Factors predicting serum clozapine levels in Middle Eastern patients: an observational study

Nomograms based on clinical factors to predict abnormal metabolism of psychotropic drugs

Interindividual variability in drug metabolism serves a critical role in the occurrence of adverse drug reactions. Factors such as age, sex, body mass index (BMI) and liver and renal function can influence the metabolism of antipsychotic medications. To the best of our knowledge, however, clinical prediction models based on these factors for estimating drug-metabolizing capacity have not yet been developed. Between January 2022 and September 2023, 185 adult patients (aged ≥18 years) who did not have cancer and were not critically ill, with or without comorbidities such diabetes, hypertension and liver and kidney diseases, who underwent pharmacogenetic testing at The First Hospital of Jilin University (Changchun, China) were enrolled. Clinical data were collected, and the participants were divided into training and validation cohorts. Logistic regression was performed to identify significant risk factors, which were incorporated into multivariable models to construct nomograms predicting psychotropic drug metabolism. A total of eight clinical indicators (BMI, hypertension, alkaline phosphatase, aspartate aminotransferase, cholinesterase, albumin to globulin ratio, urea, and uric acid) were significantly associated with psychotropic drug metabolism (all P<0.05). Based on these indicators, along with age and sex, prediction models for psychotropic drug metabolism were developed. The areas under the receiver operating characteristic curves for haloperidol, olanzapine, paroxetine, mirtazapine/venlafaxine and oxazepam/lorazepam in the validation dataset were 0.767, 0.767, 0.705, 0.740 and 0.789, respectively, indicating the models had moderate diagnostic efficiency. Nomograms were constructed to demonstrate the contribution of each indicator to drug metabolism capacity. To the best of our knowledge, the present study is the first to develop predictive models for psychotropic drug metabolism. These models offer clinicians practical tools to identify patients with impaired drug-metabolizing capacity, thereby enabling more precise and personalized medication management.

Racial and Ethnic Considerations for the Clinical Practice of Psychopharmacology and Research Methodology: A Narrative Review of the Growing Body of Literature

BACKGROUND

Race and ethnicity are important but often underexamined factors in psychopharmacology research and clinical practice. This review summarizes key findings on ethnic and racial considerations for researchers, medical practitioners, and clinical psychopharmacologists. We hope it serves an important function in highlighting a critically important, yet still emerging issue to inform research and therapeutic use of psychotropics to improve their effectiveness.

METHODS

We queried major databases (PubMed, PsycInfo, Embase) using a search strategy that included MeSH (Medical Subject Headings) terms and conducted a snowball search to identify studies addressing ethnic or racial aspects of psychopharmacological practice. Findings were synthesized and presented in clinically applicable areas.

RESULTS

The clinically relevant ethnic and racial considerations identified in this review can be broadly categorized into the following areas: (1) variations in therapeutic and adverse dose-responses (eg, non-Whites attaining therapeutic and adverse effects at lower doses with certain medications); (2) interracial differences in prescription patterns of psychotropics, with lower prescription rates among under-represented minority groups and greater use of first-generation antipsychotics in African American populations; and (3) variations in attitudes toward psychopharmacotherapy. While differences in medication response can be partially explained by genetic variations in metabolism or receptor sensitivity, systemic racism and social determinants of health continue to have an influence.

CONCLUSIONS

The evidence base for ethnic and racial considerations in psychopharmacology research and clinical practice continues to evolve with growing consideration for diversity and inclusivity in training, research, and clinical practice. This is critical to promoting equitable and effective care to a diverse population. Key questions are highlighted to draw attention to these critical needs.

Optimizing co-prescription of clozapine and antiseizure medications: a systematic review and expert recommendations for clinical practice

INTRODUCTION

Antiseizure medication (ASM) add-on to clozapine may be efficient to target clozapine-resistant mood or psychotic symptoms or clozapine-related adverse drug reactions (ADR) such as seizures. We aimed to synthesize the information relevant for clinical practice on the risks and benefits of clozapine-ASM co-prescription.

AREAS COVERED

Articles were identified with MEDLINE, Web of Sciences and PsycINFO search from inception through October 2023. The review was restricted to ASM with mood-stabilizing properties or with potential efficacy for resistant psychotic symptoms (valproate (VPA), lamotrigine, topiramate, carbamazepine, oxcarbazepine).

EXPERT OPINION

VPA add-on to clozapine is associated with a high risk of serious ADR (myocarditis, neutropenia, pneumonia) mostly explained by complex time-dependent drug-drug interactions. The initial inhibitory effects on clozapine metabolism require slow titration to avoid immuno-allergic reactions. After the titration period, VPA has mainly inductive effects on clozapine metabolism that are more marked in smokers requiring therapeutic drug monitoring. Lamotrigine and topiramate add-on may be recommended as the first-line treatment for clozapine-related seizures, but there is limited evidence regarding the efficacy of this strategy for clozapine-resistant psychotic symptoms. Carbamazepine should not be co-prescribed with clozapine because of its potential for agranulocytosis and for inducing clozapine metabolism.

Predicting clozapine dose required to achieve a therapeutic plasma concentration - A comparison of a population algorithm and three algorithms based on gene variant models

BACKGROUND

Clozapine is the most effective antipsychotic but requires careful titration to therapeutic blood levels. Methods to predict therapeutic doses are based on population data.

AIMS

We aimed to construct a model based on genetic variants which accurately predicted plasma levels for clozapine.

METHOD

We measured clozapine plasma levels in patients on a stable dose of clozapine who were known to be fully compliant. Measured plasma levels were adjusted for sampling time and dose. Hepatic enzyme variants were analysed and models were constructed to predict the required dose. These predictions were compared with a standard population-based algorithm.

RESULTS

We measured plasma clozapine concentrations in 18 adherent patients on stable doses of clozapine and recorded the exact timing of sampling. For the algorithm-predicted dose, the mean difference was -49.9 mg/day ((SD 155.9), r = 0.36) from the actual dose required to give a plasma concentration of 0.35 ng/ml. The gene variant activity score predicted a dose for which the mean difference was -43.5 mg/day ((SD 140.1), r = 0.55). For the gene variant activity score with omeprazole correction predicted dose, the mean difference was -31.0 mg/day ((SD 140.8), r = 0.54), and with the gene variant CYP1A2 inducibility predicted dose the mean difference was 44.9 mg/day ((SD 160.8), r = 0.32).

CONCLUSION

Our gene variant activity score with omeprazole correction gave the best estimate of the clozapine dose required to achieve a minimum therapeutic plasma concentration. The use of this model will allow safer titration of clozapine and may reduce the need for plasma-level monitoring during titration.

Vitamin D impact in affecting clozapine plasma exposure: A potential contribution of seasonality

Schizophrenia affects approximately 24 million people worldwide and clozapine is the most effective antipsychotic drug. Nevertheless, its use in therapy is limited due to adverse effects.Therapeutic drug monitoring is a clinical tool useful to reduce the clozapine toxicity. In the literature, papers showed how psychiatric disorders could be associated with low vitamin D levels, but a few studies focusing on its role in affecting clozapine exposure are available. A TDM repository was analyzed: clozapine and vitamin D levels measured with liquid chromatography were considered. 1261 samples obtained from 228 individuals were evaluated: 624 patients (49.5%) showed clozapine plasma levels in therapeutic range (350-600 ng/mL). Clozapine toxic plasma levels (>1000 ng/mL) were more present in winter (p = 0.025), compared to other seasons. Concerning vitamin D, a sub-analysis of 859 samples was performed: 326 (37.81%) were deficient ( ng/mL), 490 (57.12%) had insufficient concentrations (10-30 ng/mL), while 43 (5.02%) had sufficient (>30 ng/mL) levels. A correlation between vitamin D and clozapine plasma levels (p = 0.007, Pearson coefficient=0.093) was observed. The role of seasonal variation in clozapine plasma exposure in psychiatric patients treated with clozapine was suggested. Further studies in larger cohorts are needed in order to clarify these aspects.

Analysis of clozapine-induced seizures using the Japanese Adverse Drug Event Report database

Among antipsychotics, clozapine is associated with a high risk of seizures. This study aimed to generate novel hypotheses regarding trends in the onset of clozapine-induced seizures using the JADER (Japanese Adverse Drug Event Report) database. Seizures were defined according to the Standardized MedDRA Queries (SMQ) for convulsions (SMQ20000079). Trends in the onset of clozapine-induced seizures were assessed using multivariate logistic regression analysis with covariates of sex, age, clozapine dose, antipsychotic polypharmacy, concomitant medications, and history of convulsive disorder. In addition, we assessed the time-to-onset of clozapine-induced seizures using the median time, interquartile range, and Weibull shape parameter. The JADER database registered 2,745 cases of adverse events with clozapine, and 1,784 cases were included in the analysis after excluding cases for which clinical information was not available. Medium (200-400 mg) and high (> 400 mg) doses of clozapine had a significantly higher reporting rate of seizures than low doses (< 200 mg) (adjusted reporting odds ratio [aROR] = 3.05, 95% confidence interval [CI]: 1.86-4.99 and aROR = 9.81, 95% CI: 6.06-15.89, respectively). Younger age, antipsychotic polypharmacy, and concomitant use of lithium were also significantly associated with reports of seizures. The time-to-onset analysis of 222 cases of clozapine-induced seizures showed that the median time was 134 (interquartile range, 72-295) days. The 95% CI of the WSP β-value for clozapine-induced seizures included 1 and was classified as a random failure type. In conclusion, the results suggest that clozapine-induced seizures are dose-dependent adverse events that should be monitored with consideration of the effects of age and concomitant medications. Further epidemiological research is needed to strengthen and validate our hypotheses.