A New Decision Tree Combining Abeta 1-42 and p-Tau Levels in Alzheimer's Diagnosis

The objective of this work was to improve the clinical diagnosis of Alzheimer's disease (AD) by proposing a simple decision tree based on three major biomarkers of AD found in the cerebrospinal fluid (CSF): amyloid peptide Aβ1- 42, total Tau (t-Tau) and Tau phosphorylated at Thr181 (p-Tau). Two consecutive cohorts comprising 548 patients in total were recruited by the Memory and Neurology Clinics at Lille University Hospital (France). These included 293 patients with AD, 171 patients with other dementias and 84 healthy controls. All patients underwent lumbar puncture for the assessment of CSF concentrations of Aβ1-42, t-Tau and p-Tau. International criteria for dementias were used for diagnosis by investigators blind to CSF test results. To identify the combination of biomarkers that best predicted the 3 diagnoses, we used the CHAID decision tree method with the first cohort. Our analysis yielded a two-step decision tree, with a first stratification step based on the Aβ1–42/p-Tau ratio of the CSF, and a second step based on CSF p-Tau concentrations. The second cohort was then used to determine the power (0.618), sensitivity (82%) and specificity (81%) of this tree in AD diagnosis. These were found to be at least as high as those of other known algorithms based on the three CSF biomarkers, Aβ1-42, t-Tau and p-Tau. For the first time, diagnostic rules for AD based on CSF variables were compared in a single study. Our findings indicate that the measurement of Aβ1-42 and p-Tau levels in the CSF is sufficient to diagnose AD.