Establishing normative data for the evaluation of cognitive performance in Huntington's disease considering the impact of gender, age, language, and education.

Abstract

A declining cognitive performance is a hallmark of Huntington's disease (HD). The neuropsychological battery of the Unified HD Rating Scale (UHDRS'99) is commonly used for assessing cognition. However, there is a need to identify and minimize the impact of confounding factors, such as language, gender, age, and education level on cognitive decline. Aim is to provide appropriate, normative data to allow clinicians to identify disease-associated cognitive decline in diverse HD populations by compensating for the impact of confounding factors METHODS: Sample data, N = 3267 (60.5% females; mean age of 46.9years (SD = 14.61, range 18-86) of healthy controls were used to create a normative dataset. For each neuropsychological test, a Bayesian generalized additive model with age, education, gender, and language as predictors was constructed to appropriately stratify the normative dataset. With advancing age, there was a non-linear decline in cognitive performance. In addition, performance was dependent on educational levels and language in all tests. Gender had a more limited impact. Standardized scores have been calculated to ease the interpretation of an individual's test outcome. A web-based online tool has been created to provide free access to normative data. For defined neuropsychological tests, the impact of gender, age, education, and language as factors confounding disease-associated cognitive decline can be minimized at the level of a single patient examination.