Stability and transition of depression subtypes in late life

Eveline Veltman,Almar Kok,Femke Lamers,Max Stek,Roos Van Der Mast,Didi Rhebergen

doi:10.1016/j.jad.2020.01.049

Abstract

BackgroundThe heterogeneity of late-life depression hampers diagnosis and treatment. Data-driven methods have identified several subtypes of depression in older persons, but the longitudinal stability of these subtypes remains unknown. MethodsIn total 111 older persons with a major depressive disorder both at baseline and 2-year follow-up from the Netherlands Study of Depression in Older persons (NESDO) were included. Latent class analysis was performed to identify subtypes of depression at baseline and at 2-year follow-up, and latent transition analysis was used to examine the stability of these subtypes over time. Transition rates between subtypes and characteristics of groups were examined. ResultsTwo subtypes were identified in both baseline (T0) and follow-up data (T1), including a ‘melancholic’ subtype (prevalence 80.2% (T0) and 62.2% (T1)), and an ‘atypical’ subtype (prevalence 19.8% (T0) and 37.8% (T1)). The melancholic subtype was characterized by decreased appetite and weight and had a stability of 0.86. The atypical subtype was characterized by increased appetite and weight and had a stability of 0.93, although the discriminating power of different symptoms had decreased at T1. Mean age and education differed significantly between stable and transitioning subgroups, other characteristics did not differ between subgroups. LimitationsLimited sample size might have hampered the analyses. ConclusionsSubtypes of late-life depression are relatively stable, but symptoms of depression (like weight loss) seem to blur with symptoms of (patho)physiological aging. This underlines the clinical relevance of depression subtyping, but also the importance of further research into subtypes and the influence of aging.

Highlights

Late-life depression is a common disorder, with a prevalence ranging from 1–16% (Djernes, 2006)
To determine which model best fitted the data, we examined the sample size adjusted BIC, entropy, the bootstrapped Lo-Mendell-Rubin likelihood ratio test (LMR), the bootstrapped likelihood ratio test (BLRT) and the proportion of respondents in each class
In post-hoc analyses, we further explored the characteristics of the subjects that were included in our earlier latent class analysis (LCA) (Veltman et al, 2017), but not in our current Latent transition analysis (LTA)

Summary

Introduction

Late-life depression is a common disorder, with a prevalence ranging from 1–16% (Djernes, 2006). Previous, longitudinal studies demonstrated low longitudinal stability of depression categories described in the Diagnostic and Statistical Manual of Mental Disorders (DSM) edition 5 (American Psychiatry Association, 2013) such as major depressive disorder, dysthymia, and subthreshold depression (Angst et al, 1997, 2000) Acknowledging this heterogeneity, the DSM 5 contains several specifiers such as depression with atypical or melancholic features, but these have not proved sufficient to predict prognosis and treatment response (Parker et al, 2010; Lojko and Rybakowski, 2017). Conclusions: Subtypes of late-life depression are relatively stable, but symptoms of depression (like weight loss) seem to blur with symptoms of (patho)physiological aging. This underlines the clinical relevance of depression subtyping, and the importance of further research into subtypes and the influence of aging

Methods

Results

Discussion

Conclusion