Background: This article analyzed data from the intervention arm of a large treatment trial to demonstrate the importance of clinical severity, course, comorbidity, and treatment response in patient prognosis.
Methods: This is a secondary analysis of data from a large primary care-based geriatric depression treatment trial that analyzes outcomes from the measurement-based stepped-care intervention arm (N=871 patients) to determine: whether increasing severity levels of depression at baseline were linked with other factors associated with poor depression outcomes such as double depression, anxiety, medical disorders, and high levels of neuroticism and pain; and whether patients with increasing levels of depressive severity would have more intervention visits and treatment trials based on a stepped-care algorithm, but would be less likely to reach remission and have a greater likelihood of re-emerging depression in the year after intervention.
Results: Increasing levels of depression severity were a robust predictor of lack of remission and were associated with other clinical variables that have been associated with lack of remission in earlier studies such as double depression, anxiety, medical comorbidity, high neuroticism levels, and chronic pain. Patients with higher levels of severity received significantly more intervention visits, more months of antidepressant treatment and more antidepressant trials, but had fewer depression-free days during the 12-month intervention and in the postintervention year.
Conclusion: Patients with higher levels of depression severity had worse clinical outcomes despite receiving greater intensity of treatment. A new classification of depression is proposed based on clinical severity, course of illness and treatment experience.