Patients with schizophrenia have a significantly elevated risk of mortality. Clozapine is effective for treatment-resistant schizophrenia, but its use is limited by side-effects. Understanding its association with mortality risk is crucial.

To investigate the associations of clozapine with all-cause and cause-specific mortality risk in schizophrenia patients.

In this 18-year population-based cohort study, we retrieved electronic health records of schizophrenia patients from all public hospitals in Hong Kong. Clozapine users (ClozUs) comprised schizophrenia patients who initiated clozapine treatment between 2003 and 2012, with the index date set at clozapine initiation. Comparators were non-clozapine antipsychotic users (Non-ClozUs) with the same diagnosis who had never received a clozapine prescription. They were 1:2 propensity score matched with demographic characteristics and physical and psychiatric comorbidities. ClozUs were further defined according to continuation of clozapine use and co-prescription of other antipsychotics (polypharmacy). Accelerated failure time (AFT) models were used to estimate the risk of all-cause and cause-specific mortality (i.e. suicide, cardiovascular disease, infection and cancer).

This study included 9,456 individuals (mean (s.d.) age at the index date: 39.13 (12.92) years; 50.73% females; median (interquartile range) follow-up time: 12.37 (9.78–15.22) years), with 2020 continuous ClozUs, 1132 discontinuous ClozUs, 4326 continuous non-ClozUs and 1978 discontinuous Non-ClozUs. Results from adjusted AFT models showed that continuous ClozUs had a lower risk of suicide mortality (acceleration factor 3.01; 99% CI: 1.41–6.44) compared with continuous Non-ClozUs. Continuous ClozUs with co-prescription of other antipsychotics exhibited lower risks of suicide mortality (acceleration factor 3.67; 1.41–9.60) and all-cause mortality (acceleration factor 1.42; 1.07–1.88) compared with continuous Non-ClozUs. No associations were found between clozapine and other cause-specific mortalities.

These results add to the existing evidence on the effectiveness of clozapine, particularly its anti-suicide effects, and emphasise the need for continuous clozapine use for suitable patients and the possible benefit of clozapine polypharmacy.

Precise stratification of patients into homogeneous disease subgroups could address the heterogeneity of phenotypes and enhance understanding of the pathophysiology underlying specific subtypes. Existing literature on subtyping patients with major depressive disorder (MDD) mainly utilized clinical features only. Genomic and imaging data may improve subtyping, but advanced methods are required due to the high dimensionality of features.

We propose a novel disease subtyping framework for MDD by integrating brain structural features, genotype-predicted expression levels in brain tissues, and clinical features. Using a multi-view biclustering approach, we classify patients into clinically and biologically homogeneous subgroups. Additionally, we propose approaches to identify causally relevant genes for clustering.

We verified the reliability of the subtyping model by internal and external validation. High prediction strengths (PS) (average PS: 0.896, minimum: 0.854), a measure of generalizability of the derived clusters in independent datasets, support the validity of our approach. External validation using patient outcome variables (treatment response and hospitalization risks) confirmed the clinical relevance of the identified subgroups. Furthermore, subtype-defining genes overlapped with known susceptibility genes for MDD and were involved in relevant biological pathways. In addition, drug repositioning analysis based on these genes prioritized promising candidates for subtype-specific treatments.

Our approach successfully stratified MDD patients into subgroups with distinct clinical prognoses. The identification of biologically and clinically meaningful subtypes may enable more personalized treatment strategies. This study also provides a framework for disease subtyping that can be extended to other complex disorders.

Second-generation antipsychotics (SGAs) cause metabolic side effects. However, patients’ metabolic profiles were influenced by time-invariant and time-varying confounders. Real-world evidence on the long-term, dynamic effects of SGAs (e.g. different treatment sequences) are limited. We employed advanced causal inference methods to evaluate the metabolic impact of SGAs in a naturalistic cohort.

We followed 696 Chinese patients with schizophrenia-spectrum disorders receiving SGAs. Longitudinal targeted maximum likelihood estimation (LTMLE) was used to estimate the average treatment effects (ATEs) of continuous SGA treatment versus ‘no treatment’ on metabolic outcomes, including total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), fasting glucose (FG), and body mass index (BMI), over 6–18 months at 3-month intervals. LTMLE accounted for time-invariant and time-varying confounders. Post-SGA discontinuation side effects were also assessed.

The ATEs of continuous SGA treatment on BMI and TG showed an inverted U-shaped pattern, peaking at 12 months and declining afterwards. Similar patterns were observed for TC and LDL, albeit the ATEs peaked at 15 months. For FG and HDL, the ATEs peaked at ~6 months. The adverse impact of SGAs on BMI persisted even after medication discontinuation, yet other metabolic parameters did not show such lingering side effects. Clozapine and olanzapine exhibited greater metabolic side effects compared to other SGAs.

Our real-world study suggests that metabolic side effects may stabilize with prolonged continuous treatment. Clozapine and olanzapine confer higher cardiometabolic risks than other SGAs. The side effects of SGAs on BMI may persist after drug discontinuation. These insights may guide antipsychotic choice and improve management of metabolic side effects.

Contrasting the well-described effects of early intervention (EI) services for youth-onset psychosis, the potential benefits of the intervention for adult-onset psychosis are uncertain. This paper aims to examine the effectiveness of EI on functioning and symptomatic improvement in adult-onset psychosis, and the optimal duration of the intervention.

360 psychosis patients aged 26–55 years were randomized to receive either standard care (SC, n = 120), or case management for two (2-year EI, n = 120) or 4 years (4-year EI, n = 120) in a 4-year rater-masked, parallel-group, superiority, randomized controlled trial of treatment effectiveness (Clinicaltrials.gov: NCT00919620). Primary (i.e. social and occupational functioning) and secondary outcomes (i.e. positive and negative symptoms, and quality of life) were assessed at baseline, 6-month, and yearly for 4 years.

Compared with SC, patients with 4-year EI had better Role Functioning Scale (RFS) immediate [interaction estimate = 0.008, 95% confidence interval (CI) = 0.001–0.014, p = 0.02] and extended social network (interaction estimate = 0.011, 95% CI = 0.004–0.018, p = 0.003) scores. Specifically, these improvements were observed in the first 2 years. Compared with the 2-year EI group, the 4-year EI group had better RFS total (p = 0.01), immediate (p = 0.01), and extended social network (p = 0.05) scores at the fourth year. Meanwhile, the 4-year (p = 0.02) and 2-year EI (p = 0.004) group had less severe symptoms than the SC group at the first year.

Specialized EI treatment for psychosis patients aged 26–55 should be provided for at least the initial 2 years of illness. Further treatment up to 4 years confers little benefits in this age range over the course of the study.