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

This study is the first to evaluate an assessment aid for attention- deficit/hyperactivity disorder (ADHD) according to both Class-I evidence stan- dards of American Academy of Neurology and De Novo requirements of US Food and Drug Administration. The assessment aid involves a method to inte- grate 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 sep- arate 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 clini- cian’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 resolu- tion of a clinician’s uncertain cases (35/36). TBR showed statistical power spe- cific 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.

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