Predicting Optimal Outcomes in Cognitive Therapy or Interpersonal Psychotherapy for Depressed Individuals Using the Personalized Advantage Index Approach

Abstract

IntroductionAlthough psychotherapies for depression produce equivalent outcomes, individual patients respond differently to different therapies. Predictors of outcome have been identified in the context of randomized trials, but this information has not been used to predict which treatment works best for the depressed individual. In this paper, we aim to replicate a recently developed treatment selection method, using data from an RCT comparing the effects of cognitive therapy (CT) and interpersonal psychotherapy (IPT).Methods134 depressed patients completed the pre- and post-treatment BDI-II assessment. First, we identified baseline predictors and moderators. Second, individual treatment recommendations were generated by combining the identified predictors and moderators in an algorithm that produces the Personalized Advantage Index (PAI), a measure of the predicted advantage in one therapy compared to the other, using standard regression analyses and the leave-one-out cross-validation approach.ResultsWe found five predictors (gender, employment status, anxiety, personality disorder and quality of life) and six moderators (somatic complaints, cognitive problems, paranoid symptoms, interpersonal self-sacrificing, attributional style and number of life events) of treatment outcome. The mean average PAI value was 8.9 BDI points, and 63% of the sample was predicted to have a clinically meaningful advantage in one of the therapies. Those who were randomized to their predicted optimal treatment (either CT or IPT) had an observed mean end-BDI of 11.8, while those who received their predicted non-optimal treatment had an end-BDI of 17.8 (effect size for the difference = 0.51).DiscussionDepressed patients who were randomized to their predicted optimal treatment fared much better than those randomized to their predicted non-optimal treatment. The PAI provides a great opportunity for formal decision-making to improve individual patient outcomes in depression. Although the utility of the PAI approach will need to be evaluated in prospective research, this study promotes the development of a treatment selection approach that can be used in regular mental health care, advancing the goals of personalized medicine.

Innovative Psychological Treatments for Depression

“…35 On the other hand, an even more recent trial from the Netherlands found no differences between IPT and CBT 36 with indications of differential response (moderation) on the part of different patients. 37 At this time it seems fair to say that IPT remains one of the best established treatments for depression although it is still not widely practiced outside of certain areas.…”

Initial Steps to inform selection of continuation cognitive therapy or fluoxetine for higher risk responders to cognitive therapy for recurrent major depressive disorder

“…Optimal versus non-optimal treatment yielded a mean difference in depressive symptoms of 0.58 SD . Similarly, Huibers et al (2015) applied the personalized advantage index to inform selection of acute-phase CT versus interpersonal psychotherapy for MDD, focusing on post-treatment symptom severity.…”

The structure of personality disorders within a depressed sample: Implications for personalizing treatment

“…This study aimed to investigate the preceding issue by employing a factor analysis of a personality disorder assessment interview within a depressed sample, thereby providing results relevant to both depression and personality disorder research. Particularly, understanding the factor structure of personality disorders and that a depressed individual’s score can vary on a particular factor or pattern of factors may play a substantial role in the process of personalizing a depressed individual’s specific treatment (e.g., see [9]).…”