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Grigore B, Peters J, Williams J, Russell G, Coles P, Visintin C, Rogers M, Hayward R, Zhelev Z, Logan S, Hyde C. Screening for Autism Spectrum Disorder in Young Children: Still Not Enough Evidence. J Prim Care Community Health 2024; 15:21501319241263223. [PMID: 39077980 PMCID: PMC11289826 DOI: 10.1177/21501319241263223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 05/16/2024] [Accepted: 06/01/2024] [Indexed: 07/31/2024] Open
Abstract
BACKGROUND Early detection of autism spectrum disorder (ASD) has the potential to significantly reduce the impact of the condition, however previous reviews have found little evidence to support screening programs for ASD in young children. METHODS We conducted a review with the aim of updating evidence on 3 aspects: (a) diagnostic stability of ASD in young children; (b) accuracy of ASD screening tools in young children; and (c) the benefits of early interventions in screen-detected young children with ASD. RESULTS A total of 33 studies were included in our review. Five studies looking at diagnostic stability reported estimates ranging from 71.9% to 100%, however the majority only included a follow-up of 24 months and all studies raised concerns regarding the risk of bias due particularly to lack of blinding, sample size, and patient flow. A total of 25 studies, reported in 26 articles, were identified that reported accuracy data on 11 screening tools. Most of the reports were concerned with versions of M-CHAT, reporting sensitivity estimates from 0.67 to 1.0; however, many of these were deemed to be of high risk of bias due to lack of blinding and follow-up. Four studies reported on early interventions in screen-detected children; however, the majority did not find significant improvements on the relevant outcomes. CONCLUSIONS Overall, the evidence on screening for ASD in young children captured by this review is not conclusive regarding the 3 aspects of screening in this population. Future studies should attempt to ensure blinded diagnostic assessments, include longer follow-up periods and limit attrition.
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Wieckowski AT, Williams LN, Rando J, Lyall K, Robins DL. Sensitivity and Specificity of the Modified Checklist for Autism in Toddlers (Original and Revised): A Systematic Review and Meta-analysis. JAMA Pediatr 2023; 177:373-383. [PMID: 36804771 PMCID: PMC9941975 DOI: 10.1001/jamapediatrics.2022.5975] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 11/11/2022] [Indexed: 02/22/2023]
Abstract
Importance The Modified Checklist for Autism in Toddlers (M-CHAT) and the M-CHAT, Revised With Follow-up (M-CHAT-R/F)-henceforth referred to as M-CHAT(-R/F)-are the most commonly used toddler screeners for autism spectrum disorder (ASD). Their use often differs from that in the original validation studies, resulting in a range of estimates of sensitivity and specificity. Also, given the variability in reports of the clinical utility of the M-CHAT(-R/F), researchers and practitioners lack guidance to inform autism screening protocols. Objective To synthesize variability in sensitivity and specificity of M-CHAT(-R/F) across multiple factors, including procedures for identifying missed cases, likelihood level, screening age, and single compared with repeated screenings. Data Sources A literature search was conducted with PubMed, Web of Science, and Scopus to identify studies published between January 1, 2001, and August 31, 2022. Study Selection Articles were included if the studies used the M-CHAT(-R/F) (ie, original or revised version) to identify new ASD cases, were published in English-language peer-reviewed journals, included at least 10 ASD cases, reported procedures for false-negative case identification, screened children by 48 months, and included information (or had information provided by authors when contacted) needed to conduct the meta-analysis. Data Extraction and Synthesis The systematic review and meta-analysis was conducted within the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. The Quality Assessment of Diagnostic Accuracy Studies-2 tool evaluated bias in sample selection. Data extraction and quality assessment were performed by 2 authors independently. The overall diagnostic accuracy of the M-CHAT(-R/F) was assessed with the hierarchic summary receiver operating characteristic (HSROC) model. Main Outcomes and Measures Sensitivity, specificity, diagnostic odds ratios, and HSROC curves of M-CHAT(-R/F). Results The review included 50 studies with 51 samples. The pooled sensitivity of M-CHAT(-R/F) was 0.83 (95% CI, 0.77-0.88), and the pooled specificity was 0.94 (95% CI, 0.89-0.97). Heterogeneity analyses revealed greater diagnostic accuracy for low- vs high-likelihood samples, a concurrent vs prospective case confirmation strategy, a large vs small sample size, use of M-CHAT(-R/F) Follow-up, and non-English vs English only. Conclusions and Relevance Overall, results of this study suggest the utility of the M-CHAT(-R/F) as an ASD screener. The wide variability in psychometric properties of M-CHAT(-R/F) highlights differences in screener use that should be considered in research and practice.
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Affiliation(s)
| | - Lashae N. Williams
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania
| | - Juliette Rando
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania
| | - Kristen Lyall
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania
| | - Diana L. Robins
- A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania
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Chen S, Zhao J, Hu X, Tang L, Li J, Wu D, Yan T, Xu L, Chen M, Huang S, Hao Y. Children neuropsychological and behavioral scale-revision 2016 in the early detection of autism spectrum disorder. Front Psychiatry 2022; 13:893226. [PMID: 35935438 PMCID: PMC9354041 DOI: 10.3389/fpsyt.2022.893226] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 06/27/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND The Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) is a widely used developmental assessment tool for children aged 0-6 years in China. The communication warning behavior subscale of CNBS-R2016 is used to assess the symptoms of autism spectrum disorder (ASD), and its value of >30 points indicates ASD based on CNBS-R2016. However, we observed that children with relatively lower values were also diagnosed with ASD later on in clinical practice. Thus, this study aimed to identify the suitable cutoff value for ASD screening recommended by the communication warning behavior of CNBS-R2016. MATERIALS AND METHODS A total of 90 typically developing (TD) children and 316 children with developmental disorders such as ASD, developmental language disorder (DLD), and global developmental delay (GDD; 130 in the ASD group, 100 in the DLD group, and 86 in the GDD group) were enrolled in this study. All subjects were evaluated based on the CNBS-R2016. The newly recommended cutoff value of communication warning behavior for screening ASD was analyzed with receiver operating curves. RESULTS Children in the ASD group presented with lower developmental levels than TD, DLD, and GDD groups in overall developmental quotient assessed by CNBS-R2016. We compared the consistency between the scores of communication warning behavior subscale and Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), Autism Diagnostic Observation Schedule, second edition (ADOS-2), and clinical diagnosis for the classification of ASD at a value of 30 based on the previously and newly recommended cutoff value of 12 by the CNBS-R2016. The Kappa values between the communication warning behavior and ABC, CARS, ADOS-2, and clinical diagnosis were 0.494, 0.476, 0.137, and 0.529, respectively, with an agreement rate of 76.90%, 76.26%, 52.03%, and 82.27%, respectively, when the cutoff point was 30. The corresponding Kappa values were 0.891, 0.816, 0.613, and 0.844, respectively, and the corresponding agreement rate was 94.62%, 90.82%, 90.54%, and 93.10%, respectively, when the cutoff point was 12. CONCLUSION The communication warning behavior subscale of CNBS-R2016 is important for screening ASD. When the communication warning behavior score is 12 points or greater, considerable attention and further comprehensive diagnostic evaluation for ASD are required to achieve the early detection and diagnosis of ASD in children.
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Affiliation(s)
- Shuling Chen
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Department of Child Health Care, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinzhu Zhao
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaolin Hu
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lina Tang
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinhui Li
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dandan Wu
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tian Yan
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lu Xu
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Chen
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shan Huang
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Hao
- Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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