Objectives: We sought to examine whether there are patterns of evolving depression symptoms among older primary care patients that are related to prognostic factors and long-term clinical outcomes.

Method: Primary care practices were randomly assigned to Usual Care or to an intervention consisting of a depression care manager offering algorithm-based depression care. In all, 599 adults 60 years and older meeting criteria for major depression or clinically significant minor depression were randomly selected. Longitudinal analysis via growth curve mixture modeling was carried out to classify patients according to the patterns of depression symptoms across 12 months. Depression diagnosis determined after a structured interview at 24 months was the long-term clinical outcome.

Results: Three patterns of change in depression symptoms over 12 months were identified: high persistent course (19.1% of the sample), high declining course (14.4% of the sample), and low declining course (66.5% of the sample). Being in the intervention condition was more likely to be associated with a course of high and declining depression symptoms than high and persistent depression symptoms (OR = 2.53, 95% CI [1.01, 6.37]). Patients with a course of high and persistent depression symptoms were much more likely to have a diagnosis of major depression at 24 months compared with patients with a course of low and declining depression symptoms (adjusted OR = 16.46, 95% CI [7.75, 34.95]).

Conclusion: Identification of patients at particularly high risk of persistent depression symptoms and poor long-term clinical outcomes is important for the development and delivery of interventions.