Can we predict a chronic course in major depressive disorder?

Major depressive disorder (MDD) is often perceived as an episodic condition, and many patients do recover from their relatively short index episode. For the majority of patients, however, this is not the case and their MDD follows a chronic and disabling trajectory, reported Professor Brenda Penninx, University of Amsterdam, the Netherlands.

MDD develops into a chronic disorder

A long-term follow-up of more than 900 patients with MDD showed that, over time, the proportion of patients in remission steadily declines. At 2-, 4-, and 6-year follow-up, the proportion of patients in remission was 58%, 41%, and 32%, respectively.¹

The concept of chronic MDD should include affective and anxiety disorders

Patients with MDD often suffer from comorbid affective (hypomanic symptoms and dysthymia) and anxiety conditions (generalized anxiety disorder, panic disorder, social phobia, and agoraphobia), Professor Penninx highlighted. Although conceptualised as distinct disorders, these conditions have similar physiological dysregulations to MDD, and should be included when examining the clinical course of patients.¹

Chronicity of MDD is the rule, not the exception

When considering this broader concept of MDD, the proportion of patients in remission were lower at each timepoint in the study described above (37%, 24%, and 17% at 2-, 4-, and 6-year follow-up, respectively). Chronic episodes of MDD/affective/anxiety conditions were experienced by a majority (55%) of patients.¹

Can we predict chronicity in patients with MDD?

To achieve the best therapeutic response, we need to be able to predict which patients will have a chronic disease course.

To achieve the best therapeutic response, we need to predict which patients will have a chronic disease course

Many variables have been linked to a poorer clinical course of MDD, including comorbid dysthymia and anxiety, more severe symptom severity, and  earlier age of onset.² These, however, are based on group comparisons, rather than predictors of clinical course for individual patients, said Professor Penninx.

The value of a wide range of clinical, psychological, and biological characteristics for predicting the course of depression in over 800 patients with MDD or dysthymia was evaluated in a machine learning-based model. At 2-year follow-up, only the Inventory of Depressive Symptomatology had predictive value on an individual patient level (with a 66% accuracy).³

Other techniques show promise for their value in predicting the clinical course of MDD. In a study evaluating different neuroimaging modalities and clinical characteristics in 118 patients, chronic patients could be discriminated from those with more favorable trajectories by neural responses to various emotional faces (up to 73% accuracy), but not by structural and functional magnetic resonance imaging.⁴

Epigenetics may also play a predictive role. In a study of 581 patients with MDD, there was a highly significant association between blood DNA methylation profiles and MDD status at 6-year follow-up.⁵

Studies that move beyond these key indicators are required to better understand the driving force behind trajectories in MDD.