Method to Test Etiologic Heterogeneity Among Non-Competing Diagnoses that Accrue Over Time: Application to Discriminating the Impact of Perinatal Exposures on Autism and Attention Deficit Hyperactivity Disorder

Background Testing etiologic heterogeneity – whether a disorder subtype is more or less impacted by a risk factor, is important toward understanding causal pathways and optimizing statistical power. The study of mental health disorders especially benefits from strategic sub-categorization because these disorders are heterogenous and frequently co-occur. Existing methods to quantify etiologic heterogeneity are not appropriate for non-competing events in an open cohort of variable-length follow-up. Thus, we developed a new method. Methods We estimated risks from urban residence, maternal smoking during pregnancy, and parental psychiatric history, with subtypes defined by the presence or absence of a co-diagnosis: autism alone, attention deficit hyperactivity disorder (ADHD) alone, and joint diagnoses of autism+ADHD. To calculate the risk of a single diagnosis (e.g. autism alone), we subtracted the risk for autism+ADHD from the risk for autism overall. We tested the equivalency of average risk ratios over time, using a Wald-type test and bootstrapped standard errors. Results Urban residence was most strongly linked with autism+ADHD and least with ADHD only; maternal smoking was associated with ADHD only but not autism only; and parental psychiatric history exhibited similar associations with all subgroups. Conclusions Our method allowed the calculation of appropriate p values to test strength of association, showing etiologic heterogeneity wherein 2 of these 3 risk factors exhibited different impacts across diagnostic subtypes. The method used all available data, avoided neurodevelopmental outcome misclassification, exhibited robust statistical precision, and is applicable to similar heterogeneous complex conditions using common diagnostic data with variable follow-up.