Abstract
OBJECTIVES: Clinical variables were investigated in the 'treatment resistant depression (TRD)- III' sample to replicate earlier findings by the European research consortium 'Group for the Study of Resistant Depression' (GSRD) and enable cross-sample prediction of treatment outcome in TRD. EXPERIMENTAL PROCEDURES: TRD was defined by a Montgomery and Åsberg Depression Rating Scale (MADRS) score ≥22 after at least two antidepressive trials. Response was defined by a decline in MADRS score by ≥50% and below a threshold of 22. Logistic regression was applied to replicate predictors for TRD among 16 clinical variables in 916 patients. Elastic net regression was applied for prediction of treatment outcome. RESULTS: Symptom severity (odds ratio (OR) = 3.31), psychotic symptoms (OR = 2.52), suicidal risk (OR = 1.74), generalized anxiety disorder (OR = 1.68), inpatient status (OR = 1.65), higher number of antidepressants administered previously (OR = 1.23), and lifetime depressive episodes (OR = 1.15) as well as longer duration of the current episode (OR = 1.022) increased the risk of TRD. Prediction of TRD reached an accuracy of 0.86 in the independent validation set, TRD-I. CONCLUSION: Symptom severity, suicidal risk, higher number of lifetime depressive episodes, and comorbid anxiety disorder were replicated as the most prominent risk factors for TRD. Significant predictors in TRD-III enabled robust prediction of treatment outcome in TRD-I.