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A meta-analysis of the diagnostic accuracy of Autism Diagnostic Observation Schedule Module-1 for autism spectrum
Sherab Tsheringla1, K A Minju, Sushila Russell
1Child and Adolescent Psychiatry Unit, Department of Psychiatry, Christian Medical College, Vellore, 632 002, Tamil Nadu, India.
Objective:
Autism Diagnostic Observation Schedule (ADOS) is considered gold standard for the diagnosis of Autism Spectrum Disorders (ASD). The authors evaluated the cumulative diagnostic accuracy of ADOS-Module 1 (ADOS(M1)) using the original diagnostic algorithm with meta-analysis and meta-regression.
Methods:
The authors, electronically and manually searched for studies from 1999 to 2013 that evaluated the accuracy of ADOS(M1) using the original diagnostic algorithm in detecting ASD. Primary results of Sensitivity (Sn), Specificity (Sp) and Diagnostic Odds Ratio (DOR) for ADOS(M1) were summarized using random-effects model. Summary Receiver Operating characteristic Curves and its Area Under the Curve (SROC-AUC) were used to summarize overall diagnostic accuracy of ADOS(M1). The modifying effects of quality of study and sample size, on the diagnostic odds ratio, were investigated using meta-regression.
Results:
A total of 7 cross-sectional studies provided data on 4057 children. The pooled Sn, Sp, DOR and SROC-AUC for the overall diagnostic accuracy of ADOS (M1) were: 0.91 (95 %CI=0.89 to 0.93), 0.73 (95 % CI=0.69 to 0.76), 44.20 (95 %CI=15.89 to 122.95) and 0.90 respectively [corrected]. Meta-regression analysis showed a non-significant relationship between ADOS(M1) and study quality as well as sample size. There were subgroup differences in the DOR.
Conclusions:
It is concluded that ADOS (M1) with the original diagnostic algorithm has the overall diagnostic accuracy and pooled specificity suggesting moderate accuracy. The pooled sensitivity is high to be used as a screening test for Autism Spectrum Disorders. ADOS( M1)with the revised diagnostic algorithm should be used for diagnostic purpose [corrected] ADOS(M1) with the revised diagnostic algorithm should be used instead for the diagnosis of this group of disorders.
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