For someone who's depressed, the wait for relief can seem endless.
In more than half of all patients, the first antidepressant drug that's prescribed simply doesn't work. And it can take months to figure out what does. Aside from trial and error, there's never been a straightforward test for figuring out which medication will be the most effective for a particular individual.
However, it looks as if that may change.
Thanks to a new test, patients may no longer have to wait to find the most effective treatment. A nationwide study led by UCLA, with funding from NARSAD, has resulted in a test that may enable clinicians to accurately predict within a week whether a particular drug will be effective in an individual who suffers from depression, allowing physicians to quickly identify patients who should switch to an alternative treatment to increase the likelihood of feeling better.
Non-Invasive Brain Wave Measurement
At the core is a non-invasive computerized measurement known as quantitative electroencephalography, which measures changes in brain-wave patterns and has the ability to recognize specific changes over time. These changes precede improvement in mood by many weeks, helping to predict how effective a particular medication will be.
The process is simple: A patient is interviewed, then relaxes in a comfortable recliner while five electrodes are applied, three to the forehead and two to the ears. The electrodes are hooked up to a computer that takes the required measurements. The entire procedure is completely painless and lasts about ten minutes.
After this procedure is completed, each individual starts antidepressant treatment. In this study, the medication was escitalopram, commonly known as Lexapro. This antidepressant is a selective serotonin re-uptake inhibitor, or SSRI, a class of drugs commonly prescribed for depression.
One week later, the patient is given a second electroencephalography, which enables doctors to see the way in which the individual's brainwave patterns changed. The key is that when people are treated and likely to get well, the prefrontal area exhibits specific changes in activity. This change yields a measurement, called the antidepressant treatment response index, linked to the likelihood a patient is going to recover using that medication.
A Small Window of Testing
"We found that one week of exposure was highly accurate in predicting who would get better and who wouldn't," explains Ian A. Cook, M.D., associate professor in the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine at UCLA and a Research Scientist at the UCLA Semel Institute for Neuroscience and Human Behavior and the UCLA Brain Research Institute.
Dr. Cook, one of the major contributors to the BRITE-MD trial (short for "Biomarkers for Rapid Identification of Treatment Effectiveness in Major Depression"), has been working on developing biomarkers since coming to UCLA in 1990.
"We also used clinical predictors, gene types, blood levels of medication, and symptom changes in this study," he adds. "Only the QEEG measure was predictive of remission. When we look back and say, ‘Could we have predicted this?' the answer was ‘Yes,' about 74% of the time, which was stronger than any of the other predictors in this study."
The implications for people suffering from depression are enormous.
"The work we've focused on for the past 15 years has been how to deal with the thorny clinical question of how to get people well as rapidly as possible," Dr. Cook notes. "A major impediment is getting people on the right medication. We have lots of data about what may work for groups of people - but not much as far as an actual predictor that says for an individual, ‘You're on the right medication, you should go with this' - or ‘this isn't likely to work with you.' Instead, it's been, ‘Try it and see.'
"We've been working on how to get away from the old paradigm by using biomarker-guided treatments such as looking at measuring features of brain activity," he says. "The idea of a biomarker is that there may be something biological that we can measure about individual patients that gives us information about their brain and how best to treat them."
Speeding Up Diagnosis of Medication Effectiveness
"Until now, other than waiting, there has been no reliable method for predicting whether a medication would lead to a good response or remission," says Andrew F. Leuchter, M.D., professor of psychiatry at the Semel Institute for Neuroscience and Human Behavior at UCLA and national director of the BRITE-MD trial. "And that wait can be as long as 14 weeks. So these are very exciting findings for the patient suffering from depression."
Dr. Leuchter also noted that research has shown that depression patients who do not get better with a first treatment, therefore experiencing prolonged suffering, are more likely to abandon treatment altogether and may become more resistant to treatment over time.
It is estimated that 15 million people in the United States experience a depressive episode each year, and that nearly 17 percent of adults will experience major depression in their lifetime.
"For many years, those of us in mental health care have longed to deliver on the promise of personalized medicine," Dr. Cook says. "And this project brings us closer to being able to realize this promise. We're not quite ready for prime time yet, but with replication of these findings, we're close."