Agomelatine as augmentation therapy with second‐generation antipsychotics for negative symptoms of schizophrenia: An open‐label randomised clinical trial and electroencephalogram‐derived model for treatment response prediction

ABSTRACT Background Negative symptoms are a core diagnostic domain of schizophrenia that affect functional outcomes and remain difficult to treat. Agomelatine, a novel antidepressant with melatonin receptor agonism and serotonin 2C receptor antagonism, may have therapeutic potential. Aims This study aimed to evaluate the efficacy of agomelatine combined with second‐generation antipsychotics (SGAs) in reducing negative symptoms and to explore electroencephalogram (EEG)‐based biomarkers for predicting treatment response. Methods An open‐label randomised parallel‐group clinical trial was conducted at the Shanghai Mental Health Centre (December 2022 to September 2023), enrolling outpatient adults with schizophrenia and prominent negative symptoms, defined as a positive and negative syndrome scale factor score for negative symptoms (PANSS‐FSNS) higher than a PANSS factor score for positive symptoms (PANSS‐FSPS); PANSS‐FSNS ≥ 24; 7 < PANSS‐FSPS ≤ 28; at least two of three core PANSS negative symptoms ≥ 4 and a Calgary depression scale for schizophrenia score ≤ 18. Patients were randomised (1:1) using a random number table to a group receiving agomelatine (25 mg/day) plus SGAs or a group receiving SGAs alone for 12 weeks. Outcome assessors were blinded after assignment to interventions. The primary outcome was the change in score in the negative symptom factor score (NSFS) at 12 weeks. Longitudinal changes were assessed using linear mixed‐effects models. Results Seventy‐four patients were enrolled, with an agomelatine augmentation group ( n = 37) and a control group ( n = 37). The agomelatine augmentation group demonstrated significantly lower scores on the NSFS compared to the control group starting from Week 8 (estimated marginal mean [EMM] difference = −1.79, 95% confidence interval [CI] −3.00 to −0.59, p = 0.004) and sustaining through Week 12 (EMM difference = −2.65, 95% CI −3.86 to −1.44, p < 0.001). Exploratory support vector machine (SVM) models demonstrated high classification performance in distinguishing treatment responders from non‐responders (area under the curve = 0.91), highlighting notable EEG changes in the left frontotemporal region. Conclusions Agomelatine augmentation significantly improves negative symptoms, encompassing affective deficits, expressive impairments and social‐withdrawal‐related symptoms. EEG‐based SVM models suggest potential utility for informing future personalised treatment strategies. Trial registration number NCT05646264.