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Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy.
Methods
Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions.
Results
One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit.
Conclusions
If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.
Although equally efficacious in the acute phase, it is not known how cognitive therapy (CT) and interpersonal psychotherapy (IPT) for major depressive disorder (MDD) compare in the long run. This study examined the long-term outcomes of CT v. IPT for MDD.
Methods
One hundred thirty-four adult (18–65) depressed outpatients who were treated with CT (n = 69) or IPT (n = 65) in a large open-label randomized controlled trial (parallel group design; computer-generated block randomization) were monitored across a 17-month follow-up phase. Mixed regression was used to determine the course of self-reported depressive symptom severity (Beck Depression Inventory II; BDI-II) after treatment termination, and to test whether CT and IPT differed throughout the follow-up phase. Analyses were conducted for the total sample (n = 134) and for the subsample of treatment responders (n = 85). Furthermore, for treatment responders, rates of relapse and sustained response were examined for self-reported (BDI-II) and clinician-rated (Longitudinal Interval Follow-up Evaluation; LIFE) depression using Cox regression.
Results
On average, the symptom reduction achieved during the 7-month treatment phase was maintained across follow-up (7–24 months) for CT and IPT, both in the total sample and in the responder sample. Two-thirds (67%) of the treatment responders did not relapse across the follow-up period on the BDI-II. Relapse rates assessed with the LIFE were somewhat lower. No differential effects between conditions were found.
Conclusions
Patients who responded to IPT were no more likely to relapse following treatment termination than patients who responded to CT. Given that CT appears to have a prophylactic effect following successful treatment, our findings suggest that IPT might have a prophylactic effect as well.
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