Algorithm connects patients to anti-depressants

An algorithm can help connect patients who need anti-depressants with the right ones.

Researchers from McLean Hospital completed a study that planned to determine which people with depression are best suited for antidepressant medications, according to Science Daily. Their findings were published in Psychological Medicine on July 2, 2018, and led to the development of a statistical algorithm that identifies patients who may best respond to antidepressants, before they begin treatment.

Christian A. Webb, PhD, director of the Treatment and Etiology of Depression in Youth Laboratory at McLean Hospital, is one of the study’s coauthors, so are Diego A. Pizzagalli, PhD, director of McLean’s Center for Depression, Anxiety and Stress Research. Webb explained how their work: “Personalized Prediction of Antidepressant v. Placebo Response: Evidence from the EMBARC Study,” went from data derived from a large and recently completed multi-site clinical trial of antidepressant medications called Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC).

Webb and his colleagues developed an algorithm predicting that approximately one-third of individuals would receive benefits from antidepressant medications similar to placebo. In the study, participants were randomly assigned to a common antidepressant medication or a placebo pill.

Webb said that the results were like previous clinical trials in that “we found relatively little difference in average symptom improvement between those individuals randomly assigned to the medication vs. placebo. For the one-third of individuals predicted to be better suited to antidepressants, they had significantly better outcomes if they happened to be assigned to the medication rather than the placebo.”

Webb said that he will work further with his team on the subject.

Leave a Reply

Your email address will not be published. Required fields are marked *