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TRD) is a promising prediction tool for major depressive disorder (MDD) based on variables associated with treatment outcome. The objective of our study was to examine the association between the DM-TRD and clinical course in a large cohort of MDD outpatients receiving treatment as usual.Furthermore, we examined whether the addition of an item measuring the presence of childhood adversity improved this association. Methods:We included 1115 subjects with MDD (according to the DSM-IV) who were naturalistically treated at seven outpatient departments of a secondary mental healthcare center in the Netherlands. Data on subjects who had a diagnostic work-up between June 2014 and June 2016 were analyzed. Multilevel analyses were performed to examine the association between the DM-TRD score at baseline and clinical course, defined by symptom severity according to scores on the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR) over time. We also investigated whether an extra item measuring childhood adversity improved the model. Results:The model including the DM-TRD and its interaction with time was superior to previous models. The addition of childhood adversity and its interaction with time did not improve the model. Conclusions:In depressed outpatients receiving treatment as usual, the solid longer-term association between higher DM-TRD scores and worse clinical course supports its usefulness in clinical practice. Childhood adversity did not improve the model value indicating thatcounterintuitively-this parameter offers no additional predictive power to the variables included. K E Y W O R D Sambulatory care, clinical course, cohort studies, depression, major depressive disorder, multilevel analysis, outpatients, prediction, psychiatric status rating scales, the Netherlands, treatment outcome

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Efficacious treatments are available for major depressive disorder (MDD), but treatment dropout is common and decreases their effectiveness. However, knowledge about prevalence of treatment dropout and its risk factors in routine care is limited. The objective of this study was to determine the prevalence of and risk factors for dropout in a large outpatient sample. In this retrospective cohort analysis, routinely collected data from 2235 outpatients with MDD who had a diagnostic work-up between 2014 and 2016 were examined. Dropout was defined as treatment termination without achieving remission before the fourth session within six months after its start. Total and item scores on the Dutch Measure for Quantification of Treatment Resistance in Depression (DM-TRD) at baseline, and demographic variables were analyzed for their association with dropout using logistic regression and elastic net analyses. Data of 987 subjects who started routine outpatient depression treatment were included in the analyses of which 143 (14.5%) dropped out. Higher DM-TRD-scores were predictive for lower dropout odds [OR = 0.78, 95% CI = (0.70–0.86), p < 0.001]. The elastic net analysis revealed several clinical variables predictive for dropout. Higher SES, higher depression severity, comorbid personality pathology and a comorbid anxiety disorder were significantly associated with less dropout in the sample. In this observational study, treatment dropout was relatively low. The DM-TRD, an easy-to-use clinical instrument, revealed several variables associated with less dropout. When applied in daily practice and combined with demographical information, this instrument may help to reduce dropout and increase treatment effectiveness.