Adaptive behavior in autism: Minimal clinically important differences on the Vineland-II.

Autism Spectrum Disorder (ASD) is associated with persistent impairments in adaptive abilities across multiple domains. These social, personal, and communicative impairments become increasingly pronounced with development, and are present regardless of IQ. The Vineland Adaptive Behavior Scales, Second Edition (Vineland-II) is the most commonly used instrument for quantifying these impairments, but minimal clinically important differences (MCIDs) on Vineland-II scores have not been rigorously established in ASD. We pooled data from several consortia/registries (EU-AIMS LEAP study, ABIDE-I, ABIDE-II, INFOR, Simons Simplex Collection and Autism Treatment Network [ATN]) and clinical investigations and trials (Stanford, Yale, Roche) resulting in a data set of over 9,000 individuals with ASD. Two approaches were used to estimate MCIDs: distribution-based methods and anchor-based methods. Distribution-based MCID [d-MCID] estimates included the standard error of the measurement, as well as one-fifth and one-half of the covariate-adjusted standard deviation (both cross-sectionally and longitudinally). Anchor-based MCID [a-MCID] estimates include the slope of linear regression of clinician ratings of severity on the Vineland-II score, the slope of linear regression of clinician ratings of longitudinal improvement category on Vineland-II change, the Vineland-II change score maximally differentiating clinical impressions of minimal versus no improvement, and equipercentile equating. Across strata, the Vineland-II Adaptive Behavior Composite standardized score MCID estimates range from 2.01 to 3.2 for distribution-based methods, and from 2.42 to 3.75 for sample-size-weighted anchor-based methods. Lower Vineland-II standardized score MCID estimates were observed for younger and more cognitively impaired populations. These MCID estimates enable users of Vineland-II to assess both the statistical and clinical significance of any observed change. Autism Res 2018, 11: 270-283. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The Vineland Adaptive Behavior Scales (2nd edition; Vineland-II) is the most widely used scale for assessing day-to-day "adaptive" skills. Yet, it is unknown how much Vineland-II scores must change for those changes to be regarded as clinically significant. We pooled data from over 9,000 individuals with ASD to show that changes of 2-3.75 points on the Vineland-II Composite score represent the "minimal clinically-important difference." These estimates will help evaluate the benefits of potential new treatments for ASD.

Brain responses to biological motion predict treatment outcome in young children with autism.

Autism spectrum disorders (ASDs) are common yet complex neurodevelopmental disorders, characterized by social, communication and behavioral deficits. Behavioral interventions have shown favorable results-however, the promise of precision medicine in ASD is hampered by a lack of sensitive, objective neurobiological markers (neurobiomarkers) to identify subgroups of young children likely to respond to specific treatments. Such neurobiomarkers are essential because early childhood provides a sensitive window of opportunity for intervention, while unsuccessful intervention is costly to children, families and society. In young children with ASD, we show that functional magnetic resonance imaging-based stratification neurobiomarkers accurately predict responses to an evidence-based behavioral treatment-pivotal response treatment. Neural predictors were identified in the pretreatment levels of activity in response to biological vs scrambled motion in the neural circuits that support social information processing (superior temporal sulcus, fusiform gyrus, amygdala, inferior parietal cortex and superior parietal lobule) and social motivation/reward (orbitofrontal cortex, insula, putamen, pallidum and ventral striatum). The predictive value of our findings for individual children with ASD was supported by a multivariate pattern analysis with cross validation. Predicting who will respond to a particular treatment for ASD, we believe the current findings mark the very first evidence of prediction/stratification biomarkers in young children with ASD. The implications of the findings are far reaching and should greatly accelerate progress toward more precise and effective treatments for core deficits in ASD.