Fairfax, VA—Billions of dollars of antidepressants are prescribed each year, but as pharmacists are aware, most patients don’t get enough relief from their first medication.

What if there was a way for primary care physicians and psychiatrists to better predict which medications would be effective?  A new study suggests that might be possible.

George Mason University researchers point out that 11% of the U.S. population has an antidepressant prescription, but 60% of these patients do not benefit from their first antidepressant. Sales of antidepressants exceed several billion dollars annually.

Their study in the Lancet publication EClinical Medicine suggests that a patient’s existing medical conditions can have an effect on which antidepressant works best.

The study analyzed the use of 15 different antidepressants in patients who had multiple comorbidities or medical conditions. The retrospective, observational, matched case-control study used claims data available through OptumLabs for depressed patients treated with antidepressants between January 1, 2001, and December 31, 2018. The cohort included patients from all 50 states.

For their analysis, researchers focused on 3.7 million patients with major depression who had more than 10 million antidepressant treatments. By dividing the cohort into 16,770 subgroups, the researchers were able to report remission rates for the antidepressants used by these patients.

The authors concluded that “the choice of the optimal antidepressant depended on the strata defined by the patient's medical history.”

The authors noted that those study findings might not be appropriate for specific patients, adding that clinicians can visit a website to assess the transferability of study findings to specific patients.

Janusz Wojtusiak, PhD, associate professor, used the data to build the website, which is designed to help individuals with depression determine which agent will work best for them. By entering a patient’s medical history into the site, users can find similar cases in the data and receive recommendations for antidepressants based on the experience of symptom remission in other patients. Patients can share those recommendations with their clinicians to ensure their appropriateness for their individual cases.

“Unlike with previously published randomized studies, the remission rates in the study differed significantly based on the subgroup’s medical history,” said lead author Farrokh Alemi, PhD.  “The choice of the optimal antidepressant depended on the subgroup matched to the patient’s medical history.”

Dr. Alemi pointed out that in the age and gender subgroups, the best antidepressant had an average remission rate of 50.78%, which was 1.5 times higher than the average antidepressant, which has a 30.3% remission rate. It also was 20 times higher than the worst antidepressant used in the age and gender subgroup, he said.

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