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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.
Enhancing specific chemical signaling in the brain could help treat the disorder.
New technologies for treating depression could make the couch obsolete.
Studies suggest that deep brain stimulation could effectively treat depression.
This is yet another fine example of money wasted to support the failed drug industry model of perpetual medication as a "treatment" for chronic illness.
What we need is more research on natural ways to treat and cure illness using natural unpatentable substances like vitamins and other nutrients. A lot of this research has been done, but unfortunately it is largely ignored by medical schools and hospitals, whoa re always sucking up to the big drug companies.
The following nutrients have been shown to cure depression:
methyl donors
omega 3 fatty acids
chromium
selenium
methylfolate
B12
vitamin B6
vitamin D
SAM-e
and probably many more are waiting to be discovered. but instead of this actual useful research, we get garbage like this-designed to keep people sick and dependent on toxic drugs.
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190 Comments
statistics
According to the article, only a third of patients are successful with their first antidepressant. So, if I were to predict that a patient would not respond to escitalopram, I would presumably be right 67% of the time. This doesn't seem all that far from the 74% touted by this new method. Perhaps breaking down the statistics into false positives and false negatives would be more enlightening.
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