Although antidepressants are one of the most frequently taken medications in the United States (11% of the population takes antidepressants) 60% of depressed patients do not benefit from their first antidepressant.
The sales of antidepressants exceed several billion dollars annually.
In a new study from George Mason University, researchers found a person’s existing medical conditions can have an influence on which antidepressant may work best.
The data from the study can help millions alleviate depression symptoms more effectively and are now available to clinicians and patients in an online database.
In the study, the team summarized the experiences of patients who have multiple comorbidities, or medical conditions, using 15 different antidepressants.
They analyzed data from more than 3.6 million patients with major depression who had more than 10 million antidepressant treatments.
Patients were broken into more than 16,000 subgroups based on conditions, demographic information, and prescribed medications to analyze their experiences using antidepressants.
The team used the data to build a website designed to help individuals with depression find what 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.
The team found unlike previously published randomized studies, the remission rates in the study differed significantly based on the subgroup’s medical history.
The choice of the optimal antidepressant depended on the subgroup matched to the patient’s medical history.
As an example, in the age and gender subgroups, the best antidepressant had an average remission rate of 50.78%, 1.5 times higher than the average antidepressant, which has a 30.3%remission rate.
This was 20 times higher than the worst antidepressant used in the age and gender subgroup.
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The study is published in EClinical Medicine. One author of the study is Farrokh Alemi, Ph.D.
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