Diagnostic Instruments for EARLY IDENTIFICATION of AUTISM Spectrum Disorders

Background: Recent progress has been made in the early identification and diagnosis of children with Autism Spectrum Disorders (ASDs) (Fombonne & De Giacomo, 2000; van Daalen et al., 2009). On this basis, early identification of children with ASDs has come to be recognized as a critical aspect of their medical management and treatment (Itzchack & Zachor, 2009). However, the convergent validity of different tools for early diagnosis requires further investigation.

Objectives: The purpose of the current study was to investigate the relationships among four widely used diagnostic measures for ASDs in toddlers: ADOS-G, ADI-R, STAT, and clinical judgment based on DSM-IV criteria.
Methods: The participants were 43 children with ASDs: 22 with a clinical diagnosis of Autism, 15 of PDD-NOS and 6 with Asperger syndrome (35 male, 8 female, mean chron. age= 48 months, mean developmental age= 22 months). The children were diagnosed in terms of clinical judgment based on DSM-IV criteria and with the ADOS-G, ADI-R and the STAT. We calculated the sensitivity, the specificity, and the positive predictive value of the three instruments (ADI-R, ADOS-G, STAT) measured against DSM-IV-based clinical judgment for diagnosing ASDs in very young children.

Results: Based on Cohen’s kappa, there was significant agreement for the diagnosis of ASDs between clinical judgment and ADOS-G (k=0.672, p<.001), ADI-R (k=0.811, p<.001), STAT (k=0.765, p<.001), and  between STAT and ADOS (k=1.100, p<.001). Sensitivity, specificity, and positive predictive values had similar rates for the ADOS. ADI-R had lower sensitivity but equal specificity compared to the other measures. STAT specificity was slightly higher for the diagnosis of PDD-NOS.

Conclusions: The results indicate that the ADOS-G, ADI, STAT and the clinical judgment based on DSM-IV criteria converge in showing agreement in the diagnosis of ASDs in toddlers. Considering their characteristics in terms of sensitivity, specificity and positive predictive values, all these instruments should be included as important tools in clinical protocols for early identification of ASDs.