University of California scientists have identified a biomarker that can help accurately predict whether a particular drug will be effective in treating major depression.
During the study, the researchers measured changes in brain-wave patterns using quantitative electroencephalography (QEEG), a non-invasive, computerized measurement that recognizes specific alterations in brain-wave activity.
These changes precede improvement in mood by many weeks and appear to serve as a biomarker that accurately predicts how effective a given medication will be.
The new non-invasive test would help predict within a week whether a particular drug will be effective.
The added benefit of the biomarker test is that it is painless and fast - about 15 minutes - and only involves the placement of six electrodes around the forehead and on the earlobes.
The researchers recruited a total of 375 people who had been diagnosed with major depressive disorder (MDD) and prescribed the antidepressant escitalopram, commonly known as Lexapro.
Then they examined a biomarker called the antidepressant treatment response (ATR) index - a specific change in brain-wave patterns.
The study showed that the ATR predicted both response and remission with an accuracy rate of 74 percent, much higher than any other method available.
The researchers also found that they could predict whether subjects were more likely to respond to a different antidepressant, bupropion, also known as Wellbutrin XL.
"Until now, other than waiting, there has been no reliable method for predicting whether a medication would lead to a good response or remission," said Dr. Andrew Leuchter, professor of psychiatry at the Semel Institute for Neuroscience and Human Behavior at UCLA and lead author of the study.
"And that wait can be as long as 14 weeks. So these are very exciting findings for the patient suffering from depression," said Leuchter.
The study results appear in the journal Psychiatry Research.