Cost Offset Associated With Early Start Denver Model for Children With Autism

Cidav, Zuleyha; Munson, Jeff; Estes, Annette; Dawson, Geraldine; Rogers, Sally J.; Mandell, David S.

doi:10.1016/j.jaac.2017.06.007

Cited by 103 publications

(96 citation statements)

References 33 publications

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“…Moreover, screening algorithms derived from machine learning (thus, sample dependent) analyses need replication using hypotheses driven designs. The feasibility of implementation in the general community must also be established, with consideration of necessary training, acceptability to parents, and costs, although potential long term savings related to improved outcomes resulting from earlier diagnosis and treatment should be taken into account 8. Finally, because of the etiologic heterogeneity of the disorder some biomarkers may be specific to certain subtypes of ASD and informative for only a subset of cases 113.…”

Section: Potential Clinical Utility Of Predictive Biomarkers For Asdmentioning

confidence: 99%

“…Cost effectiveness studies have modeled the potential long term functional benefits4 and savings56 associated with earlier access to interventions. In a two to three year follow-up of a clinical trial,7 toddlers who had received early intensive treatment not only experienced functional gains but also needed fewer services than those who received “treatment as usual,” resulting in overall cost savings 8. Thus, early intervention—and by extension, early diagnosis—have the potential to improve function and reduce societal costs.…”

Section: Introductionmentioning

confidence: 99%

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Autism spectrum disorder: advances in diagnosis and evaluation

Zwaigenbaum

Penner

2018

BMJ

182

137

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Autism spectrum disorder (ASD) has a variety of causes, and its clinical expression is generally associated with substantial disability throughout the lifespan. Recent advances have led to earlier diagnosis, and deep phenotyping efforts focused on high risk infants have helped advance the characterization of early behavioral trajectories. Moreover, biomarkers that measure early structural and functional connectivity, visual orienting, and other biological processes have shown promise in detecting the risk of autism spectrum disorder even before the emergence of overt behavioral symptoms. Despite these advances, the mean age of diagnosis is still 4-5 years. Because of the broad consistency in published guidelines, parameters for high quality comprehensive assessments are available; however, such models are resource intensive and high demand can result in greatly increased waiting times. This review describes advances in detecting early behavioral and biological markers, current options and controversies in screening for the disorder, and best practice in its diagnostic evaluation including emerging data on innovative service models.

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Section: Potential Clinical Utility Of Predictive Biomarkers For Asdmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Autism spectrum disorder: advances in diagnosis and evaluation

Zwaigenbaum

Penner

2018

BMJ

182

137

View full text Add to dashboard Cite

show abstract

“…Numerous studies (e.g., Refs. [13][14][15][16][17] have related improved clinical outcomes to early intervention, providing motivation for diagnosing individuals as early as accurate diagnosis is possible.…”

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confidence: 99%

Multivariate techniques enable a biochemical classification of children with autism spectrum disorder versus typically‐developing peers: A comparison and validation study

Howsmon

Vargason

Rubin

et al. 2018

Bioengineering & Transla Med

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Autism spectrum disorder (ASD) is a developmental disorder which is currently only diagnosed through behavioral testing. Impaired folate‐dependent one carbon metabolism (FOCM) and transsulfuration (TS) pathways have been implicated in ASD, and recently a study involving multivariate analysis based upon Fisher Discriminant Analysis returned very promising results for predicting an ASD diagnosis. This article takes another step toward the goal of developing a biochemical diagnostic for ASD by comparing five classification algorithms on existing data of FOCM/TS metabolites, and also validating the classification results with new data from an ASD cohort. The comparison results indicate a high sensitivity and specificity for the original data set and up to a 88% correct classification of the ASD cohort at an expected 5% misclassification rate for typically‐developing controls. These results form the foundation for the development of a biochemical test for ASD which promises to aid diagnosis of ASD and provide biochemical understanding of the disease, applicable to at least a subset of the ASD population.

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“…Recent research from other fields has shown that high-quality early learning programs for disadvantaged children can deliver a high return on investment, with positive long-term benefits across educational, health, social, and employment outcomes (García et al, 2017). Preliminary evidence suggests that high-quality ASD early interventions may hold the same potential (Cidav et al, 2017).…”

mentioning

confidence: 99%