi: 10.1007/s10654-007-9146-x. Epub 2007 Jun 21.
Creutzfeldt-Jakob disease (CJD) is a rare and fatal neurodegenerative disease of unknown cause. Patients are usually aged between 50 and 75 and typical clinical features include rapidly progressive dementia associated with myoclonus and a characteristic electroencephalographic pattern. Neuropathological examination reveals cortical spongiform change, hence the term 'spongiform encephalopathy'. Several statistical techniques were applied to classify patients with sporadic CJD (sCJD), based on clinical and neuropathological investigation. We focus on the classification of neuropathologically confirmed sCJD patients. In order to obtain a classification rule that correctly classifies this type of patients and at the same time controls the overall error rate, we apply several classification techniques, which in general, produce comparable results. The boosting method produces the best results and the variable 14-3-3 protein in cerebrospinal fluid plays the most important role in the prediction of neuropathologically confirmed sCJD.
克雅氏病(CJD)是一种病因不明的罕见致命性神经退行性疾病。患者通常年龄在50至75岁之间,典型临床特征包括与肌阵挛相关的快速进展性痴呆以及特征性脑电图模式。神经病理学检查显示皮质海绵状改变,因此有“海绵状脑病”这一术语。基于临床和神经病理学研究,应用了几种统计技术对散发性克雅氏病(sCJD)患者进行分类。我们专注于对经神经病理学确诊的sCJD患者进行分类。为了获得能正确分类这类患者并同时控制总体错误率的分类规则,我们应用了几种分类技术,总体而言,这些技术产生的结果相当。提升方法产生的结果最佳,脑脊液中的14-3-3蛋白在经神经病理学确诊的sCJD预测中起最重要作用。