Incremental Utility of 24-Month Autism Spectrum Disorder Screening After Negative 18-Month Screening

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.

Diagnosis and Assessment of Autism Spectrum Disorder in South Korea

Autism spectrum disorder (ASD) is diagnosed by the clinical decision of a trained professional based on the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition or International Classification of Diseases 11th Revision diagnostic criteria. To obtain information for diagnostic formulation, professionals should explore detailed developmental history, and can use structured or semi-structured assessment tools to observe interaction between the child and parents or strangers. Diagnostic assessment should include a profile of the strength and weaknesses of the individual and should be conducted using an optimal approach by a multidisciplinary team with appropriate techniques and experience. Assessment of language, cognitive, neuropsychological, and adaptive functioning should be conducted in ASD individuals prior to establishing an individualized treatment plan. Genetic testing, brain magnetic resonance imaging or electroencephalogram testing can be considered for identification of underlying causes.

Screening for Autism Spectrum Disorder in Young Children: Still Not Enough Evidence

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.

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.

Diagnostic Accuracy of the Social Attention and Communication Surveillance-Revised With Preschool Tool for Early Autism Detection in Very Young Children

Importance

Early identification of children on the autism spectrum is crucial to facilitate access to early supports and services for children and families. The need for improved early autism identification tools is highlighted by the lack of sufficient diagnostic accuracy in current tools.

Objectives

To examine the diagnostic accuracy of the Social Attention and Communication Surveillance-Revised (SACS-R) and SACS-Preschool (SACS-PR) tools when used with a large, community-based, convenience sample and identify the prevalence of autism in this sample.

Design, Setting, and Participants

This diagnostic accuracy study was conducted in Melbourne, Australia, training maternal and child health nurses who monitored 13 511 children aged 11 to 42 months using the SACS-R and SACS-PR during their routine consultations (June 1, 2013, to July 31, 2018). Children identified as being at high likelihood for autism (12-24 months of age: n = 327; 42 months of age: n = 168) and at low likelihood for autism plus concerns (42 months of age: n = 28) were referred by their maternal and child health nurse for diagnostic assessment by the study team. Data analysis was performed from April 13, 2020, to November 29, 2021.

Exposures

Children were monitored with SACS-R and SACS-PR at 12, 18, 24, and 42 months of age.

Main Outcomes and Measures

Diagnostic accuracy of the SACS-R and SACS-PR was determined by comparing children's likelihood for autism with their diagnostic outcome using clinical judgment based on standard autism assessments (Autism Diagnostic Observation Schedule-Second Edition and Autism Diagnostic Interview-Revised).

Results

A total of 13 511 children (female: 6494 [48.1%]; male: 7017 [51.9%]) were monitored at least once with the SACS-R at their 12-, 18-, and 24-month-old routine maternal and child health consultations (mean [SD] age, 12.3 [0.59] months at 12 months; 18.3 [0.74] months at 18 months; 24.6 [1.12] months at 24 months) and followed up at their 42-month maternal and child health consultation (mean [SD] age, 44.0 [2.74] months) with SACS-PR (8419 [62.3%]). At 12 to 24 months, SACS-R showed high diagnostic accuracy, with 83% positive predictive value (95% CI, 0.77-0.87) and 99% estimated negative predictive value (95% CI, 0.01-0.02). Specificity (99.6% [95% CI, 0.99-1.00]) was high, with modest sensitivity (62% [95% CI, 0.57-0.66]). When the SACS-PR 42-month assessment was added, estimated sensitivity increased to 96% (95% CI, 0.94-0.98). Autism prevalence was 2.0% (1 in 50) between 11 and 30 months of age and 3.3% (1 in 31) between 11 and 42 months of age.

Conclusions and Relevance

The SACS-R with SACS-PR (SACS-R+PR) had high diagnostic accuracy for the identification of autism in a community-based sample of infants, toddlers, and preschoolers, indicating the utility of early autism developmental surveillance from infancy to the preschool period rather than 1-time screening. Its greater accuracy compared with psychometrics of commonly used autism screening tools when used in community-based samples suggests that the SACS-R+PR can be used universally for the early identification of autism.

Get SET Early to Identify and Treatment Refer Autism Spectrum Disorder at 1 Year and Discover Factors That Influence Early Diagnosis

OBJECTIVES

To examine the impact of a new approach, Get SET Early, on the rates of early autism spectrum disorder (ASD) detection and factors that influence the screen-evaluate-treat chain.

STUDY DESIGN

After attending Get SET Early training, 203 pediatricians administered 57 603 total screens using the Communication and Symbolic Behavior Scales Infant-Toddler Checklist at 12-, 18-, and 24-month well-baby examinations, and parents designated presence or absence of concern. For screen-positive toddlers, pediatricians specified if the child was being referred for evaluation, and if not, why not.

RESULTS

Collapsed across ages, toddlers were evaluated and referred for treatment at a median age of 19 months, and those screened at 12 months (59.4% of sample) by 15 months. Pediatricians referred one-third of screen-positive toddlers for evaluation, citing lack of confidence in the accuracy of screen-positive results as the primary reason for nonreferral. If a parent expressed concerns, referral probability doubled, and the rate of an ASD diagnosis increased by 37%. Of 897 toddlers evaluated, almost one-half were diagnosed as ASD, translating into an ASD prevalence of 1%.

CONCLUSIONS

The Get SET Early model was effective at detecting ASD and initiating very early treatment. Results also underscored the need for change in early identification approaches to formally operationalize and incorporate pediatrician judgment and level of parent concern into the process.

Characteristics of toddlers with early versus later diagnosis of autism spectrum disorder

LAY ABSTRACT

The emergence of autism symptoms in childhood is variable, with some children showing signs of autism spectrum disorder very early, and others not being identified until much later. Although most children in the United States are not diagnosed with autism spectrum disorder until preschool, at ages 3-4 years, symptoms can be reliably detected at 14 months. It is less certain how those toddlers diagnosed with autism spectrum disorder earlier versus later differ from each other clinically. This study revealed that young children diagnosed later in development, between ages 25 and 41 months, are more impaired on measures of cognitive, adaptive, and social functioning than their counterparts who are diagnosed with autism spectrum disorder earlier. All young children with autism spectrum disorder are impaired in communication to a similar degree, however. Universal autism screening at 18 months may identify toddlers with autism spectrum disorder when their symptoms are milder and more readily amenable to intervention. Repeated screening at 24 months is supported to detect those children missed by an earlier screening, who may be more severely affected. Caregivers should be encouraged to pursue diagnostic evaluation at an initial positive screening result to ensure timely diagnosis and treatment.

Early Autism Spectrum Disorders in Children Born to Fertile, Subfertile, and ART-Treated Women

INTRODUCTION

We examined the prevalence of autism spectrum disorders (ASDs) in Massachusetts (MA) comparing children born via assisted reproductive technology (ART) and children born to women with indicators of subfertility but no ART (Subfertile), to children born to women with neither ART nor indicators of subfertility (Fertile). We assessed the direct, indirect, and total effects of ART and subfertility on ASD among singletons.

METHODS

This study included 10,147 ART, 8072 Subfertile and 441,898 Fertile MA resident births from the MA Outcome Study of ART (MOSART) database linked with Early Intervention program participation data. ART included fresh in vitro fertilization (IVF), fresh intracytoplasmic sperm injection (ICSI), and frozen embryo transfer. We estimated the prevalence of ASD by fertility group. We used logistic regression to assess the natural direct effect (NDE), natural indirect effect (NIE) through preterm birth, and total effects of each fertility group on ASD.

RESULTS

The NDE indicated that, compared to the Fertile group, the odds of ASD were not statistically higher in the ART (OR_NDE 1.07; 95% CI 0.88-1.30), Subfertile (OR_NDE 1.11; 95% CI 0.89-1.38), IVF (OR_NDE 0.91; 95% CI 0.68-1.22), or ICSI (OR_NDE 1.13; 95% CI 0.84-1.51) groups, even if the rate of preterm birth was the same across all groups. The total effect (product of NDE and NIE) was not significant for ART (OR_{Total Effect} 1.08; 95% CI 0.89-1.30), Subfertile (OR_{Total Effect} 1.11; 95% CI 0.89-1.38), IVF (OR_{Total Effect} 0.92; 95% CI 0.69-1.23), or ICSI (OR_{Total Effect} 1.13; 95% CI 0.84-1.52).

CONCLUSION

Compared to children born to Fertile women, children born to ART, ICSI, or IVF, or Subfertile women are not at increased risk of receiving an ASD diagnosis.

Linking risk factors and outcomes in autism spectrum disorder: is there evidence for resilience?

Autism spectrum disorder (referred to here as autism) is one of several overlapping neurodevelopmental conditions that have variable impacts on different individuals. This variability results from dynamic interactions between biological and non-biological risk factors, which result in increasing differentiation between individuals over time. Although this differentiation continues well into adulthood, the infancy period is when the brain and behavior develop rapidly, and when the first signs and symptoms of autism emerge. This review discusses advances in our understanding of the causal pathways leading to autism and overlapping neurodevelopmental conditions. Research is also mapping trajectories of brain and behavioral development for some risk groups, namely later born siblings of children with autism and/or infants referred because of developmental concerns. This knowledge has been useful in improving early identification and establishing the feasibility of targeted interventions for infant risk groups before symptoms arise. However, key knowledge gaps remain, such as the discovery of protective factors (biological or environmental) that may mitigate the impact of risk. Also, the dynamic mechanisms that underlie the associations between risk factors and outcomes need further research. These include the processes of resilience, which may explain why some individuals at risk for autism achieve better than expected outcomes. Bridging these knowledge gaps would help to provide tools for early identification and intervention that reflect dynamic developmental pathways from risk to outcomes.