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New Tool Estimates Resistance to Antidepressant Treatment

New Tool Estimates Resistance to Antidepressant TreatmentAccurately predicting the likelihood of antidepressant response for individual patients could be an important step in developing individualized treatment plans.

A new study led by Dr. Roy Perlis and published in the journal Biological Psychiatry goes a long way toward reaching that objective.

As it stands, the effectiveness of antidepressant medications varies tremendously across patients, and the overall effectiveness of current medications is less than stellar.

For example, in the largest antidepressant trial ever conducted — the STAR*D study, funded by the National Institute of Mental Health — just 30 percent of patients responded to their initial antidepressant. They study also found that after one full year and up to four different treatments, an astounding 30 percent of patients did not achieve remission.

In his study, Perlis 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,” said Dr. John Krystal, Editor of Biological Psychiatry.

“To do better than this, we will need to include biomarkers that may serve the function that blood tests and blood pressure measurements serve in other areas of medicine.”

Perlis agreed, commenting, “There has been great emphasis on the discovery of biomarkers to help predict clinical outcomes. No doubt this effort will succeed eventually.

“On the other hand, it’s entirely possible that clinical features can help get us part of the way there – that clinical features can help make useful predictions.”

“The analogy I would draw is the Framingham score for predicting cardiovascular risk. It’s far from perfect, and there’s plenty to criticize — but it has at least spurred efforts to use prediction in a clinical setting. It has also provided a platform to which biomarkers can be added, as they are identified,” he added.

In the meantime, the whole point of providing a clinical calculator online is to allow clinicians to try it out — to see what could be done, if the will and the resources were there.

Source: Elsevier

numerous bottles of pills photo by shutterstock.

New Tool Estimates Resistance to Antidepressant Treatment

Rick Nauert PhD

Rick Nauert, PhDDr. Rick Nauert has over 25 years experience in clinical, administrative and academic healthcare. He is currently an associate professor for Rocky Mountain University of Health Professionals doctoral program in health promotion and wellness. Dr. Nauert began his career as a clinical physical therapist and served as a regional manager for a publicly traded multidisciplinary rehabilitation agency for 12 years. He has masters degrees in health-fitness management and healthcare administration and a doctoral degree from The University of Texas at Austin focused on health care informatics, health administration, health education and health policy. His research efforts included the area of telehealth with a specialty in disease management.

APA Reference
Nauert PhD, R. (2018). New Tool Estimates Resistance to Antidepressant Treatment. Psych Central. Retrieved on November 24, 2020, from
Scientifically Reviewed
Last updated: 8 Aug 2018 (Originally: 2 Jul 2013)
Last reviewed: By a member of our scientific advisory board on 8 Aug 2018
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