Introduction: The cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-Cog) has been established internationally as an instrument for the assessment of treatment efficacy and cognitive performance in clinical trials. There is no data about the validity and characteristics of ADAS-Cog in Hungarian sample. This study is a part of the Hungarian standardization process of ADAS-Cog. It is crucial to examine the cognitive performance of patients with pseudodementia caused by depression (D) because of its' similarities with Alzheimer's disease (AK). The objective of the study was to analyze the characteristics of the cognitive subscale for further validation purposes. The study aimed at analyzing the ADAS-Cog performance of patients with D and AK in a Hungarian sample to make future studies more accurate through more exact differentiation between the two diseases.
Methods: Fourty-seven normal elderly control (KNT) subjects, 66 AK patients and 39 patients with D participated in the study. The mental state and the severity of depressive symptoms of the participants were assessed by the means of ADAS-Cog, Mini Mental State Examination (MMSE) and Beck Depression Inventory.
Results: The ADAS-Cog is sensitive to the cognitive decline of the depressed group (sensitivity=69.2%, specificity=89.4%, AUC=0.868, p>0.001). While the performance of the two patient groups differed from the KNT, the groups are overlapping and the characteristic of the ROC curve and the optimal cut-off point (D:11.8; AK:12.1) indicates that the differentiation is mediocre.
Conclusion: The results suggest that pseudodementia should be considered during the design of studies using ADASCog. Because the cognitive subscale can't accurately differentiate between AK and pseudodementia additional measures like BDI should be administered.