Simple identification of complex ADHD subtypes using current symptom counts

OBJECTIVE: New attention-deficit/hyperactivity disorder (ADHD) subtypes identified through latent class analysis have been recently proposed. Here, we assess the accuracy of simple rules based on symptom counts for the assignment of youths to clinically relevant population-derived ADHD subtypes: severe inattentive (SI) and severe combined (SC). METHOD: Data from 9,675 twins and siblings from Missouri and Australia aged 7 to 19 years were analyzed using continuous and categorical models of ADHD symptoms using principal components analysis and subtyping by DSM-IV and by latent class criteria. Cut points were derived for classifying SI and SC subtypes by positive predictive value, negative predictive value, percent positive agreement, and Matthew coefficient of agreement. RESULTS: Principal components analysis suggested two underlying factors: total number of symptoms and symptom type, with SI and SC latent class subtypes clearly mapping to distinct areas on a plot of these factors. Having six or more total symptoms and fewer than three hyperactive-impulsive symptoms accurately predicts the latent class SI subtype. The latent class SC subtype was best identified by 11 or more total symptoms and 4 or more hyperactive- impulsive. The DSM-IV ADHD subtype criteria accurately identified the SC subtype but only poorly for the SI subtype. CONCLUSIONS: Symptom counts criteria allow the simple and accurate identification of subjects with severe ADHD subtypes defined by latent class analysis. Such simple symptom counts corresponding to screening cut points selected latent class-derived SI subtype subjects with greater precision than DSM-IV criteria.