PREDICTING OUTCOME OF DEPRESSION USING THE DEPRESSIVE SYMPTOM PROFILE: THE LEIDEN ROUTINE OUTCOME MONITORING STUDY


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Abstract

BackgroundTo investigate the predictive value of items for individual depressive symptoms measured with the self-rated Beck Depression Inventory-Revised (BDI-II) self-report scale on outcome in a large naturalistic cohort of depressive outpatients.MethodsWe used a cohort of 1,489 adult patients aged 18–65 years with major depressive disorder or dysthymic disorder established with the MINI-Plus 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.ResultsOf 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).ConclusionsThese 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.

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