Validation of the Modified Checklist for Autism in Toddlers, Revised with Follow-up in a Population Sample of 30-Month-Old Children in Iceland: A Prospective Approach

Screening for Autism: A Review of the Current State, Ongoing Challenges, and Novel Approaches on the Horizon

Screening for autism is recommended in pediatric primary care. However, the median age of autism spectrum disorder (ASD) diagnosis is substantially higher than the age at which autism can reliably be identified, suggesting room for improvements in autism recognition at young ages, especially for children from minoritized racial and ethnic groups, low-income families, and families who prefer a language other than English. Novel approaches are being developed to utilize new technologies in aiding in autism recognition. However, attention to equity is needed to minimize bias. Additional research on the benefits and potential harms of universal autism screening is needed. The authors provide suggestions for pediatricians who are considering implementing autism-screening programs.

Evaluating screening for autism spectrum disorder using cluster randomization

We evaluated the rate of autism spectrum disorder (ASD) in a group invited to a screening program compared to the rates in two groups who received usual care. The population eligible for screening was all children in Iceland registered for their 30-month well-child visits at primary healthcare centers (PHCs) from March 1, 2016, to October 31, 2017 (N = 7173). The PHCs in the capital area of Reykjavik were the units of cluster randomization. Nine PHCs were selected for intervention (invited group), while eight PHCs received usual care (control group 1). PHCs outside the capital area were without randomization (control group 2). An interdisciplinary team, including a pediatrician contributing with physical and neurological examination, a psychologist evaluating autism symptoms using a diagnostic instrument, and a social worker interviewing the parents, reached a consensus on the clinical diagnosis of ASD according to the ICD-10 diagnostic system. Children in the population were followed up for at least two years and 119 cases were identified. The overall cumulative incidence of ASD was 1.66 (95% confidence interval (CI): 1.37, 1.99). In the invited group the incidence rate was 2.13 (95% CI: 1.60, 2.78); in control group 1, the rate was 1.83 (95% CI: 1.31, 2.50); and in control group 2, the rate was 1.02 (95% CI: 0.66, 1.50). Although the rate of ASD was higher in the invited group than in the control groups, the wide confidence intervals prevented us from concluding definitively that the screening detected ASD more readily than usual care.

Screening and diagnostic tools for autism spectrum disorder: Systematic review and meta-analysis

INTRODUCTION

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental disorder, with main manifestations related to communication, social interaction, and behavioral patterns. The slight dynamics of change in the child over time require that the onset of clinical manifestations presented by the child be more valued, with the aim of stabilizing the condition. Faced with a variety of methods for diagnosing ASD, the question arises as to which method should be used. This systematic review aims to recommend the best tools to perform screening and diagnosis.

METHODOLOGY

This systematic review followed the PRISMA guidelines. The databases MEDLINE, Embase, CENTRAL (Cochrane), and Lilacs were accessed, and gray and manual searches were performed. The search strategy was created with terms referring to autism and the diagnosis/broad filter. The studies were qualitatively evaluated and quantitatively. Statistical analysis was performed using Meta-diSc-2.0 software, the confidence interval was 95 %.

RESULTS

The M-CHAT-R/F tool demonstrated a sensitivity of 78 % (95 % CI 0.57‒0.91) and specificity of 0.98 (95 % CI 0.88-1.00). The diagnostic tools demonstrated sensitivity and specificity respectively of: ADOS, sensitivity of 87 % (95 % CI 0.79‒0.92) and specificity 75 % (95 % CI 0.73‒0.78); ADI-R demonstrated test sensitivity of 77 % (95 % CI 0.56‒0.90) and specificity 68 % (95 % CI 0.52‒0.81), CARS test sensitivity was 89 % (95 % CI 0.78‒0.95) and specificity 79 % (95 % CI 0.65‒0.88).

CONCLUSION

It is mandatory to apply a screening test, the most recommended being the M-CHAT-R/F. For diagnosis CARS and ADOS are the most recommended tools.

Validity and feasibility of using the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F) in primary care clinics in Singapore

LAY ABSTRACT

Systematic screening for autism in early childhood has been suggested to improve eventual outcomes by facilitating earlier diagnosis and access to intervention. However, clinical implementation of screening has to take into account effectiveness and feasibility of use within a healthcare setting for accurate diagnosis of autism. In Singapore, autism screening using a structured screening tool is not currently employed as a part of routine well-child visits for children in primary care clinics. In this study, 5336 children (aged 17-20 months) were screened for autism using the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F) during their 18-month well-child visit in seven primary care clinics. Screening and follow-up interviews were administered by nursing staff at each clinic. Children screened positive and a portion of those screened negative then underwent diagnostic assessments to determine whether they met the diagnostic criteria for autism. In total, 113 (2.1%) were screened positive, of which 54 (1.0%) met the criteria for autism. Children who screened positive and received a diagnosis accessed autism-specific intervention at an average age of 22 months. Nurses and physicians rated the acceptability and practicality of the M-CHAT-R/F highly. Therefore, the M-CHAT-R/F questionnaire was an effective and feasible tool for autism screening among 18-month-old children in this study. Future studies will be designed to determine the optimal age of screening and role of repeated screening in Singapore, as well as to better understand any potential improved outcomes nationwide compared with pre-implementation of autism screening.

Meta-analysis of the Modified Checklist for Autism in Toddlers, Revised/Follow-up for Screening

CONTEXT

The Modified Checklist for Autism in Toddlers, Revised with Follow-up (M-CHAT-R/F) is used worldwide to screen for autism spectrum disorder (ASD).

OBJECTIVE

To calculate psychometric properties of the M-CHAT-R/F for subsequent diagnosis of ASD.

DATA SOURCES

Systematic searches of Medline, Embase, SCOPUS, and Trip Pro databases from January 2014 to November 2021.

STUDY SELECTION

Studies were included if they (1) used the M-CHAT-R/F (2) applied standard scoring protocol, (3) used a diagnostic assessment for ASD, and (4) reported at least 1 psychometric property of the M-CHAT-R/F.

DATA EXTRACTION

Two independent reviewers completed screening, full-text review, data extraction, and quality assessment, following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A random-effects model was used to derive pooled estimates and assess for between-study heterogeneity.

RESULTS

Of 667 studies identified, 15 with 18 distinct samples from 10 countries (49 841 children) were used in the meta-analysis. Pooled positive predictive value (PPV), was 57.7% (95% confidence interval [CI] 48.6-66.8, τ2 = 0.031). PPV was higher among high-risk (75.6% [95% CI 66.0-85.2]) than low-risk samples (51.2% [95% CI 43.0-59.5]). Pooled negative predictive value was 72.5% (95% CI 62.5-82.4 τ2 = 0.031), sensitivity was 82.6% (95% CI 76.2-88.9) and specificity 45.7% (95% CI 25.0-66.4).

LIMITATIONS

Negative predictive value, sensitivity, and specificity were calculated based on small sample sizes because of limited or no evaluation of screen-negative children.

CONCLUSIONS

These results support use of the M-CHAT-R/F as a screening tool for ASD. Caregiver counseling regarding likelihood of an ASD diagnosis after positive screen should acknowledge the moderate PPV.

Sensitivity and Specificity of the Modified Checklist for Autism in Toddlers (Original and Revised): A Systematic Review and Meta-analysis

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.

Tools for early screening of autism spectrum disorders in primary health care – a scoping review

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that manifests itself in early childhood. Early diagnosis of these disorders allows for the initiation of early therapy, which is crucial for the child's further functioning in society.

Objectives

This review aims to gather and present the existing ASD screening tools that can be used in primary care and adapted to different countries conditions linguistically and culturally.

Eligibility criteria

We searched for English-language publications on ASD screening tools for children aged 0–3 years suitable for use in primary care (i.e. free, requiring no additional training or qualifications).

Sources of evidence

Four databases were explored to find English studies on ASD screening tools intended for the rapid assessment of children aged 0–3.

Charting methods

The information sought (specific features of the questionnaires relevant to primary health care workers, psychometric and diagnostic values of a given cultural adaptation of screening tools, and the linguistic and cultural changes made) were extracted and collected to create profiles of these tools.

Results

We found 81 studies which met inclusion criteria and underwent full data extraction. Three additional data sources were included. These allowed to create 75 profiles of adaptations for 26 different screening tools and collect data on their psychometric values and characteristic features.

Conclusions

The results of our study indicate the availability of several diagnostic tools for early ASD screening in primary care setting concordant culturally and linguistically with a given population. They could be an effective method of accelerating the diagnostic process and starting personalized therapy faster. However, most tools have significant limitations – some are only available for research purposes, while others do not have scientific evidence to prove their effectiveness.