Philadelphia, PA-- As in any other field of medicine, when a depressed person visits a psychiatrist for treatment of depression, they like to be informed of the odds that they will respond to the medication they are prescribed. Unfortunately, there has been no precise way to predict antidepressant response in individual patients.
It would be very nice to have an equation that would enable doctors to predict the likelihood that individual patients would respond to specific treatments. Accurate predictions are likely to be challenging. The ability to accurately predict the likelihood of antidepressant response for individual patients could be an important step in developing individualized treatment plans.
The effectiveness of antidepressant medications varies tremendously across patients and the overall effectiveness of current medications is lower than previously expected. For example, the largest antidepressant trial ever conducted -- the NIMH STAR*D study -- provided somewhat discouraging news about the effectiveness of antidepressants. Only 30% of patients responded to their initial antidepressant and after one year and up to four different treatments, 30% of patients did not achieve remission.
In this issue of Biological Psychiatry, Dr. Roy Perlis at Massachusetts General Hospital has taken an important step toward this objective.
He gathered data collected from the STAR*D study and used multiple prediction models to identify statistical patterns. Using the best-performing model, he then generated an online risk calculator and visualization tool that provides a graphical estimate of an individuals' risk for treatment resistance.
"To address the needs of individual depressed patients, we will need to find ways to design psychiatric treatments to respond to the differences among patients with depression. The 'depression calculator' that emerges from the STAR*D trial is one step forward in this effort," sai
|Contact: Rhiannon Bugno|