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Predictors of recurrence in a sample of 508 outpatients with major depressive disorder
Gianluca Serafini1, Francesca Santi1, Xenia Gonda2
1Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Objective:
Specific predictors of relapse/recurrence in major depressive disorder (MDD) have been identified but evidence across studies are inconsistent. This study aimed to identify the most relevant socio-demographic/clinical predictors of MDD recurrence in a sample of 508 outpatients.
Methods:
This naturalistic cohort study included 508 currently euthymic MDD patients (mean age = 54.1 ± 16.2) of which 53.9% had a single and 46.1% recurrent depressive episodes. A detailed data collection was performed and illness histories were retraced through clinical files and lifetime computerized medical records.
Results:
Compared to patients with single episode, MDD patients with recurrent episodes significantly differ regarding current age, gender, working status, positive history of psychiatric disorders in family, first-lifetime illness episode characteristics, first-episode and current psychotic symptoms, current melancholic features and seasonality, age at first treatment, duration of untreated illness, and comorbid cardiovascular/endocrinological conditions. However, after multivariate analyses controlling for current age, gender, educational level, working status differences, psychiatric conditions in family, and age of illness episode, recurrence was associated with older age (p ≤ .001), younger age at first treatment (p ≤ .005), being treated with previous psychoactive treatments (p .001), and longer duration of untreated illness (p .001).
Conclusions:
The variables associated with MDD recurrence identified in the current study may aid in the stratification of patients who could benefit from more intensive maintenance treatments for MDD. However, clinicians should rapidly identify cases that are not likely to recur in order to avoid unnecessary treatments which are commonly considered as the standard of care.
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