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To predict which patients would respond to escitalopram, the researchers looked for particular changes in brainwave patterns between the first and second QEEG. Using an algorithm that considers various QEEG characteristics, called the antidepressant treatment response (ATR) index, the researchers found that they could accurately predict whether the patient would respond to the escitalopram 74 percent of the time. Leuchter says that’s much better than any other method currently available.

Earlier research had shown that the ATR index was relatively accurate at predicting a patient’s response to escitalopram. But this study went further, by determining that the biomarker could also be used to determine whether a patient would benefit by switching to another drug. “This is the first study that I am aware of that can predict differential response to two different medications,” Leuchter says. The research was published this month in the journal Psychiatry Research.

Dr. Dan Iosifescu, a coauthor of the study and director of translational neuroscience in the psychiatry department at Massachusetts General Hospital, explains that telling a patient they won’t respond to a drug isn’t “terribly useful” unless you can also tell them that they are more likely to benefit from another medication. After the success of this study, Iosifescu says it will be valuable to see whether the same results are found with other antidepressants.

The methodology used in the study could also be applied to drugs for other diseases, such as schizophrenia and Alzheimer’s disease, suggests Dr. Monte Buchsbaum, a professor of psychiatry and radiology at the University of California, San Diego, and editor-in-chief of Psychiatry Research.

Dr. Marcus Ising, a molecular psychology researcher at the Max Planck Institute of Psychiatry, says the study is helpful, but he believes it would be more valuable to try to find biomarkers that would evaluate the pathology of depression, as opposed to the effect of a drug.

Leuchter says that previous studies showed that the signal detected by the frontal electrodes comes from the anterior cingulate, a part of the brain that is “heavily involved in mood regulation,” so it makes sense that the signal would indicate antidepressant responsiveness.

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Credit: Aspect Medical Systems

Tagged: Biomedicine, EEG, biomarkers, depression, brain mapping, antidepressant

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