BACKGROUND: The course-heterogeneity of Major Depressive Disorder (MDD) hampers development of better prognostic models. Although latent class growth analyses (LCGA) have been used to explain course-heterogeneity, such analyses have failed to also account for symptom-heterogeneity of depressive symptoms. Therefore, the aim was to identify more specific data-driven subgroups based on patterns of course-trajectories on different depressive symptom domains.
METHODS: In primary care MDD patients (n=205), the presence of the MDD criterion symptoms was determined for each week during a year. Weekly 'mood/cognition' (MC) and 'somatic' (SOM) scores were computed and parallel processes-LCGA (PP-LCGA) was used to identify subgroups based on the course on these domains. The classes׳ associations with baseline predictors and 2-/3-year outcomes were investigated.
RESULTS: PP-LCGA identified four classes: quick recovery, persisting SOM, persisting MC, and persisting SOM+MC (chronic). Persisting SOM was specifically predicted by higher baseline somatic symptomatology and somatization, and was associated with more somatic depressive symptomatology at long-term follow-up. Persisting MC was specifically predicted by higher depressive severity, thinking insufficiencies, neuroticism, loneliness and lower self-esteem, and was associated with lower mental health related quality of life and more mood/cognitive depressive symptomatology at follow-up.
LIMITATIONS: The sample was small and contained only primary care MDD patients. The weekly depression assessments were collected retrospectively at 3-month intervals.
CONCLUSIONS: The results indicate that there are two specific prototypes of depression, characterized by either persisting MC or persisting SOM, which have different sets of associated prognostic factors and long-term outcomes, and could have different etiological mechanisms.
- Latent class growth analysis
- COGNITIVE-BEHAVIORAL THERAPY
- RECURRENT DEPRESSION
- SOMATIC SYMPTOMS
- ANXIETY NESDA