This Perspective argues that best-estimate clinical diagnosis must be grounded in rigorous developmental anchoring, collateral information, and judicious clinical judgment, and proposes a set of core stratification domains for systematic phenotypic stratification.
Abstract
The reported prevalence of autism spectrum disorder (ASD) has risen dramatically over the past two decades. Although increased awareness, broader diagnostic criteria, and improved access to assessment have corrected historical under-identification, this diagnostic expansion also raises a significant methodological concern: the risk of diagnostic dilution. Increasingly, surveillance systems and clinical cohorts may include individuals whose phenotypic profiles, developmental histories, and functional impairments do not fully align with a developmentally anchored neurodevelopmental presentation of ASD. This challenge is particularly acute in adolescent and adult assessments, where developmental history may be incomplete and standardized instruments or self-report measures may show limited specificity when applied to clinically complex psychiatric populations. Conflating developmentally anchored ASD with partially overlapping clinical phenotypes may reduce the signal-to-noise ratio in genetic, biomarker, neuroimaging, and therapeutic research, contributing to findings that are difficult to replicate or interpret. To preserve diagnostic validity, this Perspective argues that best-estimate clinical diagnosis must be grounded in rigorous developmental anchoring, collateral information, and judicious clinical judgment. It further proposes a set of core stratification domains for systematic phenotypic stratification, including age at first concern and diagnosis, biological sex and sex-related ascertainment factors, language and cognitive trajectories, adaptive functioning, intellectual disability, psychiatric comorbidities, ascertainment source, diagnostic instruments used, collateral developmental documentation, and support needs and functional impairment across contexts and over time. Stratification should not be understood as a restriction on clinical access, but as a scientific requirement for meaningful prevalence estimates and biologically informative autism research.
This narrative review is an argumentative reappraisal addressing three convergent failures — classificatory, sociocultural, and methodological — and asking what minimum evidentiary standards should govern adult ASD differential diagnosis in complex cases.
L. Croce, I. Fusaro· Frontiers in Psychiatry· 0 citations
A comprehensive review of recent advancements in ASD research, with particular emphasis on neuroimaging, artificial intelligence (AI), and machine learning (ML)-based diagnostic approaches, highlights the growing potential of AI-driven tools for supporting early ASD diagnosis and emphasizes the need for standardized pr...
Kuljeet Singh, Khushi Mogha, S. Moctar· Neurological Sciences· 0 citations
This review systematically summarizes the conceptual definition and clinical phenotypes of profound autism and emphasizes the need to shift the intervention focus toward managing serious comorbidities and establishing augmentative and alternative communication systems.
Yang Xue, Fei-Yong Jia· Zhongguo dang dai er ke za z...· 0 citations
There is an urgent need for prospective longitudinal studies to adequately map the aging trajectories of this population of older adults with ASD, which constitute a vulnerable population.
J. P. S. Gontijo, Marcelo H S S Martins, L. M. Alves· Trends in Psychiatry and Psy...· 0 citations
This critical narrative review examines early autism identification as a pathway problem rather than as a single testing event and argues that early autism identification should be evaluated through linked quality measures: response to concern, repeated surveillance following negative or ambiguous screening, referral c...
R. Kurmashev, Mavile Karaieva· Pediatric Investigation· 0 citations
A narrative review of papers published between 1 January 2015 and 16 February 2026 that were pertinent to comorbidity and autism finds how the variable risk of comorbidity mimics the heterogeneity present in autism, thus inviting further investigations.
E. Dando, Juergen Hahn, D. Geier et al.· Healthcare· 0 citations
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