Expert Clinician Certainty in Diagnosing Autism Spectrum Disorder in 16-30-Month-Olds: A Multi-site Trial Secondary
Cheryl Klaiman1,2, Stormi White1,2, Shana Richardson1
1Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA.
Insights
Diagnosing autism spectrum disorder (ASD) in young children can be uncertain. This study found that mid-level symptoms and verbal skills were linked to clinician uncertainty, impacting early ASD diagnosis.
Area of Science:
- Developmental Psychology
- Pediatric Neurology
- Clinical Psychiatry
Background:
- Differential diagnosis of autism spectrum disorder (ASD) in young children presents significant challenges.
- Clinician uncertainty in diagnosing ASD can lead to misdiagnosis and delayed access to crucial early interventions.
- Previous research indicated diagnostic certainty rates as low as 60% in toddlers and preschoolers referred for ASD evaluation.
Purpose of the Study:
- To replicate and expand upon previous findings regarding diagnostic certainty in young children with suspected ASD.
- To identify factors contributing to clinician uncertainty in the diagnosis of ASD in toddlers and preschoolers.
- To explore the impact of symptomatology and demographic variables on diagnostic certainty.
Main Methods:
- Secondary analysis of diagnostic, demographic, and clinical data from 496 children aged 16-30 months.
- Data collected from a 6-site clinical trial involving experienced clinicians using best-practice procedures for ASD diagnosis.
- Utilized the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) and assessed verbal age equivalents.
Main Results:
- Overall diagnostic certainty for ASD was 70.2% among the evaluated children.
- Mid-level autism-related symptomatology was the most significant factor associated with clinician uncertainty.
- Mid-level verbal age equivalents also correlated with uncertainty, but symptomatology was a stronger predictor.
- Socio-demographic variables, including child's sex, were not significantly associated with diagnostic certainty.
Conclusions:
- Approximately one-third of early ASD diagnoses are made with some level of uncertainty.
- Identifying specific ADOS-2 score ranges associated with uncertainty can help standardize diagnostic decision-making.
- Calibration of diagnostic thresholds using longitudinal outcome data may reduce subjectivity in diagnosing young children with ASD.
Abstract:
Differential diagnosis of young children with suspected autism spectrum disorder (ASD) is challenging, and clinician uncertainty about a child's diagnosis may contribute to misdiagnosis and subsequent delays in access to early treatment. The current study was designed to replicate and expand a recent report in this Journal (McDonnell et al. in J Autism Dev Disord 49:1391-1401, https://doi.org/10.1080/15374416.2020.1823850 , 2019), in which only 60% of diagnoses were made with complete certainty by clinicians evaluating 478 toddlers and preschool children referred for possible ASD to specialized clinics. In this study, secondary analyses were performed on diagnostic, demographic and clinical data for 496 16-30-month-old children who were consecutive referrals to a 6-site clinical trial executed by specialized centers with experienced clinicians following best-practice procedures for the diagnosis of ASD. Overall, 70.2% of diagnoses were made with complete certainty. The most important factor associated with clinician uncertainty was mid-level autism-related symptomatology. Mid-level verbal age equivalents were also associated with clinician uncertainty, but measures of symptomatology were stronger predictors. None of the socio-demographic variables, including sex of the child, was significantly associated with clinician certainty. Close to one third of early diagnoses of ASD are made with a degree of uncertainty. The delineation of specific ranges on the ADOS-2 most likely to result in clinician uncertainty identified in this study may provide an opportunity to reduce random subjectivity in diagnostic decision-making via calibration of young-child diagnostic thresholds based on later-age longitudinal diagnostic outcome data, and via standardization of decision-making in regard to clinical scenarios frequently encountered by clinicians.
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