期刊
THERAPEUTIC DRUG MONITORING
卷 45, 期 1, 页码 110-116出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/FTD.0000000000000996
关键词
nivolumab; population pharmacokinetics; real-world data; nonsmall cell lung cancer
This study aimed to characterize the real-world population pharmacokinetics (PK) of nivolumab in Japanese patients with non-small cell lung cancer (NSCLC). Population PK analysis revealed that clearance of nivolumab was influenced by factors such as serum albumin level, estimated glomerular filtration rate, and treatment period. Further studies are needed to determine optimal dosing regimens for these patients.
Background: Nivolumab is an antiprogrammed death-1 (PD-1) antibody used for immuno-oncological therapy of various cancers, including nonsmall cell lung cancer (NSCLC). This study aimed to characterize the real-world population pharmacokinetics (PK) of nivolumab in patients with NSCLC. Methods: PK samples were collected by opportunistic sampling of Japanese patients with NSCLC treated with nivolumab monotherapy. Population PK analysis was performed using a two-compartment model in Nonlinear Mixed Effect Model. Patient-specific factors such as body weight, age, sex, serum albumin, estimated glomerular filtration rate, performance status, programmed cell death receptor ligand 1 expression in tumors, and treatment periods were evaluated as potential covariates for clearance. Results: A total of 223 serum samples collected from 34 patients were available for analysis. The median (min-max) age and weight were 69 years (38-83 years) and 62.7 kg (36.8-80.5 kg), respectively. The mean (95% confidence interval) clearance estimate was 0.0064 L/h (0.0058-0.0070 L/h). The inclusion of the ALB level, estimated glomerular filtration rate, and treatment period significantly improved the model fit. Conclusions: A real-world nivolumab population PK model was developed using an opportunistic sampling strategy in Japanese patients with NSCLC. Further studies are warranted to characterize the exposure-response relationship and determine the optimal dosing regimens for these patients.
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