domingo, 8 de febrero de 2015

Predictors of Later Outcomes in Younger Siblings of Children With Autism Spectrum Disorder - NIH OBSSR: The Connector

Predictors of Later Outcomes in Younger Siblings of Children With Autism Spectrum Disorder - NIH OBSSR: The Connector



Photo of 2 young siblings lying on a bed

Predictors of Later Outcomes in Younger Siblings of Children With Autism Spectrum Disorder

By William Riley, Ph.D. on 






Photo of Dr. William Riley

Dr. William Riley, OBSSR Acting Director
Identifying early signs of Autism Spectrum Disorder (ASD) could not only improve screening and diagnosis, but also inform the development of novel treatments.
ASD is a severe neurobehavioral disorder with an early onset that is characterized by impairments in communication and social capabilities as well as sensory and repetitive behaviors. Because of the early childhood onset, it is difficult to identify a high risk group of young children who can be followed over time to recognize early signs of ASD.
The heredity of ASD, however, makes younger siblings of ASD children a potential high risk group for developing the disorder. One place to find a good sample of at risk siblings is the Baby Siblings Research Consortium (BSRC). It is formed of 25 principal investigators across 21 research institutions in four countries that study early autism risk factors, including behavioral and neurobehavioral measures.
Using the BSRC and with funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and from the National Institute of Mental Health, Katarzyna Chawasrska and colleagues conducted a study of 719 younger siblings of children with ASD.
The results of the study are discussed in the article 18-month predictors of later outcomes in younger siblings of children with autism spectrum disorder: a baby siblings research consortium study, in the latest issue of the Journal of the American Academy of Child and Adolescent Psychiatry.
The study participants were assessed at 18 months on a range of cognitive, behavioral, and social measures of development and followed until 36 months of age to assess for symptoms of ASD.
The researchers used a machine learning approach, Classification and Regression Trees (CART), to generate a predictive model. Three distinct combinations of features at 18 months predicted ASD at 36 months:
  1. poor eye contact combined with a lack of communicative gestures and giving,
  2. poor eye contact combined with a lack of imaginative play, and
  3. lack of giving and the presence of repetitive behaviors, but with normal eye contact.
These behavioral models predicted ASD with 82.7% accuracy in the test sample, and with 77.3% accuracy in the validation sample.
The findings suggest different developmental pathways to ASD that with further exploration could produce developmentally specific treatments for the disorder.
Image of chart depicting Classification and Regression Tree (CART) diagram predicting groups with autism spectrum disorder (ASD), atypical development (ATYP), and typical development (TD) based on 18-month Autism Diagnostic Observation Schedule (ADOS) item data
Image reposted from Journal of the American Academy of Child & Adolescent Psychiatry, Vol 53, Katarzyna Chawarska et. al.,18-Month Predictors of Later Outcomes in Younger Siblings of Children With Autism Spectrum Disorder: A Baby Siblings Research Consortium Study, Pages 1317–1327, Copyright (2014), with permission from Elsevier.

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