Can Depression Subtype Predict Treatment Success?


Researchers seek to determine whether depression subtype is an useful predictor of which medication regimen might be most effective in treating patients with those subtypes.

Depression and its co-morbidities logically fall into certain subtypes, but identifying those subtypes and then classifying patients within them can be, at best, challenging. Some research has specified categories such as dysthymic disorder, depression with melancholic features, depression with atypical features, depression with psychotic features, and other situational types, including post-partum and seasonal. But classifying patients into these subtypes involves some arbitrary decisions, and some of the subtypes can be difficult to distinguish.

The point of sub-categorization potentially goes beyond identifying etiology and pathophysiology. There could be a major treatment advance if research were to show that the category of depression could be a predictor of which medication regimen might be most effective in treating patients with those subtypes. This effort was a component of the seminal National Institutes of Mental Health Sequenced Treatment Alternatives to Relieve Depression (STAR*D) Study. It is also the main goal of a more recent study published in The American Journal of Psychiatry.

The aim of the study was to describe the proportions of patients who met criteria for melancholic, atypical, and anxious depressive subtypes (and subtype combinations), and then compare those profiles with treatment success for three different antidepressant medications. This was a large study of more than 1,000 patients who met criteria for major depressive disorder were randomly assigned to 8 weeks of treatment with escitalopram, sertraline, or extended-release venlafaxine.

Participants were classified by subtype. Those who met criteria for no subtype or multiple subtypes were classified separately, resulting in eight mutually exclusive groups. Thirty-nine percent of participants exhibited a pure-form subtype, 36% met criteria for more than one subtype, and 25% did not meet criteria for any subtype.

The researchers used a mixed-effects model using the intent-to-treat sample compared the groups’ symptom score trajectories, and logistic regression compared likelihood of remission (defined as a score ≤5 on the 16-item Quick Inventory of Depressive Symptomatology—Self-Report).

Unfortunately, as with the STAR*D results, likelihood of remission did not differ significantly between subtype groups, and depression subtype was not a moderator of treatment effect. All subtype groups exhibited a similar significant trajectory of symptom reduction across the trial. “The consistency of these findings with those of the Sequenced Treatment Alternatives to Relieve Depression trial suggests that subtypes may be of minimal value in antidepressant selection,” the study authors conclude.

While the result isn’t exactly devastating or surprising, it is discouraging; the possibility that certain subtypes of patients respond better to certain antidepressants could simplify treatment regimens that are often characterized by hit-and-miss medication therapies. That remains the status quo for now, but the study authors hope future research may be able to establish workable connections between depression subtypes and treatments.

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