Subtypes of Late-Life Depression: A Data-Driven Approach on Cognitive Domains and Physical Frailty

Abstract

Background

With increasing age, symptoms of depression may increasingly overlap with age-related physical frailty and cognitive decline. We aim to identify late-life-related subtypes of depression based on measures of depressive symptom dimensions, cognitive performance, and physical frailty.

Methods

A clinical cohort study of 375 depressed older patients with a DSM-IV depressive disorder (acronym NESDO). A latent profile analysis was applied on the three subscales of the Inventory of Depressive Symptomatology, as well as performance in five cognitive domains and two proxies for physical frailty. For each class, we investigated remission, dropout, and mortality at 2-year follow-up as well as change over time of depressive symptom severity, cognitive performance, and physical frailty.

Results

A latent profile analysis model with five classes best described the data, yielding two subgroups suffering from pure depression (“mild” and “severe” depression, 55% of all patients) and three subgroups characterized by a specific profile of cognitive and physical frailty features, labeled as “amnestic depression,” “frail-depressed, physically dominated,” and “frail-depressed, cognitively dominated.” The prospective analyses showed that patients in the subgroup of “mild depression” and “amnestic depression” had the highest remission rates, whereas patients in both frail-depressed subgroups had the highest mortality rates.

Conclusions

Late-life depression can be subtyped by specific combinations of age-related clinical features, which seems to have prospective relevance. Subtyping according to the cognitive profile and physical frailty may be relevant for studies examining underlying disease processes as well as to stratify treatment studies on the effectiveness of antidepressants, psychotherapy, and augmentation with geriatric rehabilitation.