Autism Symptom Clustering Scale

Background: Autism is a neurodevelopmental disorder that often has multiple medical and behavioral symptoms.   Autism is now estimated to occur at a rate of more than 1/500 [1], and is currently the focus of much basic research

Objectives: A major impediment to research in autism is the lack of clinical sub-typing and the need for instruments that can be employed to more carefully sub-type the disorder under examination, creating more homogeneity in  subject cohorts and less spurious variation in subsequent analysis.

Methods:  Given the multi-dimensional nature of autism, its symptoms and related co-morbidities, an Autism Symptom Cluster Index (ASCI) was developed to broadly measure clinical severity on a validated set of autism cases, guided by clinical interpretation.  A cohort of approximately 200 complete cases was used, with detailed information available on each subject. To develop the ASCI each symptom dimension was scored and incorporated into a weighted average to provide an overall score for each subject.

Results: The ASCI score was then shown to clearly differentiate the autism group from the PDD-NOS and Asperger’s groups. Sub-scale analysis was also conducted and demographic aspects investigated.

Conclusions: The broad nature of the ASD diagnosis is often a challenge for researchers as it introduces much heterogeneity into patient cohorts. The ASCI is an instrument based on individual symptomology that will help in the clinical sub-typing of ASD.