Depression is a complex condition influenced by psychological, biological, and social factors, leading to wide variation in its symptoms and causes. As such, treatment must also be highly individualized, often involving a mix of medication, therapy, and lifestyle changes.

To improve treatment precision, psychologists from the University of Alberta and Radboud University in the Netherlands conducted a decade-long, multi-institutional study. Published in PLOS One, their research introduces a personalized approach to treating depression based on individual characteristics like age and gender.

“First-line treatment shouldn't be one-size-fits-all,” said Zachary Cohen, senior author and U of A assistant professor of psychology. Currently, treatment often relies on trial and error, with about half of patients not responding to the first therapy tried.

Focusing on adult depression, the team analyzed data from over 60 global clinical trials involving nearly 10,000 patients. These trials covered five common treatments: antidepressant medications, cognitive therapy, behavioral therapy, interpersonal therapy, and short-term psychodynamic therapy. Patients were assessed for factors including coexisting psychiatric conditions like anxiety and personality disorders.

“We looked at whether certain features, like comorbidities, predicted better outcomes with specific treatments,” said lead author Ellen Driessen of Radboud University.

The goal is to create a clinical decision-support tool- an algorithm that processes multiple variables to recommend the most effective treatment for each individual.

Building this model has required years of data sharing and collaboration across disciplines and countries. “Just cleaning and merging the data took five years,” Cohen noted. While this paper outlines the protocol, the actual tool is expected to be developed over the next couple of years.

Source: https://news.arizona.edu/news/new-precision-mental-health-care-approach-depression-addresses-unique-patient-needs