Superiority of ceftazidime off‐label high‐dose regimen in PK/PD target attainment during treatment of extensively drug‐resistant Pseudomonas aeruginosa infections in cancer patients

British Journal of Clinical Pharmacology(2022)

引用 0|浏览4
暂无评分
摘要
The objective of this study was to evaluate off-label high-dose ceftazidime population pharmacokinetics in cancer patients with suspected or proven extensively drug-resistant (XDR) Pseudomonas aeruginosa infections and then to compare the achievement of the pharmacokinetic/pharmacodynamic (PK/PD) target after standard and off-label high-dose regimens using population model-based simulations. A further aim was to clinically observe the occurrence of adverse effects during the off-label high-dose ceftazidime treatment.In patients treated with off-label high-dose ceftazidime (3 g every 6 h), blood samples were collected and ceftazidime serum levels measured using LC-MS/MS. A pharmacokinetic population model was developed using a nonlinear mixed-effects modelling approach and Monte Carlo simulations were then used to compare standard and high-dose regimens for PK/PD target attainment.A total of 14 cancer patients with serious infection suspected of XDR P. aeruginosa aetiology were eligible for PK analysis. XDR P. aeruginosa was confirmed in 10 patients as the causative pathogen. Population ceftazidime volume of distribution was 13.23 L, while clearance started at the baseline of 1.48 L/h and increased by 0.0076 L/h with each 1 mL/min/1.73 m2 of eGFR. High-dose regimen showed significantly higher probability of target attainment (i.e., 86% vs. 56% at MIC of 32 mg/L). This was translated into a very low mortality rate of 20%. Only one case of reversible neurological impairment was observed.We proved the superiority of the ceftazidime off-label high-dose regimen in PK/PD target attainment with very low occurrence of adverse effects. The off-label high-dose regimen should be used to optimize treatment of XDR P. aeruginosa infections.
更多
查看译文
关键词
<i>pseudomonas
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要