Diagnosis and management of Cornelia de Lange syndrome: first international consensus statement.

Cornelia de Lange syndrome (CdLS) is an archetypical genetic syndrome that is characterized by intellectual disability, well-defined facial features, upper limb anomalies and atypical growth, among numerous other signs and symptoms. It is caused by variants in any one of seven genes, all of which have a structural or regulatory function in the cohesin complex. Although recent advances in next-generation sequencing have improved molecular diagnostics, marked heterogeneity exists in clinical and molecular diagnostic approaches and care practices worldwide. Here, we outline a series of recommendations that document the consensus of a group of international experts on clinical diagnostic criteria, both for classic CdLS and non-classic CdLS phenotypes, molecular investigations, long-term management and care planning.

Measurement invariance of the PROMIS emotional distress and subjective well-being domains among autistic and General Population adolescents.

PURPOSE: Quality of life (QoL) is identified as a clinical and research priority by the autistic community. Researchers have the responsibility to ensure that instruments used to measure QoL do so reliably and accurately among autistic participants. METHODS: Our study evaluated measurement invariance of Emotional Distress (Depression, Anxiety, Anger, Psychological Stress) and Subjective Well-Being (Life Satisfaction, Positive Affect, and Meaning & Purpose) scales of the Patient-Reported Outcomes Measurement Information System (PROMIS) among groups of autistic (N=140, n per scale=132-140) and general population (N=1,224, n per scale=406-411) teenagers (14-17 years). These scales were included in the PROMIS Autism Battery-Lifespan, which uses PROMIS scales to measure QoL domains most relevant for autistic people. RESULTS: Multi-group confirmatory factor analyses using permutation tests demonstrated that Depression and Positive Affect scales exhibited scalar invariance between groups, indicating that scores can be meaningfully compared across autistic and general population teens. Anger and Psychological Stress scales demonstrated metric invariance between groups, indicating that these scales measure the same latent trait in both groups, but group comparisons are not supported. CONCLUSION: We provide guidance as to how these scales can be used in psychometrically supported ways to capture constructs relevant for understanding QoL among autistic teens.

Quality of life is an important outcome for autistic people and their families. However, many quality of life scales have not been tested to make sure they accurately measure quality of life among autistic people. It is important to make sure that quality of life measures works similarly among the autistic population. The goal of our study is to test whether scales on a common quality of life measure ­ the Patient-Reported Outcomes Measurement Information System (PROMIS) ­ measures quality of life in the same way between autistic and general population adolescents. We found that some of the PROMIS scales worked the same way for autistic and general population adolescents and others did not. These results help researchers confidently use the PROMIS scales to measure different aspects of quality of life among autistic youth.

Delay from Screening to Diagnosis in Autism Spectrum Disorder: Results from a Large National Health Research Network.

To examine delay from developmental screening to autism diagnosis, we used real-world health care data from a national research network to estimate the time between these events. We found an average delay of longer than 2 years from first screening to diagnosis, with no significant differences observed by sex, race, or ethnicity.

Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.

BACKGROUND: Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations. METHODS: We comparatively evaluated these NLP tools using autism spectrum disorder (ASD) as a case study. We collected 827 ASD-related terms based on previous literature as the benchmark list for performance evaluation. Then, we applied CLAMP, cTAKES, and MetaMap on 544 full-text articles and 20,408 abstracts from PubMed to extract ASD-related terms. We evaluated the predictive performance using precision, recall, and F1 score. RESULTS: We found that CLAMP has the best performance in terms of F1 score followed by cTAKES and then MetaMap. Our results show that CLAMP has much higher precision than cTAKES and MetaMap, while cTAKES and MetaMap have higher recall than CLAMP. CONCLUSION: The analysis protocols used in this study can be applied to other neuropsychiatric or neurodevelopmental disorders that lack well-defined terminology sets to describe their phenotypic presentations.

Early Indicators of Creatine Transporter Deficiency.

Early identification is a goal for creatine transporter deficiency and will be critical for future treatment. Before their first birthday, one-half of this sample showed both a significant feeding/weight gain issue and delayed sitting or crawling. Combined, these early indicators could have alerted providers to conduct a urine screen.

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.

Missing Ethnicity and Language Information in Healthcare Records of Patients from the Asian Diaspora.

The electronic health record (EHR) should contain information to support culturally responsive care and research; however, the widely used default "Asian" demographic variable in most US social systems (including EHRs) lacks information to describe the diverse experience within the Asian diaspora (e.g., ethnicities, languages). This has a downstream effect on research, identifying disparities, and addressing health equity. We were particularly interested in EHRs of autistic patients from the Asian diaspora, since the presence of a developmental diagnosis might call for culturally responsive care around understanding causes, treatments, and services to support good outcomes. The aim of this study is to determine the degree to which information about Asian ethnicity, languages, and culture is documented and accessible in the EHR, and whether it is differentially available for patients with or without autism. Using electronic and manual medical chart review, all autistic and "Asian" children (group 1; n = 52) were compared to a randomly selected comparison sample of non-autistic and "Asian" children (group 2; n = 50). Across both groups, manual chart review identified more specific approximations of racial/ethnic backgrounds in 54.5% of patients, 56% for languages spoken, and that interpretation service use was underestimated by 13 percentage points. Our preliminary results highlight that culturally responsive information was inconsistent, missing, or located in progress notes rather than a central location where it could be accessed by providers. Recommendations about the inclusion of Asian ethnicity and language data are provided to potentially enhance cultural responsiveness and support better outcomes for families with an autistic child.

Early diagnosis of autism spectrum disorder: stability and change in clinical diagnosis and symptom presentation.

BACKGROUND: Although a diagnosis of autism spectrum disorder (ASD) appears to be stable in children as young as age three, few studies have explored stability of a diagnosis in younger children. Predictive value of diagnostic tools for toddlers and patterns of symptom change are important considerations for clinicians making early diagnoses. Most findings come from high-risk samples, but reports on children screened in community settings are also needed. METHODS: Stability of diagnosis and Autism Diagnostic Observation Schedule ­ Toddler Module (ADOS-T) classifications and scores was examined across two time points in a sample of 82 children identified through the FIRST WORDS Project.Children received two comprehensive diagnostic evaluations at average ages of 19.39 (SD = 2.12) and 36.89 (SD = 3.85) months. RESULTS: Stability was 100% when confirming and ruling out a diagnosis of ASD based on a comprehensive diagnostic evaluation that included clinic and home observations,although diagnosis was initially deferred for 17% of the sample. Receiver Operating Characteristic curves revealed excellent sensitivity and acceptable specificity for the ADOS-T compared to concurrent diagnosis. Logistic regressions indicated good predictive value of initial ADOS-T scores for follow-up diagnosis. Finally, both ASD and Non-ASD children demonstrated a decrease in Social Affect scores (i.e.,improvement), whereas children with ASD demonstrated an increase in Restricted and Repetitive Behavior scores (i.e., worsening), changes that were accounted for by nonverbal developmental level in mixed model analyses. CONCLUSIONS: Short-term stability was documented for children diagnosed at 19 months on average, although a minority of children initially showed unclear diagnostic presentations.Findings highlight utility of the ADOS-T in making early diagnoses and predicting follow-up diagnoses. Children with ASD demonstrated improvement in social communication behaviors and unfolding of repetitive behaviors, suggesting that certain early patterns of change in symptoms may be characteristic of ASD. KEYWORDS: Autism spectrum disorder, developmental delay, diagnosis, development,assessment.

Lower Completion of Depression Screening and Higher Positivity Among Autistic Adolescents Across a Large Pediatric Primary Care Network.

OBJECTIVE: To examine rates of depression screening and positivity among autistic adolescents where electronic depression screening is administered universally; to compare rates between autistic and nonautistic youth; and to explore sociodemographic and clinical factors associated with screening completion and results. METHODS: We conducted a retrospective cohort study comparing 12-17-year-old autistic and nonautistic adolescents presenting for well-child care in a large pediatric primary care network between November 2017 and January 2019 (N = 60,181). Sociodemographic and clinical data, including PHQ-9-M completion status and results, were extracted digitally from the electronic health record and compared between autistic and nonautistic youth. Logistic regression explored the relationship between sociodemographic and clinical factors and screen completion and results, stratified by autism diagnosis. RESULTS: Autistic adolescents were significantly less likely to have a completed depression screen compared to nonautistic adolescents [67.0% vs 78.9%, odds ratio (OR) = 0.54, P < .01]. Among those with a completed screen, a higher percentage of autistic youths screened positive for depression (39.1% vs 22.8%; OR = 2.18, P < .01,) and suicidal ideation/behavior (13.4% vs 6.8%; OR = 2.13, P < .01). Factors associated with screening completion and positivity differed between autistic and nonautistic groups. CONCLUSIONS: Autistic adolescents were less likely to have a completed depression screen when presenting for well-child care. However, when screened, they were more likely to endorse depression and suicide risk. This suggests disparities in depression screening and risk among autistic youth compared to nonautistic youth. Additional research should evaluate the source of these disparities, explore barriers to screening, and examine longitudinal outcomes of positive results among this population.

Prevalence of autism spectrum disorder in a large pediatric primary care network.

LAY ABSTRACT: Historically, children from non-Hispanic Black and Hispanic backgrounds, those from lower-income families, and girls are less likely to be diagnosed with autism spectrum disorder. Under-identification among these historically and contemporaneously marginalized groups can limit their access to early, autism spectrum disorder-specific interventions, which can have long-term negative impacts. Recent data suggest that some of these trends may be narrowing, or even reversing. Using electronic health record data, we calculated autism spectrum disorder prevalence rates and age of first documented diagnosis across socio-demographic groups. Our cohort included children seen at young ages (when eligible for screening in early childhood) and again at least after 4 years of age in a large primary care network. We found that autism spectrum disorder prevalence was unexpectedly higher among Asian children, non-Hispanic Black children, children with higher Social Vulnerability Index scores (a measure of socio-economic risk at the neighborhood level), and children who received care in urban primary care sites. We did not find differences in the age at which autism spectrum disorder diagnoses were documented in children's records across these groups. Receiving primary care at an urban site (regardless of location of specialty care) appeared to account for most other socio-demographic differences in autism spectrum disorder prevalence rates, except among Asian children, who remained more likely to be diagnosed with autism spectrum disorder after controlling for other factors. We must continue to better understand the process by which children with autism spectrum disorder from traditionally under-identified and under-served backgrounds come to be recognized, to continue to improve the equity of care.

The earlier the better: An RCT of treatment timing effects for toddlers on the autism spectrum.

LAY ABSTRACT: Behavioral interventions that incorporate naturalistic, developmental strategies have been shown to improve outcomes for young children who receive an autism spectrum disorder (ASD) diagnosis. Although there is broad consensus that children on the spectrum should begin supports as soon as possible, the empirical evidence for this is relatively limited and little is known about the optimal age to start autism-specific interventions. Our team conducted a randomized controlled trial (RCT) to test the effects of starting intervention at different ages, using the Early Social Interaction (ESI) model, a parent-implemented intervention for toddlers on the spectrum. Participants included 82 autistic toddlers and their caregiver(s) who received 9 months of Individual-ESI and 9 months of Group-ESI, with the timing/order of these two treatment conditions randomized. Thus, families received the more intensive and individualized Individual-ESI at either 18 or 27 months of age. Results revealed that children who received Individual-ESI earlier showed greater treatment gains than those who received this intervention later. Gains were demonstrated in several areas, which included the use and understanding of language, social use of communication skills, and self-help skills. Importantly, these findings were specific to the intensive and individualized parent coaching model compared to group-based treatment, allowing us to rule out the possibility that these timing effects were due to children getting older rather than the treatment itself. Our results suggest that even a narrow window of 18 versus 27 months may have an impact on outcomes and underscore the importance of screening and evaluation as young as possible.

Elevated amyloid beta peptides and total tau in cerebrospinal fluid in individuals with Creatine transporter deficiency.

Background: Creatine transporter deficiency (CTD) is a rare X-linked disorder of creatine transport caused by pathogenic variants in SLC6A8 (Xq28). The disorder is marked by developmental delay, especially speech delay. The biomarkers Aß40, Aß42 and total tau are abnormal in Alzheimer disease (AD), a common neurodegenerative disorder pathologically characterized by Aß peptide containing amyloid plaques and tau neurofibrillary tangles. Although CTD results in neuronal energy deficiency, the pathological processes underlying the CTD phenotype are not fully characterized. Methods: Cerebral spinal fluid (CSF) was collected as an optional part of a natural history study of CTD. Aß40, Aß42 and total tau levels were quantified in CSF from individuals with CTD and from age-appropriate comparison samples. Neuro3-Plex enzyme-linked immunoassay was performed on a Quanterix SR-X instrument. The Vineland Adaptive Behavior Scale, 3rd Edition was used to determine an overall Adaptive Behavior Composite (ABC) standard score. Results: CSF from 12 individuals with CTD and 23 age appropriate non-CTD comparison samples were analyzed. We found that levels of total tau [t(32) = 4.05, p = 0.0003], Aß40 [t(31) = 6.11, p < 0.0001], and Aß42 [t(32) = 3.20, p = 0.003] were elevated in the participants with CTD relative to the comparison group. Additionally, except for one individual that we considered an outlier, all three biomarkers correlated inversely with the adaptive behavior score (total tau: ρ = -0.60 [-0.88, 0.005]; Aß40: ρ = -0.67 [-0.91, -0.12]; Aß42: ρ = -0.62 [-0.89, -0.02]). Conclusion: We describe here the novel finding of elevated protein biomarkers in the CSF of individuals with CTD. Aß40, Aß42 and total tau are markedly elevated in individuals with CTD compared to comparison samples, and increased levels of these biomarkers inversely correlated with ABC scores. We hypothesize that elevated CSF levels of Aß40 and Aß42 are due to cellular energy deficiency. Elevated CSF total tau levels may indicate ongoing neuronal damage. The observed inverse correlation of Vineland ABC scores with increased biomarker levels needs to be confirmed in a larger CTD cohort; however, our observation of increased Aß40, Aß42 and total tau levels in CSF from individuals with CTD may provide insight into pathological mechanisms contributing to the CTD phenotype and may prove useful as supportive data in future therapeutic trials.

Corrigendum to "Elevated amyloid beta peptides and total tau in cerebrospinal fluid in individuals with Creatine transporter deficiency".

[This corrects the article DOI: 10.1016/j.ymgmr.2023.101001.].

Consistency and inconsistency in caregiver reporting of vocabulary.

Vocabulary checklists completed by caregivers are a common way of measuring children's vocabulary knowledge. We provide evidence from checklist data from 31 children with and without autism spectrum disorder. When asked to report twice about whether or not their child produces a particular word, caregivers are largely consistent in their responses, but where they are inconsistent, these inconsistencies affect verbs more than nouns. This difference holds both for caregivers of children with autism spectrum disorder and caregivers of typically-developing children. We suggest that caregivers may be less sure of their child's knowledge about verbs than nouns. This data converges with prior evidence comparing language samples of words children produce in a recorded interaction with checklist data, and it has implications for how researchers use checklist data in cases where the reliability of estimates of verb knowledge is critical.

Autism Spectrum Disorder Screening During the COVID-19 Pandemic in a Large Primary Care Network.

OBJECTIVE: To assess the impact of the COVID-19 pandemic on screening for autism spectrum disorder (ASD) and screening equity among eligible children presenting for well-child care in a large primary care pediatric network, we compared rates of ASD screening completion and positivity during the pandemic to the year prior, stratified by sociodemographic factors. METHODS: Patients who presented for in-person well-child care at 16 to 26 months between March 1, 2020 and February 28, 2021 (COVID-19 cohort, n = 24,549) were compared to those who presented between March 1, 2019 and February 29, 2020 (pre-COVID-19 cohort, n = 26,779). Demographics and rates of completion and positivity of the Modified Checklist for Autism in Toddlers with Follow-up (M-CHAT/F) were calculated from the electronic health record and compared by cohort using logistic regression models. RESULTS: Total eligible visits decreased by 8.3% between cohorts, with a greater decline in Black and publicly insured children. In the pre-COVID-19 cohort, 89.0% of eligible children were screened at least once, compared to 86.4% during the pandemic (P < 0.001). Significant declines in screening completion were observed across all sociodemographic groups except among Asian children, with the sharpest declines among non-Hispanic White children. Sociodemographic differences were not observed in screen-positive rates by cohort. CONCLUSIONS: Well-child visits and ASD screenings declined across groups, but with different patterns by race and ethnicity during the COVID-19 pandemic. Findings regarding screen-completion rates should not be interpreted as a decline in screening disparities, given differences in who presented for care. Strategies for catch-up screening for all children should be considered.

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyping ASD due in part to the lack of a validated, standardized vocabulary to characterize clinical phenotypic presentation of ASD. Although the human phenotype ontology (HPO) plays an important role in delineating nuanced phenotypes for rare genetic diseases, it is inadequate to capture characteristic of behavioral and psychiatric phenotypes for individuals with ASD. There is a clear need, therefore, for a well-established phenotype terminology set that can assist in characterization of ASD phenotypes from patients' clinical narratives. METHODS: To address this challenge, we used natural language processing (NLP) techniques to identify and curate ASD phenotypic terms from high-quality unstructured clinical notes in the electronic health record (EHR) on 8499 individuals with ASD, 8177 individuals with non-ASD psychiatric disorders, and 8482 individuals without a documented psychiatric disorder. We further performed dimensional reduction clustering analysis to subgroup individuals with ASD, using nonnegative matrix factorization method. RESULTS: Through a note-processing pipeline that includes several steps of state-of-the-art NLP approaches, we identified 3336 ASD terms linking to 1943 unique medical concepts, which represents among the largest ASD terminology set to date. The extracted ASD terms were further organized in a formal ontology structure similar to the HPO. Clustering analysis showed that these terms could be used in a diagnostic pipeline to differentiate individuals with ASD from individuals with other psychiatric disorders. CONCLUSION: Our ASD phenotype ontology can assist clinicians and researchers in characterizing individuals with ASD, facilitating automated diagnosis, and subtyping individuals with ASD to facilitate personalized therapeutic decision-making.

Healthcare utilization among children with early autism diagnoses, children with other developmental delays and a comparison group.

Aim: To describe healthcare utilization patterns among children with autism (n = 1821), and compare these patterns to children with other developmental delays (DD; n = 12,336) and a population comparison (PC; n = 18,210) cohort. Materials & methods: Retrospective study of administrative billing data. Results: Children with autism had roughly six-times more annual outpatient visits as PC children and twice as many as children with DD. Children with autism were more likely than PC children to use nearly all services, but comparisons between the autism and DD cohorts were mixed. Children with autism were more likely to have psychiatry/psychology visits, 'other' specialty care visits and psychotropic prescriptions, but less likely to have pediatric specialty care visits, immunizations and some prescriptions. Conclusion: Findings reveal opportunities to streamline, coordinate or improve care for young children with autism, particularly for outpatient services, and to give caregivers appropriate anticipatory guidance about what to expect after an autism diagnosis.

Lay abstract We compared how young children with autism use healthcare services versus children with other developmental delays (DDs) and a population comparison (PC) group. We examined medical billing records of children with private health insurance from across the USA. Children with autism were more likely than PC children to use nearly all healthcare services. Children with autism had about six-times as many annual outpatient visits as PC children and twice as many as children with DD. Children with autism were more likely to use some services and less likely to use other services compared with children with DD. For example, children with autism were more likely to have mental health visits and medications, but less likely to have pediatric specialty care visits or allergy medications. Outpatient visits and other healthcare services may need to be streamlined, coordinated or improved for young children with autism.

Provider Responses to Positive Developmental Screening: Disparities in Referral Practices?

OBJECTIVES: Guidelines recommend universal screening for developmental concerns in young children in pediatric primary care, with referral to early intervention (EI) as early as possible for children with a positive screen. However, participation in EI differs by child race, ethnicity, language, and sex. This study evaluated disparities in rates of referral to EI and estimated the factors associated with referral before and immediately after a positive developmental screen. METHODS: Children seen in a large primary care network that has implemented universal developmental screening were included if they screened positive on the Survey of Well-being of Young Children (SWYC) Milestones during a 16- to 30-month well-child visit (n = 7358). Demographics, screening results, and referrals were extracted from the electronic health record. RESULTS: Among children who screened positive, 17.5% were already in EI, and 39.9% were referred to EI during the visit with positive screen; 42.5% were not referred. In adjusted regression, the following factors were associated with being in EI before the positive screen: lower SWYC score and being male, older, and White. The following factors were associated with new referral to EI during a visit with positive SWYC: having lower SWYC score or lower income and being male, older, and Black race. CONCLUSION: The finding that White children were more likely referred before developmental screening and non-White children more likely referred at the time of positive screen suggests that screening decreases disparities by increasing referral for children with developmental delays from traditionally underserved backgrounds.

The Early Screening for Autism and Communication Disorders: Field-testing an autism-specific screening tool for children 12 to 36 months of age.

LAY ABSTRACT: There is a critical need for accurate screening tools for autism spectrum disorder in very young children so families can access tailored intervention services as early as possible. However, there are few screeners designed for children 18-24 months. Developing screeners that pick up on the signs of autism spectrum disorder in very young children has proved even more challenging. In this study, we examined a new autism-specific parent-report screening tool, the Early Screening for Autism and Communication Disorders for children between 12 and 36 months of age. Field-testing was done in five sites with 471 children screened for communication delays in primary care or referred for familial risk or concern for autism spectrum disorder. The Early Screening for Autism and Communication Disorders was tested in three age groups: 12-17, 18-23, and 24-36 months. A best-estimate diagnosis of autism spectrum disorder, developmental delay, or typical development was made. Analyses examined all 46 items and identified 30 items that best discriminated autism spectrum disorder from the non-spectrum groups. Cutoffs were established for each age group with good sensitivity and specificity. Results provide preliminary support for the accuracy of the Early Screening for Autism and Communication Disorders as an autism-specific screener in children 12-36 months with elevated risk of communication delay or autism spectrum disorder.

Adherence to screening and referral guidelines for autism spectrum disorder in toddlers in pediatric primary care.

OBJECTIVES: Although the American Academy of Pediatrics recommends screening for autism spectrum disorder (ASD) for all young children, disparities in ASD diagnosis and intervention in minority children persist. One potential contributor to disparities could be whether physicians take different actions after an initial positive screen based on patient demographics. This study estimated factors associated with physicians completing the follow-up interview for the Modified Checklist for Autism in Toddlers with Follow-up (M-CHAT-F), and referring children to diagnostic services, audiology, and Early Intervention (EI) immediately after a positive screen. METHODS: Children seen in a large primary care network that has implemented universal ASD screening were included if they screened positive on the M-CHAT parent questionnaire during a 16-30 month well child visit (N = 2882). Demographics, screening results, and referrals were extracted from the electronic health record. RESULTS: Children from lower-income families or on public insurance were more likely to have been administered the follow-up interview. Among children who screened positive, 26% were already in EI, 31% were newly referred to EI, 11% were referred each to audiology and for comprehensive ASD evaluation. 40.2% received at least one recommended referral; 3.7% received all recommended referrals. In adjusted multivariable models, male sex, white versus black race, living in an English-speaking household, and having public insurance were associated with new EI referral. Male sex, black versus white race, and lower household income were associated with referral to audiology. Being from an English-speaking family, white versus Asian race, and lower household income were associated with referral for ASD evaluation. A concurrent positive screen for general developmental concerns was associated with each referral. CONCLUSIONS: We found low rates of follow-up interview completion and referral after positive ASD screen, with variations in referral by sex, language, socio-economic status, and race. Understanding pediatrician decision-making about ASD screening is critical to improving care and reducing disparities.