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Little is known about factors that contribute to attrition in clinical trials of the pharmacotherapy of psychotic depression. The purpose of this study was to identify factors associated with attrition during acute pharmacotherapy in the Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II) clinical trial. Sociodemographic and clinical variables were assessed at baseline in 269 men and women, aged 18-85 years, who were treated with up to 12 weeks of open-label sertraline plus olanzapine. Univariate analyses examined the association of baseline variables with overall non-completion, as well as reasons for non-completion. Logistic regression was used to model the relationship of the significant univariate predictors with non-completion and its reasons. Seventy-four (27.5 %) participants did not complete the acute treatment phase of STOP-PD II. Male gender, younger age, inpatient status, higher Clinical Global Impression (CGI) severity of illness, and higher severity of psychomotor disturbance were associated with non-completion in univariate analyses. In regression models, higher CGI severity of illness score was the only significant independent predictor of non-completion, explained by withdrawal of consent. Our findings have implications for the retention of persons with psychotic depression in clinical trials., Competing Interests: Declaration of competing interest R. A. Ihaddadene has no competing interests; G.S. Alexopoulos has received NIMH grants and has served in the speakers bureau of Takeda, Lundbeck, Otsuka, Alergan, Astra/Zeneca, Sunovion; P. Marino received research support from the NIMH at the time this work was done; B.S. Meyers received research support from the NIMH at the time this work was done; B.H. Mulsant holds and receives support from the Labatt Family Chair in Biology of Depression in Late-Life Adults at the University of Toronto. He currently receives or has received research support during the past three years from Brain Canada, the Canadian Institutes of Health Research, the CAMH Foundation, the Patient-Centered Outcomes Research Institute (PCORI), the US National Institute of Health (NIH), Capital Solution Design LLC (software used in a study founded by CAMH Foundation), and HAPPYneuron (software used in a study founded by Brain Canada). Within the past three years, he has also been an unpaid consultant to Myriad Neuroscience; N.H Neufeld has served on an advisory board for Boehringer Ingelheim; he has received grant support from the Brain and Behavior Research Foundation, Canadian Institutes of Health Research, Physicians' Services Incorporated Foundation, Labatt Family Network for Research on the Biology of Depression and the University of Toronto (including an Academic Scholars Award); A.J. Rothschild has received, in the past three years, grant or research support from Compass Pathways, Janssen, Otsuka, and the Irving S. and Betty Brudnick Endowed Chair in Psychiatry. In the past three years, he has been a consultant to Daiichi Sankyo, Inc., Sage Therapeutics, Xenon Pharmaceuticals, Neumora Therapeutics, Zydus Pharmaceuticals (USA), Inc., Sandoz, Inc., and Lupin Pharmaceuticals, Inc. He has received royalties in the past three years for the Rothschild Scale for Antidepressant Tachyphylaxis (RSAT)®, Clinical Manual for the Diagnosis and Treatment of Psychotic Depression, American Psychiatric Press, 2009, The Evidence-Based Guide to Antipsychotic Medications, American Psychiatric Press, 2010, The Evidence-Based Guide to Antidepressant Medications, American Psychiatric Press, 2012, and from UpToDate®; A.N. Voineskos has received funding from the NIMH, Canadian Institutes of Health Research, Canada Foundation for Innovation, CAMH Foundation, and the University of Toronto; E.M. Whyte has received grant support from the NIMH and HRSA; A.J. Flint has received grant support from the U.S. National Institutes of Health, Patient-Centered Outcomes Research Institute, Canadian Institutes of Health Research, Brain Canada, Ontario Brain Institute, Alzheimer's Association, AGE-WELL, the Canadian Foundation for Healthcare Improvement, and the University of Toronto; K.S. Bingham has received grant support from the University of Toronto., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Some data suggest that antipsychotics may adversely affect brain structure. We examined the relationship among olanzapine exposure, relapse, and changes in brain structure in patients with major depressive disorder with psychotic features. We analyzed data from the Study of the Pharmacotherapy of Psychotic Depression II trial (STOP-PD II), a randomized, placebo-controlled trial in patients with psychotic depression who attained remission on sertraline and olanzapine and were randomized to continue sertraline plus olanzapine or placebo for 36 weeks. Olanzapine steady state concentration (SSC) were calculated based on sparsely-sampled levels. Rates of relapse and changes in brain structure were assessed as outcomes. There were significant associations between dosage and relapse rates (N = 118; HR = 0.94, 95% CI [0.897, 0.977], p = 0.002) or changes in left cortical thickness (N = 44; B = -2.0 × 10 -3 , 95% CI [-3.1 × 10 -3 , -9.6 × 10 -4 ], p < 0.001) and between SSC and changes in left cortical thickness (N = 44; B = -8.7 × 10 -4 , 95% CI [-1.4 × 10 -3 , -3.6 × 10 -4 ], p = 0.001). Similar results were found for the right cortex. These associations were no longer significant when the analysis was restricted to participants treated with olanzapine. Our findings suggest that, within its therapeutic range, the effect of olanzapine on relapse or cortical thickness does not depend on its dosage or SSC. Further research is needed on the effect of olanzapine and other antipsychotics on mood symptoms and brain structure., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory., Method: One hundred and twenty-six persons aged 18-85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics., Results: Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model., Conclusions: Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Background: The neurobiology of psychotic depression is not well understood and can be confounded by antipsychotics. Magnetic resonance spectroscopy (MRS) is an ideal tool to measure brain metabolites non-invasively. We cross-sectionally assessed brain metabolites in patients with remitted psychotic depression and controls. We also longitudinally assessed the effects of olanzapine versus placebo on brain metabolites., Methods: Following remission, patients with psychotic depression were randomized to continue sertraline + olanzapine (n = 15) or switched to sertraline + placebo (n = 18), at which point they completed an MRS scan. Patients completed a second scan either 36 weeks later, relapse, or discontinuation. Where water-scaled metabolite levels were obtained and a Point-RESolved Spectroscopy sequence was utilized, choline, myo-inositol, glutamate + glutamine (Glx), N-acetylaspartate, and creatine were measured in the left dorsolateral prefrontal cortex (L-DLPFC) and dorsal anterior cingulate cortex (dACC). An ANCOVA was used to compare metabolites between patients (n = 40) and controls (n = 46). A linear mixed-model was used to compare olanzapine versus placebo groups., Results: Cross-sectionally, patients (compared to controls) had higher myo-inositol (standardized mean difference [SMD] = 0.84; 95%CI = 0.25-1.44; p = 0.005) in the dACC but not different Glx, choline, N-acetylaspartate, and creatine. Longitudinally, patients randomized to placebo (compared to olanzapine) showed a significantly greater change with a reduction of creatine (SMD = 1.51; 95%CI = 0.71-2.31; p = 0.0002) in the dACC but not glutamate + glutamine, choline, myo-inositol, and N-acetylaspartate., Conclusions: Patients with remitted psychotic depression have higher myo-inositol than controls. Olanzapine may maintain creatine levels. Future studies are needed to further disentangle the mechanisms of action of olanzapine., (© 2023. The Author(s).)

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis., (© 2024 World Psychiatric Association.)