Predictors of continuation for asenapine from real-world data in patients with schizophrenia

Abstract

Abstract Background The continuation rates of pharmacotherapy in schizophrenia exhibit variability, a phenomenon influenced by the specific antipsychotic agent prescribed and patient-related factors such as age and duration of illness. In this context, our study aims to elucidate the predictors of medication continuation for asenapine sublingual tablets, characterized by unique formulation properties. Methods Our investigation leveraged real-world data collected through post-marketing surveillance in Japan, comprising 3236 cases. Utilizing multivariate logistic regression analysis, we identified patient-related factors associated with medication continuation as the primary outcome measure, subsequently employing survival analysis for further evaluation. Additionally, adverse event occurrence was assessed as a secondary outcome measure. Results Multivariate logistic regression analysis unveiled significant predictors of asenapine continuation, notably including patient-related factors such as a chlorpromazine equivalent dose exceeding 600 mg/day and an illness duration of 25 years or more. While the overall continuation rate stood at 40.6%, patients exhibiting factors such as a chlorpromazine equivalent dose surpassing 600 mg/day or an illness duration exceeding 25 years demonstrated continuation rates of 46.3% and 47.9%, respectively. Remarkably, patients presenting both factors showcased the highest continuation rate at 52.5%. Conclusions Our findings shed light on distinct patient-related predictors of asenapine continuation, deviating from those observed with other antipsychotic medications. This underscores the necessity of recognizing that predictive factors for antipsychotic medication continuation vary across different agents. Moving forward, elucidating these predictive factors for various antipsychotic medications holds paramount importance in schizophrenia treatment, facilitating the delivery of tailored therapeutic interventions for individual patients.

Keywords

• Schizophrenia
• Predictor
• Asenapine
• Continuation rate
• Real world data