HealthDay News — Antidepressant treatment efficacy varies for empirically-defined clusters of symptoms, according to a study published in JAMA Psychiatry.
Adam M. Chekroud, from Yale University in New Haven, Connecticut, and colleagues determined the efficacy of antidepressant treatments on empirically defined groups of symptoms. Data on patients with depression from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial were used to identify clusters of symptoms. These findings were replicated using the Combining Medications to Enhance Depression Outcomes (CO-MED) trial. Using intent-to-treat data for the 4706 patients from both trials, the authors examined whether observed symptom clusters have differential response trajectories; data were also included for 2515 additional placebo and active-comparator phase 3 trials of duloxetine.
The researchers found that at baseline, there were three symptom clusters identified in the self-reported Quick Inventory of Depressive Symptomatology scale in STAR*D, which was replicated in CO-MED and was similar for the clinician-rated Hamilton Depression rating scale. Eight of 9 antidepressants were more effective for core emotional symptoms than for sleep or atypical symptoms. Between-drug differences in efficacy were often greater than the difference between treatments and placebo.
“Selecting the best drug for a given cluster may have a bigger benefit than that gained by use of an active compound versus a placebo,” the authors write.
Several authors disclosed financial ties to the pharmaceutical industry.
Chekroud AM, Gueorguieva R, Krumholz HM, et al. Reevaluating the Efficacy and Predictability of Antidepressant Treatments: A Symptom Clustering Approach. JAMA Psychiatry. 2017; doi: 10.1001/jamapsychiatry.2017.0025. [Epub ahead of print]