Patients with schizophrenia experience accelerated aging, accompanied by abnormalities in biomarkers such as shorter telomere length. Brain age prediction using neuroimaging data has gained attention in schizophrenia research, with consistently reported increases in brain-predicted age difference (brain-PAD). However, its associations with clinical symptoms and illness duration remain unclear.

We developed brain age prediction models using structural magnetic resonance imaging (MRI) data from 10,938 healthy individuals. The models were validated on an independent test dataset comprising 79 healthy controls, 57 patients with recent-onset schizophrenia, and 71 patients with chronic schizophrenia. Group comparisons and the clinical associations of brain-PAD were analyzed using multiple linear regression. SHapley Additive exPlanations (SHAP) values estimated feature contributions to the model, and between-group differences in SHAP values and group-by-SHAP value interactions were also examined.

Patients with recent-onset schizophrenia and chronic schizophrenia exhibited increased brain-PAD values of 1.2 and 0.9 years, respectively. Between-group differences in SHAP values were identified in the right lateral prefrontal area (false discovery rate [FDR] p = 0.022), with group-by-SHAP value interactions observed in the left prefrontal area (FDR p = 0.049). A negative association between brain-PAD and Full-scale Intelligence Quotient scores in chronic schizophrenia was noted, which did not remain significant after correction for multiple comparisons.

Brain-PAD increases were pronounced in the early phase of schizophrenia. Regional brain abnormalities contributing to brain-PAD likely vary with illness duration. Future longitudinal studies are required to overcome limitations related to sample size, heterogeneity, and the cross-sectional design of this study.

Although disconnectivity among brain regions has been one of the main hypotheses for schizophrenia, the superficial white matter (SWM) has received less attention in schizophrenia research than the deep white matter (DWM) owing to the challenge of consistent reconstruction across subjects.

We obtained the diffusion magnetic resonance imaging (dMRI) data of 223 healthy controls and 143 patients with schizophrenia. After harmonising the raw dMRIs from three different studies, we performed whole-brain two-tensor tractography and fibre clustering on the tractography data. We compared the fractional anisotropy (FA) of white matter tracts between healthy controls and patients with schizophrenia. Spearman’s rho was adopted for the associations with clinical symptoms measured by the Positive and Negative Syndrome Scale (PANSS). The Bonferroni correction was used to adjust multiple testing.

Among the 33 DWM and 8 SWM tracts, patients with schizophrenia had a lower FA in 14 DWM and 4 SWM tracts than healthy controls, with small effect sizes. In the patient group, the FA deviations of the corticospinal and superficial–occipital tracts were negatively correlated with the PANSS negative score; however, this correlation was not evident after adjusting for multiple testing.

We observed the structural impairments of both the DWM and SWM tracts in patients with schizophrenia. The SWM could be a potential target of interest in future research on neural biomarkers for schizophrenia.

Substantial evidence indicates structural abnormalities in the cerebral cortex of patients with schizophrenia (SCZ), although their clinical implications remain unclear. Previous case-control studies have investigated group-level differences in structural abnormalities, although the study design cannot account for interindividual differences. Recent research has focused on the association between the heterogeneity of the cerebral cortex morphometric features and clinical heterogeneity.

We used neuroimaging data from 420 healthy controls and 695 patients with SCZ from seven studies. Four cerebral cortex measures were obtained: surface area, gray matter volume, thickness, and local gyrification index. We calculated the coefficient of variation (CV) and person-based similarity index (PBSI) scores and performed group comparisons. Associations between the PBSI scores and cognitive functions were evaluated using Spearman's rho test and normative modeling.

Patients with SCZ had a greater CV of surface area and cortical thickness than those of healthy controls. All PBSI scores across cortical measures were lower in patients with SCZ than in HCs. In the patient group, the PBSI scores for gray matter volume and all cortical measures taken together positively correlated with the full-scale IQ scores. Patients with deviant PBSI scores for gray matter volume and all cortical measures taken together had lower full-scale IQ scores than those of other patients.

The cerebral cortex in patients with SCZ showed greater regional and global structural variability than that in healthy controls. Patients with deviant similarity of cortical structural profiles exhibited a lower general intelligence than those exhibited by the other patients.

Current evidence on antipsychotic treatment and risk of psychiatric hospitalization in first-episode schizophrenia (FES) is largely based on the findings from randomized clinical trials (RCTs). However, the generalization of the findings to real-world patients is limited due to inherent caveats of the RCT. We aimed to investigate the treatment discontinuation and risk of psychiatric hospitalization using a nationwide population database.

The Health Insurance Review Agency database in South Korea was obtained, and the observation period started from 1 January 2009 to 31 December 2016. We defined the maintenance period as the period from 6-month after the diagnosis of schizophrenia, which is utilized for the main results. For a total of 44 396 patients with FES, a within-individual Cox regression model was used to compare the risk of the treatment discontinuation and psychiatric hospitalization.

In group comparison, a long-acting injectable (LAI) antipsychotic group was associated with the lowest risk of the treatment discontinuation (0.64, 0.55–0.75) and psychiatric hospitalization (0.29, 0.22–0.38) in comparison with a typical antipsychotic group and no use, respectively. Among individual antipsychotics, the lowest risk of the treatment discontinuation was observed in LAI paliperidone (0.46, 0.37–0.66) compared to olanzapine. Clozapine was found to be the most effective antipsychotic in lowering the risk of psychiatric hospitalization as monotherapy compared to no use (0.23, 0.18–0.31).

In real-world patients with FES, LAI paliperidone and clozapine were associated with low treatment discontinuation and better effectiveness in lowering the risk of psychiatric hospitalization.

Depressive symptoms are common in bereaved caregivers; however, there have been few prospective studies using a structured interview. This study investigated the prevalence and preloss predictors of major depressive disorder (MDD) in bereaved caregivers of patients in a palliative care unit.

This prospective cohort study collected caregiver sociodemographic and psychological data before the death of a palliative care unit patient, including MDD, care-burden, coping style, and hopeful attitude. Postloss MDD was assessed 6 and 13 months after death, and a multivariate logistic regression analysis was conducted to identify its predictors.

Of 305 caregivers contacted, 92 participated in this study. The prevalence of preloss MDD was 21.8%; the prevalences of postloss MDD were 34.8% and 24.7% at 6 and 13 months, respectively. Preloss MDD predicted postloss MDD at 6 months (odds ratio [OR] = 5.38, 95% confidence interval [CI95%] = 1.29, 22.43); preloss nonhopeful attitude and unemployment status of caregivers predicted postloss MDD at 13 months (OR = 8.77, CI95% = 1.87, 41.13 and OR = 7.10, CI95% = 1.28, 39.36, respectively).

Approximately 35% of caregivers suffered from MDD at 6 months postloss, but the prevalence of MDD decreased to about 25% at 13 months. Preloss MDD significantly predicted postloss MDD at 6 months, whereas hopeful attitude and unemployment at baseline were significantly associated with postloss MDD at 13 months.

To determine the influence of caregiver personality and other factors on the burden of family caregivers of terminally ill cancer patients.

We investigated a wide range of factors related to the patient–family caregiver dyad in a palliative care setting using a cross-sectional design. Caregiver burden was assessed using the seven-item short version of the Zarit Burden Interview (ZBI–7). Caregiver personality was assessed using the 10-item short version of the Big Five Inventory (BFI–10), which measures the following five personality dimensions: extroversion, agreeableness, conscientiousness, neuroticism, and openness. Patient- and caregiver-related sociodemographic and psychological factors were included in the analysis because of their potential association with caregiver burden. Clinical patient data were obtained from medical charts or by using other measures. Multivariate linear regression analysis was performed to identify the independent factors associated with caregiver burden.

We analyzed 227 patient–family caregiver dyads. The multivariate analysis revealed that caregiver extroversion was protective against caregiver burden, whereas depressive symptoms in caregivers were related to increased burden. Neuroticism was positively correlated with caregiver burden, but this relationship was nonsignificant following adjustment for depressive symptoms. Patient-related factors were not significantly associated with caregiver burden.

Evaluating caregiver personality traits could facilitate identification of individuals at greater risk of high burden. Furthermore, depression screening and treatment programs for caregivers in palliative care settings are required to decrease caregiver burden.