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PREDICTING OUTCOME OF DEPRESSION USING THE DEPRESSIVE SYMPTOM PROFILE: THE LEIDEN ROUTINE OUTCOME MONITORING STUDY
Author(s) -
van Noorden Martijn S.,
van Fenema Esther M.,
van der Wee Nic J. A.,
Zitman Frans G.,
Giltay Erik J.
Publication year - 2012
Publication title -
depression and anxiety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.634
H-Index - 129
eISSN - 1520-6394
pISSN - 1091-4269
DOI - 10.1002/da.21958
Subject(s) - depression (economics) , outcome (game theory) , psychiatry , medicine , depressive symptoms , psychology , clinical psychology , cognition , economics , macroeconomics , mathematics , mathematical economics
Background To investigate the predictive value of items for individual depressive symptoms measured with the self‐rated B eck D epression I nventory‐Revised (BDI‐II) self‐report scale on outcome in a large naturalistic cohort of depressive outpatients. Methods We used a cohort of 1,489 adult patients aged 18–65 years with major depressive disorder or dysthymic disorder established with the MINI ‐ P lus diagnostic interview. All patients had a routine outcome monitoring baseline measurement in 2004–2009, with a maximum of 2 years follow‐up. We used multivariable Cox regression models to predict remission ( MADRS < 10; where MADRS stands for Montgomery–Åsberg Depression Rating Scale) and response (≥50% improvement), and adjusted for clinical and demographic characteristics (i.e. marital status, level of education, working status, comorbid anxiety, avoidant and borderline personality traits, and suicidality) that were identified as predictors in earlier studies. Results Of the 21 BDI‐II items, the items “pessimism” and “loss of energy” independently predicted for both remission and response. For pessimism, the hazard ratio ( HR ) for remission was 0.81 (95% confidence interval [CI]: 0.73–0.89, P < .001) and for loss of energy, the HR was 0.81 (95% CI: 0.72–0.92, P = .001). Conclusions These findings of robust prediction of poor outcome by baseline items of “pessimism” and “loss of energy” in a naturalistic treatment setting may help clinicians to identify depressive patients in need for additional or alternative therapeutic approaches.