Hippocampal Subfield Volumes Predict Disengagement from Maintenance Treatment in First Episode Schizophrenia. (12th November 2022) - Qi, Wei; Marx, Julia; Zingman, Michael; Li, Yi; Petkova, Eva; Blessing, Esther; Ardekani, Babak; Sakalli Kani, Ayse; Cather, Corinne; Freudenreich, Oliver; Holt, Daphne; Zhao, Jingping; et al.
Abstract: Objectives: Disengagement from treatment is common in first episode schizophrenia (FES) and is associated with poor outcomes. Our aim was to determine whether hippocampal subfield volumes predict disengagement during maintenance treatment of FES. Methods: FES patients were recruited from sites in Boston, New York, Shanghai, and Changsha. After stabilization on antipsychotic medication, participants were randomized to add-on citalopram or placebo and followed for 12 months. Demographic, clinical and cognitive factors at baseline were compared between completers and disengagers in addition to volumes of hippocampal subfields. Results: Baseline data were available for 95 randomized participants. Disengagers ( n = 38, 40%) differed from completers ( n = 57, 60%) by race (more likely Black; less likely Asian) and in more alcohol use, parkinsonism, negative symptoms and more impairment in visual learning and working memory. Bilateral dentate gyrus (DG), CA1, CA2/3 and whole hippocampal volumes were significantly smaller in disengagers compared to completers. When all the eight volumes were entered into the model simultaneously, only left DG volume significantly predicted disengagement status and remained significant after adjusting for age, sex, race, intracranial volume, antipsychotic dose, duration of untreated psychosis, citalopram status, alcohol status, and smoking status ( P < .01). Left DG volume predicted disengagement with 57% sensitivity and 83% specificity. Conclusions: Smaller left DG was significantly associated with disengagement status over 12 months of maintenance treatment in patients with FES participating in a randomized clinical trial. If replicated, these findings may provide a biomarker to identify patients at risk for disengagement and a potential target for interventions.