Mega-analytic support for Early Start Denver Model, age at intervention start, and pre-intervention developmental level as factors differentiating early intervention outcomes in autism

ObjectiveAutism early intervention meta-analyses have provided initial answers to questions such as what types of interventions work and for what outcomes? However, we also want to know for whom is early intervention most effective for? Mega-analysis can offer up complementary insights to meta-analyses regarding the what works and for what, while also offering unique insights into the for whom question. MethodsHere we conduct a mega-analysis with linear mixed effect modeling on AEIR consortium early intervention datasets totaling n=645 children spanning several countries (e.g., USA, Switzerland, Italy, Israel, and Australia). Early Start Denver Model (ESDM) and other non-ESDM approaches (e.g., EIBI, NDBI, other community/treatment as usual approaches) was evaluated as contrasting intervention types. Models also evaluated intervention intensity, type, participant sex, age at intervention start, and pre-intervention developmental quotient. Subscales of Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behavior Scales (VABS), and Autism Diagnostic Observation Schedule (ADOS) were utilized as outcome measures. ResultsNeither intervention intensity nor participant sex affected outcomes. ESDM showed faster growth in language and non-verbal cognition compared to non-ESDM intervention. Irrespective of intervention type, earlier intervention start was associated with increased MSEL and VABS scores and decreased ADOS severity. Growth trajectories on the MSEL also varied by pre-intervention developmental quotient, with higher quotients predicting faster growth irrespective of intervention type. ConclusionsAge at intervention start and pre-intervention developmental quotient are important individualized factors that predict early intervention response. ESDM also impacts language, non-verbal cognition, and core autism features.