Predictors of the Agreement between Diagnostic Instruments and Clinical Diagnosis of ASD in Adults without Intellectual Disability

Poster Presentation
Thursday, May 10, 2018: 5:30 PM-7:00 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
L. Fusar-Poli1,2, N. Brondino2, M. Rocchetti2, U. Provenzani2, S. Damiani2 and P. Politi2, (1)Department of Clinical and Experimental Medicine, Psychiatric Unit, University of Catania, Catania, Italy, (2)Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
Background: Diagnosing autism spectrum disorders (ASD) in adulthood often represents a challenge. Clinical diagnosis should be supported by the use of standardized tools, such as the Autism Diagnostic Observation Schedule (ADOS) or the Autism Diagnostic Interview (ADI).

Objectives: To evaluate potential predictors of the agreement between diagnostic instruments (ADOS-2 and ADI-R) and clinical diagnosis in a population of adults who were formally diagnosed with ASD for the first time.

Methods: After an extensive clinical evaluation, 95 adults with an IQ ≥ 70 were diagnosed with ASD according to DSM-5 criteria. ADOS-2 was separately administered to all participants and 81 caregivers underwent ADI-R interview. Binary logistic regressions were conducted to find potential predictors of the agreement (gender, age, IQ, severity levels of criteria A and B of DSM-5).

Results: Female gender was a negative predictor of the agreement between ADOS-2 and clinical diagnosis (B = -1.59, OR = 0.204, p = 0.03). IQ seemed to negatively predict the agreement between ADI-R and DSM-5 (B = -0.03, OR = 0.968, p = 0.04), while people with higher severity levels at criterion B better agreed with clinical diagnosis (B = 1.20, OR = 3.326, p = 0.03).

Conclusions: Clinicians’ training and experience remains of primary importance while assessing adults who could potentially belong to the autism spectrum. Women and individuals with higher IQ, in fact, seem to have more camouflaging strategies and less pronounced symptoms. In these subsamples, it is more difficult to correctly identify ASD only by means of standardized instruments.