Neuroendocrine Biomarkers

Schizophrenia spectrum disorders (SSD) pose complex challenges in mental health, with ongoing research exploring factors that influence their course. Emerging evidence suggests a role for hormonal factors in the development and progression of SSD, making neuroendocrine biomarkers promising candidates for constructing diagnostic models. This review spans the past 12 years (2011–2023) and focuses on the use of neuroendocrine biomarkers in developing diagnostic models, evaluated through receiver operating characteristic (ROC) curve analysis. A comprehensive screening of nine articles involving seven countries and over 3000 patients with SSD was conducted. These articles emphasized the efficacy of neuroendocrine biomarkers in predicting the disease course in individuals at clinical high risk of psychosis or monitoring improvement during treatment. In general, the models presented modest performance, with area under the curve (AUC) values ranging from 22% to 80%. However, one study distinguished itself by incorporating a diverse array of compound classes and integrating scores derived from the CAARMS clinical tool, which evaluates early signs and symptoms of psychosis. Impressively, this model achieved an AUC of 90%. This standout result underscores the potential value of incorporating a broader range of biomarkers alongside clinical assessments in enhancing the predictive accuracy of models for SSD.