A change in rapid eye movement sleeping pattern as measured by quantitative EEG in patients with major depressive disorder after just a single week on a first-line antidepressant predicts eventual clinical response or nonresponse to the medication weeks later, Thorsten Mikoteit, MD, reported at the virtual congress of the European College of Neuropsychopharmacology.
This finding from a small, randomized, controlled trial opens the door to a novel biomarker-based treatment strategy: namely, an immediate switch to a different antidepressant in predicted nonresponders to the first agent. The goal is to improve the final treatment response rate while collapsing the time required to get there, explained Dr. Mikoteit, a psychiatrist affiliated with the University of Basel (Switzerland).
“In real terms, it means that patients, often in the depths of despair, might not need to wait weeks to see if their therapy is working before modifying their treatment,” he observed.
There is a huge unmet need for a biomarker predictive of response to antidepressant medication in patients with major depression, the psychiatrist added. At present, the treatment response rate is unsatisfactory. Moreover, clinical improvement takes a long time to achieve, often requiring several rounds of therapeutic trials during which patients are exposed to weeks of unpleasant side effects of drugs that are ultimately switched out for lack of efficacy or poor tolerance.
The quantitative EEG biomarker under investigation is prefrontal theta cordance (PTC) during REM sleep. It is computed from the absolute and relative theta power in tonic REM sleep. PTC has been shown to correlate with frontocingulate brain activity and cerebral blood perfusion. In an earlier pilot study, Dr. Mikoteit and coinvestigators demonstrated in 33 patients who were experiencing a depressive episode that an increase in PTC after their first week on an antidepressant was associated a significantly increased treatment response rate at the end of the fourth week on the drug, while nonresponders failed to show such increase ().
At ECNP 2020, Dr. Mikoteit presented preliminary results from an ongoing randomized, controlled trial including 37 patients hospitalized for major depressive disorder. All underwent baseline evaluation using the Hamilton Depression Rating Scale (HAMD) and were placed on the first-line antidepressant of their psychiatrist’s choice. After 1 week of therapy, participants underwent polysomnography with PTC measurement during tonic REM sleep.
Twenty-two patients were randomized to the intervention arm, in which investigators informed treating psychiatrists of the PTC results. The clinicians were instructed to change to another antidepressant if the biomarker predicted nonresponse or stay the course if the PTC results were favorable. Polysomnography was repeated 1 week later in the intervention arm, and the second-line antidepressant was either continued or switched out depending on the PTC findings. In the control arm, psychiatrists weren’t informed of the PTC results and patients continued on their initial antidepressant. The intervention and control groups were comparable in terms of age, sex, and severity of depression, with an average baseline HAMD score of 22.
A treatment response was defined as at least a 50% reduction in HAMD score from baseline to week 5. About 86% of patients who switched antidepressants based upon their 1-week quantitative EEG findings were categorized as treatment responders at week 5, compared with 20% of controls.
The overall 5-week response rate in the intervention group was 73%, compared with 60% in the control arm. This favorable trend didn’t achieve statistical significance, presumably because of the study’s sample size; however, the study is continuing to enroll participants in order to achieve a definitive result.
Dr. Mikoteit noted that the cost and inconvenience of spending a night in a sleep laboratory would be worthwhile if it resulted in the ability to give effective treatment much sooner. This would be particularly advantageous in patients at increased risk for suicide.