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Autism Res. 2019 May 31. doi: 10.1002/aur.2128. [Epub ahead of print]

Clustering of co-occurring conditions in autism spectrum disorder during early childhood: A retrospective analysis of medical claims data.

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Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York.
Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York.
OptumLabs Visiting Fellow, Cambridge, Massachusetts.
Department of Child Health, University of Arizona College of Medicine, Phoenix, Arizona.
Phoenix Children's Hospital, Phoenix, Arizona.
Department of Computer Science, Rensselaer Polytechnic Institute, Troy, New York.
Department of Cognitive Science, Rensselaer Polytechnic Institute, Troy, New York.
Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York.


Individuals with autism spectrum disorder (ASD) are frequently affected by co-occurring medical conditions (COCs), which vary in severity, age of onset, and pathophysiological characteristics. The presence of COCs contributes to significant heterogeneity in the clinical presentation of ASD between individuals and a better understanding of COCs may offer greater insight into the etiology of ASD in specific subgroups while also providing guidance for diagnostic and treatment protocols. This study retrospectively analyzed medical claims data from a private United States health plan between years 2000 and 2015 to investigate patterns of COC diagnoses in a cohort of 3,278 children with ASD throughout their first 5 years of enrollment compared to 279,693 children from the general population without ASD diagnoses (POP cohort). Three subgroups of children with ASD were identified by k-means clustering using these COC patterns. The first cluster was characterized by generally high rates of COC diagnosis and comprised 23.7% (n = 776) of the cohort. Diagnoses of developmental delays were dominant in the second cluster containing 26.5% (n = 870) of the cohort. Children in the third cluster, making up 49.8% (n = 1,632) of the cohort, had the lowest rates of COC diagnosis, which were slightly higher than rates observed in the POP cohort. A secondary analysis using these data found that gastrointestinal and immune disorders showed similar longitudinal patterns of prevalence, as did seizure and sleep disorders. These findings may help to better inform the development of diagnostic workup and treatment protocols for COCs in children with ASD. Autism Res 2019. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Medical conditions that co-occur with autism spectrum disorder (ASD) vary significantly from person to person. This study analyzed patterns in diagnosis of co-occurring conditions from medical claims data and observed three subtypes of children with ASD. These results may aid with screening for co-occurring conditions in children with ASD and with understanding ASD subtypes.


k-means clustering; autism spectrum disorder; co-occurring condition; comorbidity; medical claims; retrospective analysis


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