PracticeUpdate Conference Series European Congress of Psychiatry 2019

Five Patient Characteristics Predict Recurrence of Major Depressive Disorder Specific symptomatology, patient age and duration of illness were among themost relevant predictors.

T he chances of a patient having recurring episodes of major depressive disorder can be predicted by five sociodemographic and clinical findings, according to an abstract featured at EPA 2019. In their abstract, Gianluca Serafini, MD, PhD, from the University of Genoa in Italy, and colleagues remarked that, although specific predictors of depression relapse/recurrence have been iden- tified, evidence for which predictors are the most relevant is currently inconsistent across various studies. The researchers conducted their own nat- uralistic cohort study to identify the most relevant sociodemographic and clinical predictors of major depressive disorder recurrence. The 508 subjects in their study all had euthymic- type major depressive disorder and were outpatients. Their mean age was 54.1 ± 16.2 years. The subjects who were experiencing their first episode of major depressive disorder comprised 53.9% of the cohort, and 46.1% of the cohort had experienced recurrent depressive episodes. The investigators performed a detailed data col- lection, and they traced illness histories through clinical files and lifetime computerized medical records. The analysis showed that, compared with patients who had a single episode of major depres- sive disorder, patients with recurrent episodes

differed significantly with regard to a plethora of characteristics: age, age at first treatment, gender, working status, family history of mental disorders, typical depressive characteristics at first episode, psychotic symptoms at first episode, duration of untreated illness, melancholic characteristics, seasonality, and comorbid cardiovascular/endo- crinologic conditions. The researchers narrowed the field of possibly relevant characteristics through multivariate analyses that adjusted for age, gender, educational level and working status. Results showed that recurrence was associated with five characteristics: typical depressive features at first episode (beta coefficient = 4.635, P ≤ .001), melancholic features (beta coefficient = 4.011, P ≤ .05), age at first treatment (beta coefficient = –9.723, P ≤ .005), duration of untreated illness (beta coefficient = –5.630, P ≤.05), and current age (beta coefficient = 14.702, P ≤ .001). Dr. Serafini and colleagues state in their abstract that, “the predictors of recurrence of major depressive episodes identified in the current study may aid in the stratification of patients who could benefit from more intensive maintenance treatments for major depressive disorder.” They also caution that “clinicians should rapidly identify cases that are not likely to recur in order to avoid unnecessary treatments [that] are commonly considered as the standard of care.”

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PRACTICEUPDATE CONFERENCE SERIES • EPA 2019