A simple questionnaire filled out by people suffering from depression can help identify whether a particular medication is likely to help them.
Researchers say data mined from clinical trials could soon help doctors tailor antidepressant therapy to their patients.
Currently, only about 30 percent of patients get relief from the first drug they are prescribed, and it can often take a year or more before doctors find the right medication to alleviate symptoms.
For a new study, published in the journal Lancet Psychiatry, scientists analyzed data from a large clinical trial on depression and pinpointed 25 questions that best predicted the patients’ response to a particular antidepressant.
Using these questions, they developed a mathematical model to predict whether a patient will respond to Celexa after three months of treatment.
“These are questions any patient can fill out in 5 or 10 minutes, on any laptop or smartphone, and get a prediction immediately,” says lead author Adam Chekroud, a PhD candidate in the Human Neuroscience Lab at Yale University.
The model performed better at predicting whether a patient would get better by using that drug than a group of practicing psychiatrists.
Researchers then tested the model by predicting outcomes in a second clinical trial, conducted years later. They found the model worked well in predicting patient responses to similar drugs (Lexapro, as well as a combination of Lexapro and Wellbutrin). However, the model did not predict response to drugs that have a different mechanism in the brain (Effexor and Remeron).
Once more data is analyzed from new and existing clinical trials, predictions about other treatment options will become available, says Philip Corlett, assistant professor of psychiatry and senior author of the study.
“And there is no reason why we can’t predict other important outcomes for our patients, like suicide or return to work,” he says.
This article was previously published by Yale University. Republished via Futurity.org under Creative Commons License 4.0.
