Amyotrophic lateral sclerosis - frontotemporal spectrum disorder (ALS-FTSD): Revised diagnostic criteria

Abstract

This article presents the revised consensus criteria for the diagnosis of frontotemporal dysfunction in amyotrophic lateral sclerosis (ALS) based on an international research workshop on frontotemporal dementia (FTD) and ALS held in London, Canada in June 2015. Since the publication of the Strong criteria, there have been considerable advances in the understanding of the neuropsychological profile of patients with ALS. Not only is the breadth and depth of neuropsychological findings broader than previously recognised - - including deficits in social cognition and language - but mixed deficits may also occur. Evidence now shows that the neuropsychological deficits in ALS are extremely heterogeneous, affecting over 50% of persons with ALS. When present, these deficits significantly and adversely impact patient survival. It is the recognition of this clinical heterogeneity in association with neuroimaging, genetic and neuropathological advances that has led to the current re-conceptualisation that neuropsychological deficits in ALS fall along a spectrum. These revised consensus criteria expand upon those of 2009 and embrace the concept of the frontotemporal spectrum disorder of ALS (ALS-FTSD).

Keywords: Amyotrophic lateral sclerosis; behaviour; cognition; frontotemporal dementia; genetics; neuropsychology.

Figure 1.

Schematic of levels of investigation. The revised criteria are designed to address the need for rapid, easily applied tools that can be used in the clinical setting (Level I) through to assessment tools that are more appropriate to research studies (Level III). Levels II and III require formal neuropsychological and speech and language expertise to implement, reflect higher statistical complexity, and include tests that may require further validation in the ALS population. Level II is an intermediary level which can be applied in clinical trials and would be appropriate to be included in clinical case reports as minimum datasets.