Now is the time for personalized treatment of depression

Depression is a complex interaction of psychological patterns, biological susceptibility and social stressors, making its causes and symptoms highly variable. Equally complex is the treatment of depression, requiring an individualized approach that may include a combination of medication, psychotherapy, and lifestyle changes.

In a decade-long multi-institutional study, psychologists at the University of South Africa, in collaboration with Radboud University in the Netherlands, developed a precision approach to treating depression that provides patients with individualized recommendations based on multiple characteristics, such as age and gender. The results of the study are published in the journal PLOS One.

According to Zachary Cohen, senior author of the paper and associate professor in the Department of Psychology at the University of South Africa, first-line treatment for depression should not be a “one size fits all” approach. Unfortunately, he says, the current standard of care largely involves a trial-and-error approach in which different medications or treatments are used until an intervention or combination is found that effectively alleviates symptoms.

About 50% of people do not respond to first-line treatment for depression. There is a great deal of heterogeneity in response to treatment, meaning there are people who respond very well to treatment and people who do not respond at all.

Zachary Cohen, lead author of the paper, an assistant professor in the Department of Psychology at the University of South Africa.

The study focused on depression in adults. The research team collected patient data from randomized clinical trials conducted around the world that evaluated the effectiveness of five commonly used treatments for depression.

According to Ellen Driessen, lead researcher and associate professor in the Department of Clinical Psychology at Radboud University, patients were assessed on a range of parameters, including the presence of co-occurring mental health conditions such as anxiety and personality disorders, before beginning treatment.

“We studied whether people with certain characteristics, such as the presence of comorbidities, might benefit more from one treatment method than another,” Driessen said.

The researchers hope their findings will lead to a clinical decision-making tool – an algorithm that simultaneously takes into account multiple variables such as age, gender and comorbidities, as well as the interrelationships between them, to create a single recommendation. Once a patient’s variables are entered into this tool, it will generate an individualized recommendation, as opposed to a protocol that provides a list of generalized recommendations.

The team’s data looked at clinical trials of antidepressants, cognitive therapy, behavioral therapy, interpersonal therapy and short-term psychodynamic therapy, a form of in-depth talk therapy.

“Most previous work on treatment selection has relied on data from single trials, where sample size limited the ability to develop powerful and reliable clinical prediction models,” Cohen says.

The research team spent about 10 years collecting and processing data from more than 60 trials involving nearly 10,000 patients. Researchers from around the world participated in the initiative by sharing data from their studies. The research team also assembled an international group of scientists from different fields to develop a strategy for analyzing the data.

In the future, the team plans to conduct a clinical trial to evaluate the benefits of using a clinical decision-making tool to help match patients with the best treatment. If the results are favorable, the tool could be expanded and implemented in real-world clinical settings. The researchers envision the tool to be a simple computer program or web application into which patient information can be entered.

The team hopes to provide clinicians, people with depression and society with a means to better utilize existing treatment resources and help reduce the enormous personal and societal costs associated with depression.

“If the results are generalized, the tool could be applicable worldwide,” Cohen says. “What’s interesting is that the variables that go into this tool are relatively easy to obtain through self-report questionnaires or clinical and demographic characteristics. The cost of implementing this approach will also be relatively low.”