Open Access

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.

Background There is limited knowledge of whether cognitive-behavioral therapy (CBT) or second-generation antipsychotics (SGAs) should be recommended as the first-line treatment in individuals at clinical high risk for psychosis (CHRp). Hypothesis To examine whether individual treatment arms are superior to placebo and whether CBT is non-inferior to SGAs in preventing psychosis over 12 months of treatment. Study Design PREVENT was a blinded, 3-armed, randomized controlled trial comparing CBT to clinical management plus aripiprazole (CM + ARI) or plus placebo (CM + PLC) at 11 CHRp services. The primary outcome was transition to psychosis at 12 months. Analyses were by intention-to-treat. Study Results Two hundred eighty CHRp individuals were randomized: 129 in CBT, 96 in CM + ARI, and 55 in CM + PLC. In week 52, 21 patients in CBT, 19 in CM + ARI, and 7 in CM + PLC had transitioned to psychosis, with no significant differences between treatment arms (P = .342). Psychopathology and psychosocial functioning levels improved in all treatment arms, with no significant differences. Conclusions The analysis of the primary outcome transition to psychosis at 12 months and secondary outcomes symptoms and functioning did not demonstrate significant advantages of the active treatments over placebo. The conclusion is that within this trial, neither low-dose aripiprazole nor CBT offered additional benefits over clinical management and placebo.