Smoking and weight among patients using clozapine

Pharmacometric modeling of drug adverse effects: an application of mixture models in schizophrenia spectrum disorder patients treated with clozapine

Clozapine has superior efficacy to other antipsychotics yet is underutilized due to its adverse effects, such as neutropenia, weight gain, and tachycardia. The current investigation aimed to introduce a pharmacometric approach to simultaneously model drug adverse effects, with examples from schizophrenia spectrum patients receiving clozapine. The adverse drug effects were represented as a function of time by incorporating a mixture model to describe individual susceptibility to the adverse effects. Applications of the proposed method were presented by analyzing retrospective data from patients' medical records in Psychiatric Clinic, Penang General Hospital. Tachycardia, weight gain, and absolute neutrophils count (ANC) decrease were best described by an offset, a piecewise linear, and a transient surge function, respectively. 42.9% of the patients had all the adverse effects, including weight gain (0.01 kg/m² increase every week over a baseline of 24.7 kg/m² until stabilizing at 279 weeks), ANC decrease (20% decrease from 4540 cells/µL week 12-20.8), and tachycardia (14% constant increase over a baseline of 87.9 bpm for a clozapine maintenance dose of 450 mg daily). 32.5% of the patients had only tachycardia, while the remaining 24.6% had none of the adverse effects. A new pharmacometric approach was proposed to describe adverse drug effects with examples of clozapine-induced weight gain, ANC drop, and tachycardia. The current approach described the longitudinal time changes of continuous data while assessing patient susceptibility. Furthermore, the model revealed the possible co-existence of ANC drop and weight gain; thus, neutrophil monitoring might predict future changes in body weight.

Development of multivariable models to predict change in Body Mass Index within a clinical trial population of psychotic individuals

Many antipsychotics promote weight gain, which can lead to non-compliance and relapse of psychosis. By developing models that accurately identify individuals at greater risk of weight gain, clinicians can make informed treatment decisions and target intervention measures. We examined clinical, genetic and expression data for 284 individuals with psychosis derived from a previously published randomised controlled trial (IMPACT). These data were used to develop regression and classification models predicting change in Body Mass Index (BMI) over one year. Clinical predictors included demographics, anthropometrics, cardiac and blood measures, diet and exercise, physical and mental health, medication and BMI outcome measures. We included genetic polygenic risk scores (PRS) for schizophrenia, bipolar disorder, BMI, waist-hip-ratio, insulin resistance and height, as well as gene co-expression modules generated by Weighted Gene Co-expression Network Analysis (WGCNA). The best performing predictive models for BMI and BMI gain after one year used clinical data only, which suggests expression and genetic data do not improve prediction in this cohort.

Resistin as an inflammatory marker in patients with schizophrenia treated with clozapine

BACKGROUND

Schizophrenia is associated with excess cardiovascular comorbidity and mortality related to lifestyle factors, such as lack of physical activity, poor diet, and smoking. The prevalence of metabolic syndrome is increased among patients with schizophrenia, with the highest rates among patients on clozapine treatment. Smoking, obesity, physical inactivity, airway inflammation and obstruction, and adipose tissue and inflammatory marker activation are related in systemic inflammation. Low-grade inflammation is also associated with schizophrenia. Adipokine resistin is a biomarker involving several acute and chronic inflammatory states. However, the inflammatory role of resistin is so far inconclusive and studies in schizophrenia are scanty.

AIMS

The aim of the present study was to explore the role of serum resistin as an inflammatory marker in patients with schizophrenia on clozapine treatment.

METHODS

Associations between serum levels of resistin and some other selected cytokines/adipokines (adiponectin, leptin, adipsin, IL-6, IL-1Ra, TNF-α, hs-CRP) and metabolic markers in 190 patients with schizophrenia on clozapine treatment were studied using a cross-sectional study design.

RESULTS

Among male patients especially, smokers had higher levels of resistin than non-smokers, and among smokers resistin levels were associated with IL-1Ra and hs-CRP levels. In the whole patient group levels of resistin associated with levels of IL-1Ra, and among male patients with low HDL-cholesterol.

CONCLUSIONS

Resistin is a biomarker of systemic inflammation associated with smoking among patients with schizophrenia on clozapine treatment. Resistin might have a role as a marker of cardiovascular comorbidity.

Predicting Weight Gain in Patients Treated With Clozapine: The Role of Sex, Body Mass Index, and Smoking

OBJECTIVES

Weight gain on clozapine is highly variable and poorly predictable. Its mechanisms are not well understood. This study explores the factors that predict weight gain between 3 and 12 months of clozapine therapy in community-dwelling patients.

METHODS

We conducted a retrospective audit of patients attending an outpatient clozapine clinic. Weight change from 3 to 12 months of therapy was recorded, expressed as a percentage of the 3-month weight. Univariate analyses compared percent weight change according to sex, smoking status, country of birth, and baseline body mass index. Correlations between weight gain, age, and clozapine dose were explored. A general linear model identified independent predictors of weight gain.

RESULTS

The mean weight change from 3 to 12 months in 117 patients was +3.1% (range, -17% to +30%). Females gained more weight than males (+5.5% vs +1.3%, P = 0.01), smokers gained more than nonsmokers (+5.1% vs +1.2%, P = 0.02), and obese patients gained less than normal or overweight individuals (0.15% vs 4.6% and 5.2%, respectively, P = 0.01). Age and clozapine dose had no relation to weight change. On multivariate analysis, baseline BMI and smoking status remained independent predictors of percent weight change in females. These 2 predictors explained 25% of weight change in females in the first 3 to 12 months of therapy. These associations were not observed in males.

CONCLUSIONS

We hypothesize that smoking affects weight change by promoting clozapine metabolism to norclozapine via cytochrome P450 enzymes. Verifying this hypothesis and exploring the mechanisms underpinning the sex dichotomy are areas for further research.