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Replication study for ADOS-2 cut-offs to assist evaluation of autism spectrum disorder.

ABSTRACT: The Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) has been widely used for ASD assessment. While prior studies investigated sensitivity and specificity of ADOS-2 Modules 1-3, there has been limited research addressing algorithm cut-off scores to optimize ADOS-2 classification. The goal of this study was to assess algorithm cut-off scores for diagnosing ASD with Modules 1-3, and to evaluate alignment of the ADOS-2 classification with the best estimate clinical diagnosis. Participants included 3144 children aged 31 months or older who received ADOS-2 Modules 1-3, as well as the best estimate clinical diagnosis. Five classification statistics were reported for each module: sensitivity, specificity, positive predictive value, negative predictive value, and accuracy (i.e., Receiver Operator Classification Statistic), and these statistics were calculated for the optimal cut-off score. Frequency tables were used to compare ADOS-2 classification and the best estimate clinical diagnosis. Half of the sample received Module 3, 21% received Module 2, and 29% received Module 1. The overall prevalence of ASD was 60%; the male-to-female ratio was 4:1, and half of the sample was non-White. Across all modules, the autism spectrum cut-off score from the ADOS-2 manual resulted in high sensitivity (95%+) and low specificity (63%-73%). The autism cut-off score resulted in better specificity (76%-86%) with favorable sensitivity (81%-94%). The optimal cut-off scores for all modules based on the current sample were within the autism spectrum classification range except Module 2 Algorithm 2. In the No ASD group, 29% had false positives (ADOS-2 autism spectrum classification or autism classification). The ADOS-2 autism spectrum classification did not indicate directionality for diagnostic outcome (ASD 56% vs. No ASD 44%). While cut-off scores of ADOS-2 Modules 1-3 in the manual yielded good clinical utility in ASD assessment, false positives and low predictability of the autism spectrum classification remain challenging for clinicians.

SUBMITTER: Hong JS

PROVIDER: S-EPMC10246880 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Replication study for ADOS-2 cut-offs to assist evaluation of autism spectrum disorder.

Hong Ji Su JS Singh Vini V Kalb Luke L Reetzke Rachel R Ludwig Natasha N NN Pfeiffer Danika D Holingue Calliope C Menon Deepa D Lu Qing Q Ashkar Ahlam A Landa Rebecca R

Autism research : official journal of the International Society for Autism Research 20220902 11

The Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) has been widely used for ASD assessment. While prior studies investigated sensitivity and specificity of ADOS-2 Modules 1-3, there has been limited research addressing algorithm cut-off scores to optimize ADOS-2 classification. The goal of this study was to assess algorithm cut-off scores for diagnosing ASD with Modules 1-3, and to evaluate alignment of the ADOS-2 classification with the best estimate clinical diagnosis. Partici ...[more]

PMID: 36054678

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Project description:BackgroundNeuroinflammation is closely associated with the occurrence and development of autism spectrum disorder (ASD). This study aims to describe the global development history and current status of neuroinflammation in ASD from 2004 to 2021 and reveal the research hotspots and frontiers to provide a reference for scholars in related fields to carry out further research.MethodsJournal articles on ASD and neuroinflammation-related research were obtained from the Web of Science Core Collection (WOSCC) database from its inception to 2021. Literature was analyzed visually by VOSviewer, CiteSpace, and R language, including publication analysis, author, institution, national/regional cooperative network analysis, and keyword analysis. We screened the most accumulatively cited 10 experimental papers in the field and the most cited 10 experimental papers in the last 2 years (2020 and 2021) for combing.ResultsA total of 620 publications were included in this study, and the number of publications has increased in recent years. The United States (256, 41.29%) was the country with the largest number of publications. King Saud University (40, 6.45%) was the most published institution; Laila Al-Ayadhi Yousef was the most published researcher; the Brain Behavior and Immunity was the main journal for the study of neuroinflammation in autism, having published 22 related articles. Keyword co-occurrence analysis showed that short chain fatty acid, mast cells, and glial cells have been the focus of recent attention. Burst keywords show that gut microbiota and immune system are the future research trends.ConclusionThis bibliometric study describes the basic framework for the development in the field of neuroinflammation and ASD through an exploration of key indicators (countries, institutions, journals, authors, and keywords). We found that the key role of neuroinflammation in the development of ASD is attracting more and more researchers' attention. Future studies can investigate the changes in cytokines and glial cells and their related pathways in ASD neuroinflammation. Immunotherapy to inhibit neuroinflammation may be intensively studied as a direction for ASD treatment or intervention.

Dataset Information

Replication study for ADOS-2 cut-offs to assist evaluation of autism spectrum disorder.

Publications

Replication study for ADOS-2 cut-offs to assist evaluation of autism spectrum disorder.

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