Integration of an EEG biomarker with a clinician's ADHD evaluation

BACKGROUND: This study is the first to evaluate an assessment aid for attention-deficit/hyperactivity disorder (ADHD) according to both Class-I evidence standards of American Academy of Neurology and De Novo requirements of US Food and Drug Administration. The assessment aid involves a method to integrate an electroencephalographic (EEG) biomarker, theta/beta ratio (TBR), with a clinician's ADHD evaluation. The integration method is intended as a step to help improve certainty with criterion E (i.e., whether symptoms are better explained by another condition). METHODS: To evaluate the assessment aid, investigators conducted a prospective, triple-blinded, 13-site, clinical cohort study. Comprehensive clinical evaluation data were obtained from 275 children and adolescents presenting with attentional and behavioral concerns. A qualified clinician at each site performed differential diagnosis. EEG was collected by separate teams. The reference standard was consensus diagnosis by an independent, multidisciplinary team (psychiatrist, psychologist, and neurodevelopmental pediatrician), which is well-suited to evaluate criterion E in a complex clinical population. RESULTS: Of 209 patients meeting ADHD criteria per a site clinician's judgment, 93 were separately found by the multidisciplinary team to be less likely to meet criterion E, implying possible overdiagnosis by clinicians in 34% of the total clinical sample (93/275). Of those 93, 91% were also identified by EEG, showing a relatively lower TBR (85/93). Further, the integration method was in 97% agreement with the multidisciplinary team in the resolution of a clinician's uncertain cases (35/36). TBR showed statistical power specific to supporting certainty of criterion E per the multidisciplinary team (Cohen's d, 1.53). Patients with relatively lower TBR were more likely to have other conditions that could affect criterion E certainty (10 significant results; P ≤ 0.05). Integration of this information with a clinician's ADHD evaluation could help improve diagnostic accuracy from 61% to 88%. CONCLUSIONS: The EEG-based assessment aid may help improve accuracy of ADHD diagnosis by supporting greater criterion E certainty.