Venlafaxine XR treatment for older patients with major depressive disorder: decision trees for when to change treatment.

Abstract

Background: Predictors of antidepressant response in older patients with major depressive disorder (MDD) need to be confirmed before they can guide treatment.

Objective: To create decision trees for early identification of older patients with MDD who are unlikely to respond to 12 weeks of antidepressant treatment, we analysed data from 454 older participants treated with venlafaxine XR (150-300 mg/day) for up to 12 weeks in the Incomplete Response in Late-Life Depression: Getting to Remission study.

Methods: We selected the earliest decision point when we could detect participants who had not yet responded (defined as >50% symptom improvement) but would do so after 12 weeks of treatment. Using receiver operating characteristic models, we created two decision trees to minimise either false identification of future responders (false positives) or false identification of future non-responders (false negatives). These decision trees integrated baseline characteristics and treatment response at the early decision point as predictors.

Finding: We selected week 4 as the optimal early decision point. Both decision trees shared minimal symptom reduction at week 4, longer episode duration and not having responded to an antidepressant previously as predictors of non-response. Test negative predictive values of the leftmost terminal node of the two trees were 77.4% and 76.6%, respectively.

Conclusion: Our decision trees have the potential to guide treatment in older patients with MDD but they require to be validated in other larger samples.

Clinical implications: Once confirmed, our findings may be used to guide changes in antidepressant treatment in older patients with poor early response.