{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T16:36:50Z","timestamp":1791823010347,"version":"4.3.4"},"reference-count":32,"publisher":"American Medical Association (AMA)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Autism detection early in childhood is critical to ensure that autistic children and their families have access to early behavioral support. Early correlates of autism documented in electronic health records (EHRs) during routine care could allow passive, predictive model-based monitoring to improve the accuracy of early detection.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To quantify the predictive value of early autism detection models based on EHR data collected before age 1 year.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This retrospective diagnostic study used EHR data from children seen within the Duke University Health System before age 30 days between January 2006 and December 2020. These data were used to train and evaluate L2-regularized Cox proportional hazards models predicting later autism diagnosis based on data collected from birth up to the time of prediction (ages 30-360 days). Statistical analyses were performed between August 1, 2020, and April 1, 2022.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Prediction performance was quantified in terms of sensitivity, specificity, and positive predictive value (PPV) at clinically relevant model operating thresholds.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Data from 45\u202f080 children, including 924 (1.5%) meeting autism criteria, were included in this study. Model-based autism detection at age 30 days achieved 45.5% sensitivity and 23.0% PPV at 90.0% specificity. Detection by age 360 days achieved 59.8% sensitivity and 17.6% PPV at 81.5% specificity and 38.8% sensitivity and 31.0% PPV at 94.3% specificity.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this diagnostic study of an autism screening test, EHR-based autism detection achieved clinically meaningful accuracy by age 30 days, improving by age 1 year. This automated approach could be integrated with caregiver surveys to improve the accuracy of early autism screening.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2022.54303","type":"journal-article","created":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T11:11:26Z","timestamp":1675336286000},"page":"e2254303","source":"Crossref","is-referenced-by-count":29,"title":["Predictive Value of Early Autism Detection Models Based on Electronic Health Record Data Collected Before Age 1 Year"],"prefix":"10.1001","volume":"6","author":[{"given":"Matthew M.","family":"Engelhard","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ricardo","family":"Henao","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina"},{"name":"Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina"},{"name":"Duke AI Health, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel I.","family":"Berchuck","sequence":"additional","affiliation":[{"name":"Department of Statistical Science, Duke University, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junya","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian","family":"Eichner","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darby","family":"Herkert","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott H.","family":"Kollins","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Olson","sequence":"additional","affiliation":[{"name":"Duke AI Health, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eliana M.","family":"Perrin","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland"},{"name":"Department of Pediatrics, Johns Hopkins University School of Nursing, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ursula","family":"Rogers","sequence":"additional","affiliation":[{"name":"Duke AI Health, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Connor","family":"Sullivan","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YiQin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guillermo","family":"Sapiro","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina"},{"name":"Duke Institute for Brain Sciences, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geraldine","family":"Dawson","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina"},{"name":"Duke Institute for Brain Sciences, Durham, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","published-online":{"date-parts":[[2023,2,2]]},"reference":[{"issue":"1","key":"zoi221535r1","doi-asserted-by":"publisher","first-page":"e17","DOI":"10.1542\/peds.2009-0958","article-title":"Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model.","volume":"125","author":"Dawson","year":"2010","journal-title":"Pediatrics"},{"issue":"9","key":"zoi221535r2","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1016\/j.jaac.2019.01.004","article-title":"A multisite randomized controlled two-phase trial of the Early Start Denver Model compared to treatment as usual.","volume":"58","author":"Rogers","year":"2019","journal-title":"J Am Acad Child Adolesc Psychiatry"},{"issue":"9","key":"zoi221535r3","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1111\/dmcn.v64.9","article-title":"Early intervention for very young children with or at high likelihood for autism spectrum disorder: An overview of reviews.","volume":"64","author":"Franz","year":"2022","journal-title":"Dev Med Child Neurol"},{"issue":"5","key":"zoi221535r4","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1542\/peds.2007-2361","article-title":"Identification and evaluation of children with autism spectrum disorders.","volume":"120","author":"Johnson","year":"2007","journal-title":"Pediatrics"},{"issue":"1","key":"zoi221535r5","doi-asserted-by":"publisher","DOI":"10.1542\/peds.2019-3448","article-title":"Executive summary: identification, evaluation, and management of children with autism spectrum disorder.","volume":"145","author":"Hyman","year":"2020","journal-title":"Pediatrics"},{"issue":"10321","key":"zoi221535r6","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1016\/S0140-6736(21)01541-5","article-title":"The Lancet Commission on the future of care and clinical research in autism.","volume":"399","author":"Lord","year":"2022","journal-title":"Lancet"},{"issue":"11","key":"zoi221535r7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.15585\/mmwr.ss7011a1","article-title":"Prevalence and characteristics of autism spectrum disorder among children aged 8 years\u2014Autism and Developmental Disabilities Monitoring Network, 11 sites, United States, 2018.","volume":"70","author":"Maenner","year":"2021","journal-title":"MMWR Surveill Summ"},{"issue":"4","key":"zoi221535r8","doi-asserted-by":"publisher","DOI":"10.1542\/peds.2018-3963","article-title":"Accuracy of autism screening in a large pediatric network.","volume":"144","author":"Guthrie","year":"2019","journal-title":"Pediatrics"},{"issue":"3","key":"zoi221535r9","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2021.46415","article-title":"Diagnostic accuracy of the Social Attention and Communication Surveillance-Revised With Preschool Tool for early autism detection in very young children.","volume":"5","author":"Barbaro","year":"2022","journal-title":"JAMA Netw Open"},{"issue":"2","key":"zoi221535r10","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1002\/imhj.21356","article-title":"An abbreviated screening instrument for autism spectrum disorders.","volume":"34","author":"Smith","year":"2013","journal-title":"Infant Ment Health J"},{"issue":"5","key":"zoi221535r11","doi-asserted-by":"publisher","first-page":"1151","DOI":"10.1007\/s10803-012-1656-z","article-title":"Sex differences in the timing of identification among children and adults with autism spectrum disorders.","volume":"43","author":"Begeer","year":"2013","journal-title":"J Autism Dev Disord"},{"issue":"6","key":"zoi221535r12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.15585\/mmwr.ss6706a1","article-title":"Prevalence of autism spectrum disorder among children aged 8 years\u2014Autism and Developmental Disabilities Monitoring Network, 11 sites, United States, 2014.","volume":"67","author":"Baio","year":"2018","journal-title":"MMWR Surveill Summ"},{"issue":"1","key":"zoi221535r13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1097\/DBP.0000000000000235","article-title":"Prevalence and characteristics of autism spectrum disorder among 4-year-old children in the Autism and Developmental Disabilities Monitoring Network.","volume":"37","author":"Christensen","year":"2016","journal-title":"J Dev Behav Pediatr"},{"issue":"2","key":"zoi221535r14","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1542\/peds.2010-1036","article-title":"Perinatal and neonatal risk factors for autism: a comprehensive meta-analysis.","volume":"128","author":"Gardener","year":"2011","journal-title":"Pediatrics"},{"issue":"3","key":"zoi221535r15","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1055\/s-0036-1597624","article-title":"Association of perinatal risk factors with autism spectrum disorder.","volume":"34","author":"Getahun","year":"2017","journal-title":"Am J Perinatol"},{"issue":"5","key":"zoi221535r16","doi-asserted-by":"publisher","first-page":"e817","DOI":"10.1542\/peds.2008-3582","article-title":"Can association between preterm birth and autism be explained by maternal or neonatal morbidity?","volume":"124","author":"Buchmayer","year":"2009","journal-title":"Pediatrics"},{"issue":"1","key":"zoi221535r17","doi-asserted-by":"publisher","first-page":"e54","DOI":"10.1542\/peds.2013-0819","article-title":"Comorbidity clusters in autism spectrum disorders: an electronic health record time-series analysis.","volume":"133","author":"Doshi-Velez","year":"2014","journal-title":"Pediatrics"},{"issue":"6","key":"zoi221535r18","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1111\/ppe.2008.22.issue-6","article-title":"Neonatal jaundice: a risk factor for infantile autism?","volume":"22","author":"Maimburg","year":"2008","journal-title":"Paediatr Perinat Epidemiol"},{"issue":"18","key":"zoi221535r19","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000006696","article-title":"Prenatal, perinatal, and postnatal factors associated with autism: a meta-analysis.","volume":"96","author":"Wang","year":"2017","journal-title":"Medicine (Baltimore)"},{"issue":"3","key":"zoi221535r20","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1007\/s10803-005-3301-6","article-title":"Variation in early developmental course in autism and its relation with behavioral outcome at 3-4 years of age.","volume":"35","author":"Werner","year":"2005","journal-title":"J Autism Dev Disord"},{"issue":"1","key":"zoi221535r21","doi-asserted-by":"publisher","first-page":"17677","DOI":"10.1038\/s41598-020-74458-2","article-title":"Health system utilization before age 1 among children later diagnosed with autism or ADHD.","volume":"10","author":"Engelhard","year":"2020","journal-title":"Sci Rep"},{"issue":"41","key":"zoi221535r22","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abf0354","article-title":"Reduced false positives in autism screening via digital biomarkers inferred from deep comorbidity patterns.","volume":"7","author":"Onishchenko","year":"2021","journal-title":"Sci Adv"},{"issue":"8","key":"zoi221535r23","doi-asserted-by":"publisher","first-page":"2283","DOI":"10.1007\/s10803-015-2361-5","article-title":"Co-occurring psychiatric disorders in preschool and elementary school-aged children with autism spectrum disorder.","volume":"45","author":"Salazar","year":"2015","journal-title":"J Autism Dev Disord"},{"issue":"3","key":"zoi221535r24","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1007\/s00787-010-0092-x","article-title":"Shared heritability of attention-deficit\/hyperactivity disorder and autism spectrum disorder.","volume":"19","author":"Rommelse","year":"2010","journal-title":"Eur Child Adolesc Psychiatry"},{"key":"zoi221535r25","doi-asserted-by":"publisher","first-page":"S91","DOI":"10.1542\/peds.2012-0900G","article-title":"Attention-deficit\/hyperactivity disorder symptoms, adaptive functioning, and quality of life in children with autism spectrum disorder.","volume":"130","author":"Sikora","year":"2012","journal-title":"Pediatrics"},{"issue":"5","key":"zoi221535r26","doi-asserted-by":"publisher","first-page":"317","DOI":"10.3109\/17518423.2013.846947","article-title":"The relationship of attention-deficit hyperactivity disorder and autism spectrum disorder to adaptive skills in young children.","volume":"18","author":"Turygin","year":"2015","journal-title":"Dev Neurorehabil"},{"issue":"4","key":"zoi221535r27","doi-asserted-by":"publisher","first-page":"e830","DOI":"10.1542\/peds.2015-1502","article-title":"Timing of the diagnosis of attention-deficit\/hyperactivity disorder and autism spectrum disorder.","volume":"136","author":"Miodovnik","year":"2015","journal-title":"Pediatrics"},{"key":"zoi221535r28","doi-asserted-by":"publisher","DOI":"10.1016\/j.socscimed.2022.114759","article-title":"Using electronic health records to understand the population of local children captured in a large health system in Durham County, NC, USA, and implications for population health research.","volume":"296","author":"Stolte","year":"2022","journal-title":"Soc Sci Med"},{"issue":"7","key":"zoi221535r29","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0159621","article-title":"Electronic health record based algorithm to identify patients with autism spectrum disorder.","volume":"11","author":"Lingren","year":"2016","journal-title":"PLoS One"},{"issue":"3","key":"zoi221535r30","doi-asserted-by":"publisher","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.","volume":"44","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"key":"zoi221535r31","first-page":"4768","article-title":"A unified approach to interpreting model predictions.","volume":"30","author":"Lundberg","year":"2017","journal-title":"Adv Neural Inf Process Syst"},{"issue":"4","key":"zoi221535r32","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.1177\/1362361318785171","article-title":"Delayed autism spectrum disorder recognition in children and adolescents previously diagnosed with attention-deficit\/hyperactivity disorder.","volume":"23","author":"Kentrou","year":"2019","journal-title":"Autism"}],"container-title":["JAMA Network Open"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/articlepdf\/2800898\/engelhard_2023_oi_221535_1675968311.50638.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T11:01:33Z","timestamp":1676631693000},"score":1,"resource":{"primary":{"URL":"https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/fullarticle\/2800898"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,2]]},"references-count":32,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,2,1]]}},"URL":"https:\/\/doi.org\/10.1001\/jamanetworkopen.2022.54303","relation":{},"ISSN":["2574-3805"],"issn-type":[{"value":"2574-3805","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,2]]}}}