Abstract
There has been a surge of interest in biomarkers that can rapidly predict or assess response to psychiatric treatment, as the current standard practice of extended therapeutic trials is often dissatisfying to both clinicians and patients. Electroencephalographic (EEG) biomarkers in particular have been proposed as an inexpensive yet rapid way of determining whether a patient is responding to an intervention, usually before subjective mood improvement occurs. However, even the most well-reported EEG algorithms have not been subjected to independent replication, limiting their clinical generalizability. It is also unclear whether those biomarkers can generalize beyond their original study population, e.g. to patients undergoing somatic treatments for depression. We report here analysis of EEG data from the pivotal OPT-TMS study of transcranial magnetic stimulation (rTMS) for major depressive disorder. In this dataset, previously reported biomarkers of medication response showed no significant correlation with eventual response to rTMS treatment. Furthermore, EEG power in multiple bands measured at baseline and throughout the treatment course did not correlate with or predict either binary (response/nonresponse) or continuous (Hamilton Rating Scale for Depression) outcome measures. While somewhat limited by technical difficulties in data collection, these analyses are adequately powered to detect clinically relevant biomarkers. We believe this highlights a need for wider-scale independent replication of previous EEG biomarkers, both in pharmacotherapy and neuromodulation.