Lessons from Population-Based Surveillance for ASD
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1 Lessons from Population-Based Surveillance for ASD Marshalyn Yeargin-Allsopp, MD Medical Epidemiologist Developmental Disabilities Branch National Center on Birth Defects and Developmental Disabilities Centers for Disease Control and Prevention IOM Workshop on Public Health Surveillance March 21 st, 2011 National Birth Defects Center and on Developmental Birth Defects and Disabilities Developmental BranchDisabilities
2 What is Autism?
3 Autism Spectrum Disorders (ASDs) Autism Spectrum Disorders (Pervasive Developmental Disorders) Autism, PDD-NOS, and Asperger s Disorder Diagnostic labels describing a pattern of unusual development affecting an individual early in life, and usually, throughout the lifespan Developmental disabilities with social, communication, and behavioral features No biologic test to confirm at present Diagnosis based on developmental history and observable behaviors Presentation changes with development
4 ASDs (continued) Complex group of disorders Social, communication, behavioral profile Many areas affected Overlap with other conditions Multiple causes likely Complex genetic and environmental interactions likely Wide range of impact Mild to severe impairment across areas
5 What is CDC s Role in Autism Surveillance?
6 Concerns Over Increases in Number of People with Autism It is clear that more children are identified with an Autism Spectrum Disorder (ASD) than in the past. Children diagnosed in a medical or clinical setting Children receiving services under a specific classification CA Department of Developmental Services
7 CDC s Public Health Action: ASD Surveillance
8 Autism and Developmental Disabilities Monitoring (ADDM) Network CDC formed the Autism and Developmental Disabilities Monitoring (ADDM) Network in an effort to better understand ASDs in the US. The network produced the first and largest multi-site report on ASD prevalence using common methods in the US (2007) Built on population-based study of DDs in the 1980s in metropolitan Atlanta (included epilepsy in 10-year-old children) Ongoing CDC surveillance of DDs started in 1991 (ID, CP, HL, VI); ASD added in 1996
9 Goals: Accurate and comparable populationbased estimates of the prevalence of Autism Spectrum Disorder (ASD) in selected regions of U.S Describe the characteristics of children with Autism Examine trends in prevalence
10
11 ADDM Network Methods Active case-finding with broad retrospective recordsbased screening for ASD classifications or behaviors Focus on children at age 8 to identify peak prevalence Multiple health and education sources of information Detailed behavioral, developmental, and testing information collected; no clinical examinations performed Ongoing quality control within and across sites Independent review and clinician confirmation of ASD case status based on the DSM-IV criteria Estimates considered the gold standard for the U.S.
12 ADDM Network Approach Children with autism identified in two phases: Phase 1: All children suspected of having autism who meet the age, study year, and parental residence requirements are identified through the screening and abstraction of source files at multiple educational, clinical and medical sources. Phase 2: Abstracted data from Phase 1 are systematically scored by clinician reviewers to determine whether the identified children meet the autism surveillance case definition.
13 ADDM Network Methods: Key Features Identify data sources in the community Department of Education programs for exceptional children Health department programs for children with developmental disabilities; local pediatric hospitals, clinics, diagnostic centers; other clinical providers that evaluate and treat children with ASD Request data from health and education sources on potential cases. Convert information received from the data requests into a standardized format and import into Access database. Screen source files of potential cases for autism triggers ASD diagnosis by a qualified professional OR Autism as primary disability category for special education services OR Autism behavioral triggers Abstract source files with autism triggers Record review and abstraction in the field into a copy of the Access database that each abstractor has on their laptop computer. Clinician review of abstracted data to determine case status Abstracted information is reviewed by clinician reviewers using a coding scheme based on DSM-IV-TR criteria for autistic disorder, PDD-NOS, and Asperger s disorder.
14 Annual Data Request Medical /Clinical Sources In January of each calendar year, MADDSP requests data on select children receiving inpatient/outpatient services (no limit on service date): Children 3-10 years of age Residing in the five-county metro Atlanta area With select ICD-9 diagnosis codes; the following types of conditions were used to generate potential case lists: ASD (Autistic Disorder, PDD-NOS, Asperger s Disorder) Conditions associated with ASD (e.g., Tuberous Sclerosis, Fragile X Syndrome) ASD differential diagnoses (e.g., Rett s Disorder, CDD, Selective Mutism, Expressive Language Disorder, Mixed Receptive-Language Disorder, Mental Retardation, Stereotypic Movement Disorder, ADHD) Data requested includes: name, birth date, race, sex, county of residence, patient type, diagnosis, service dates, medical record number
15 Access to Records Goal: to get as complete a count as possible of all children with ASD living in the catchment area during the study period of interest Institutional or agency permission to review records without parental consent is the best way to accomplish this goal MADDSP has a Memorandum of Agreement with GA State Department of Education and GA Department of Human Resources to access educational records. CDC serves as an authorized representative of the State DHR. All ADDM sites are considered public health surveillance for review of medical records (HIPAA).
16 ADDM Network Overall ASD Prevalence Estimates, Surv Year Birth Year # sites 8-year-old Population 8-year-old children with an ASD Average Prev / 1,000 Range ,761 1, ,578 2, ,335 1, , (14) In process In process
17 ADDM 2006 ASD Prevalence Results Average prevalence of ASD about 1% of 8- year-old children Average = about 1 in 110 children (range 1 in 80 to 1 in 240) Approximately 1 in 70 boys and 1 in 315 girls Prevalence increased 57% between 2002 and 2006 No single factor explains changes in ASD prevalence Some increases due to better documentation in records Despite slight improvements in age of diagnosis, significant delays persist
18 Prevalence by Race and Sex Subgroups Boys and Girls Average 4.5 boys to every girl identified with ASD Males = 14.5 per 1,000 (~ 1 in 70 boys) Females = 3.2 per 1,000 (~ 1 in 315 girls) Race/ethnicity White, non-hispanic children with highest ASD prevalence, but variability across sites White, non-hispanic: average 9.9 per 1,000 (~ 1 in 100 children) Black, non-hispanic: average 7.2 per 1,000 (~ 1 in 140 children) Hispanic: average 5.9 per 1,000 (~ 1 in 170 children)
19 Change in ASD Prevalence from 2002 to 2006 by Total, Sex, & Race or Ethnicity (10 Sites) % Change Average Total Males Females White non- Hispanic Black non- Hispani c Hispanic 57% 60% 48% 55% 41% 91% Data reflect increases in ASD prevalence overall and among subgroups site variation exists.
20 Strengths of ADDM Methods Only multi-site program focusing on surveillance Large, population-based identification of cases (10% of US 8-year olds in 2002) Standardization of methods across sites Training of abstracters, clinician reviewers; quality control Multiple sources; detailed information Clinical validation: (comparable to clinical screens): Ability to evaluate change in prevalence over time Data utility high Link to other data sources for risk factor analysis Ability to study co-occurring conditions
21 Limitations of ADDM Methods Inability to locate all records Quality/quantity of information in records Requires access to education records for completeness but not accessible at some sites because of FERPA regulations Does not include information on children home schooled, in private or charter schools No validation at all sites
22 ADDM ASD Successes Collaborative network Prevalence data for 4 surveillance years (2000 to 2006) Only ongoing population-based surveillance for multiple DDs in children in the US; considered the gold standard for ASD prevalence in the US Numerous ADDM reports from surveillance data) Data utility: l Healthcare/insurance reform Service provision
23 ADDM ASD Challenges Behavioral phenotype identified from records Proposed DSM-V changes; impact on ADDM? Methods: Access to education records, i.e., FERPA Labor intensive Changes in number of sites, size of geographic areas within sites over time Funding
24 Application of ADDM Methods to Cast a wide net Epilepsy Surveillance EEG labs important for epilepsy surveillance based on CDC study in the 1980s Agency permission rather than individual: Increased completeness Decreased bias Detailed information important Maximize efficiency: select peak prevalence age Community cooperation is essential Emphasize data utility
25 ADDM Reports in CDC s MMWR Surveillance Summaries: ADDM Video Updated autism website : Learn the Signs. Act Early. For more information please contact Centers for Disease Control and Prevention 1600 Clifton Road NE, Atlanta, GA Telephone, CDC-INFO ( )/TTY: cdcinfo@cdc.gov Web: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. National Center on Birth Defects and Developmental Disabilities
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