Cross-trial prediction in psychotherapy: External validation of the Personalized Advantage Index using machine learning in two Dutch randomized trials comparing CBT versus IPT for depression. (2nd January 2021)

• Record Type: Journal Article
• Authors: van Bronswijk, Suzanne C.; Bruijniks, Sanne J. E.; Lorenzo-Luaces, Lorenzo; Derubeis, Robert J.; Lemmens, Lotte H. J. M.; Peeters, Frenk P. M. L.; Huibers, Marcus. J. H.
• Is Part Of: Psychotherapy research. Volume 31:Number 1(2021)
• Page Start: 78
• Page End: 91
• Publication Date: 2021-01-02
• Subjects: depression -- cognitive behavioural therapy -- interpersonal psychotherapy -- precision medicine -- prediction -- external validation; Psychotherapy -- Periodicals; Psychotherapy -- Research -- Periodicals; Psychotherapy -- Periodicals; Psychothérapie -- Périodiques; Psychothérapie -- Recherche -- Périodiques; 616.891405
• DOI: 10.1080/10503307.2020.1823029
• Languages: English
• ISSNs: 1050-3307

Abstract

Abstract: Objective: Optimizing treatment selection may improve treatment outcomes in depression. A promising approach is the Personalized Advantage Index (PAI), which predicts the optimal treatment for a given individual. To determine the generalizability of the PAI, models needs to be externally validated, which has rarely been done. Method: PAI models were developed within each of two independent trials, with substantial between-study differences, that both compared CBT and IPT for depression (STEPd: n = 151 and FreqMech: n = 200). Subsequently, both PAI models were tested in the other dataset. Results: In the STEPd study, post-treatment depression was significantly different between individuals assigned to their PAI-indicated treatment versus those assigned to their non-indicated treatment ( d = .57). In the FreqMech study, post-treatment depression was not significantly different between patients receiving their indicated treatment versus those receiving their non-indicated treatment ( d = .20). Cross-trial predictions indicated that post-treatment depression was not significantly different between those receiving their indicated treatment and those receiving their non-indicated treatment ( d = .16 and d = .27). Sensitivity analyses indicated that cross-trial prediction based on only overlapping variables didn't improve the results. Conclusion: External validation of the PAI has modest results and emphasizes between-study differences and many other challenges.