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

ABSTRACT: 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, 12: 1272-1285. © 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.

SUBMITTER: Vargason T

PROVIDER: S-EPMC6688922 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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

Vargason Troy T Frye Richard E RE McGuinness Deborah L DL Hahn Juergen J

Autism research : official journal of the International Society for Autism Research 20190531 8

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 ...[more]

PMID: 31149786

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Project description:Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) are two of the most represented neurodevelopmental conditions in childhood. The diagnostic shift introduced by the DSM-5, allowing a combined diagnosis of ADHD and ASD, poses different clinical challenges related to diagnostic overshadowing, accuracy of clinical judgment and potential delay in an ASD diagnosis in children presenting with ADHD. Here we tried to disentangle the clinical phenotype and specificity of the two co-occurring conditions in relation to autism traits and empathy, by comparing children with ASD with and without comorbid ADHD with children presenting ADHD only and children with typical development. The child versions of the Autism Quotient (C-AQ) and Empathy Quotient (C-EQ) were administered to a total sample of 198 male children between 6 and 14 years old with age appropriate language skills and normal intelligence. Univariate analysis demonstrated no significant differences in the C-AQ total and subscale scores as well as the C-EQ between children with ASD and children with ASD + ADHD, while children with ADHD alone presented an intermediate phenotype between ASD and TD. Furthermore, a receiver operating characteristic (ROC) analysis was applied to discriminate among the different phenotypes. We found that the C-AQ and C-EQ were accurate at distinguishing with satisfactory reliability between: (a) ASD vs. non- ASD (N-ASD) groups comprising both ADHD and TD children (Area Under the Curve AUC 88% for C-AQ and 81% for C-EQ); (b) ASD and TD (AUC 92% for C-AQ and 95% for C-EQ); (c) ASD and ADHD (AUC 80% for C-AQ and 68% for C-EQ). Our data confirm the reliability of the C-AQ and C-EQ as behavioral markers to differentiate ASD (regardless of comorbid ADHD) from an ADHD condition and TD. Interestingly, in our sample an ADHD condition does not increase the severity of the clinical phenotype in terms of autism traits distribution and empathy, suggesting that the psychological measures detected by the two quantitative instruments are independent of ADHD traits. This evidence will contribute to the translational efforts in developing better tailored treatments and preventive strategies.

Project description:ObjectivesTo estimate the prevalence of epilepsy in children with Autism Spectrum Disorder (ASD) and to determine the demographic and clinical characteristics of children with ASD and epilepsy in a large patient population.MethodsCross-sectional study using four samples of children with ASD for a total of 5,815 participants with ASD. The prevalence of epilepsy was estimated from a population-based sample. Children with and without epilepsy were compared on demographic and clinical characteristics. Multivariate logistic regression was used to examine the association between demographic and clinical characteristics and epilepsy.ResultsThe average prevalence of epilepsy in children with ASD 2-17 years was 12.5%; among children aged 13 years and older, 26% had epilepsy. Epilepsy was associated with older age, lower cognitive ability, poorer adaptive and language functioning, a history of developmental regression and more severe ASD symptoms. The association between epilepsy and the majority of these characteristics appears to be driven by the lower IQ of participants with epilepsy. In a multivariate regression model, only age and cognitive ability were independently associated with epilepsy. Children age 10 or older had 2.35 times the odds of being diagnosed with epilepsy (p<.001) and for a one standard deviation increase in IQ, the odds of having epilepsy decreased by 47% (p<.001).ConclusionThis is among the largest studies to date of patients with ASD and co-occurring epilepsy. Based on a representative sample of children with ASD, the average prevalence of epilepsy is approximately 12% and reaches 26% by adolescence. Independent associations were found between epilepsy and older age and lower cognitive ability. Other risk factors, such as poor language and developmental regression, are not associated with epilepsy after controlling for IQ. These findings can help guide prognosis and alert clinicians to patients with ASD who are at increased risk for epilepsy.

Project description:BackgroundThe association between autism spectrum disorder and hydrocephalus is not well understood, despite demonstrated links between autism spectrum disorder and cerebrospinal fluid abnormalities. Based on the hypothesis that autism spectrum disorder and hydrocephalus may, at least in some cases, be two manifestations of a shared congenital brain pathology, we investigated the potential association between autism spectrum disorder and hydrocephalus in a large Danish population-based cohort.MethodsPatients and controls were obtained from the Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH2012 case-cohort, which includes all patients with selected psychiatric disorders born in Denmark 1981-2005 along with randomly selected population controls (end of follow-up, December 31, 2016). The associations between individual psychiatric disorders and hydrocephalus were estimated using binary logistic regression with adjustment for age and sex.ResultsThe cohort consisted of 86,571 individuals, of which 14,654 were diagnosed with autism spectrum disorder, 28,606 were population controls, and the remaining were diagnosed with other psychiatric disorders. We identified 201 hydrocephalus cases; 68 among autism spectrum disorder patients and 40 among controls (OR 3.77, 95% CI 2.48-5.78), which corresponds to an absolute risk of 0.46 % (i.e. approximately one in 217 children with autism spectrum disorder had co-occurring hydrocephalus). The autism spectrum disorder-hydrocephalus association was significant over the entire subgroup spectrum of autism spectrum disorder.ConclusionsGiven the considerable risk of hydrocephalus among patients with autism spectrum disorder, we suggest that patients with autism spectrum disorder should be evaluated for co-occurring hydrocephalus on a routine basis as timely neurosurgical intervention is important. Likewise, attention must be paid to traits of autism spectrum disorder in children with hydrocephalus. The results of this study call for future investigations on a potential shared aetiology between hydrocephalus and autism spectrum disorder, including the role abnormal CSF dynamics in the pathogenesis of autism spectrum disorder.

Project description:Background: The diagnosis of autism spectrum disorder (ASD) relies on behavioral assessment. Efforts to define biomarkers of ASD have not resulted in an objective, reliable test. Studies of RNA levels in ASD have demonstrated potential utility, but have been limited by a focus on single RNA types, small sample sizes, and lack of developmental delay controls. We hypothesized that a saliva-based poly-"omic" RNA panel could objectively distinguish children with ASD from their neurotypical peers and children with non-ASD developmental delay. Methods: This multi-center cross-sectional study included 456 children, ages 19-83 months. Children were either neurotypical (n = 134) or had a diagnosis of ASD (n = 238), or non-ASD developmental delay (n = 84). Comprehensive human and microbial RNA abundance was measured in the saliva of all participants using unbiased next generation sequencing. Prior to analysis, the sample was randomly divided into a training set (82% of subjects) and an independent validation test set (18% of subjects). The training set was used to develop an RNA-based algorithm that distinguished ASD and non-ASD children. The validation set was not used in model development (feature selection or training) but served only to validate empirical accuracy. Results: In the training set (n = 372; mean age 51 months; 75% male; 51% ASD), a set of 32 RNA features (controlled for demographic and medical characteristics), identified ASD status with a cross-validated area under the curve (AUC) of 0.87 (95% CI: 0.86-0.88). In the completely separate validation test set (n = 84; mean age 50 months; 85% male; 60% ASD), the algorithm maintained an AUC of 0.88 (82% sensitivity and 88% specificity). Notably, the RNA features were implicated in physiologic processes related to ASD (axon guidance, neurotrophic signaling). Conclusion: Salivary poly-omic RNA measurement represents a novel, non-invasive approach that can accurately identify children with ASD. This technology could improve the specificity of referrals for ASD evaluation or provide objective support for ASD diagnoses.

Dataset Information

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

Publications

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

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