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[Value of autism screening checklists in the early identification of autism spectrum disorder]
Qiu-Hong Wei1, Xiao-Fen Xie1, Jing-Jing Dai1
1Department of Health Care, Children's Hospital of Chongqing Medical University/Ministry of Education Key Laboratory of Child Development and Disorders/National Clinical Research Center for Child Health and Disorders/China International Science and Technology Cooperation Base of Child Development and Critical Disorders/Chongqing Key Laboratory of Pediatrics, Chongqing 400014, China.
Objective:
To evaluate the value of autism screening checklists in the early identification of autism spectrum disorder (ASD).
Methods:
A total of 2 571 children who attended the Children's Hospital of Chongqing Medical University and completed autism screening and diagnostic test were enrolled as subjects, among whom 2 074 were diagnosed with ASD, 261 were diagnosed with global developmental delay (GDD), 206 were diagnosed with developmental language disorder (DLD), and 30 had normal development. The sensitivity, specificity, and optimal threshold value of the Modified Checklist for Autism in Toddlers (M-CHAT) and the Autism Behavior Checklist (ABC) for the early identification of ASD were evaluated by the receiver operating characteristic (ROC) curve.
Results:
The M-CHAT had a high sensitivity of 88.3% but a low specificity of 36.0% for the identification of ASD. Its sensitivity decreased with age, and was maintained above 80% for children aged 16 to < 48 months. The ABC had a high specificity of 87.3% but a low sensitivity of 27.2%, with an optimal cut-off value of 47.5 based on the ROC curve analysis. The multivariate linear regression model based on a combination of the M-CHAT and ABC for screening of ASD showed a specificity of 85.8% and a sensitivity of 56.6%.
Conclusions:
The M-CHAT has a high sensitivity and a low specificity in the identification of ASD, with a better effect in children aged 16 to < 48 months. The ABC has a high specificity and a low sensitivity. The multiple linear regression model method based on the combined M-CHAT and ABC to screen ASD appears to be effective.
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