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新生儿哌拉西林-他唑巴坦群体药代动力学模型的评估:外部验证

Assessment of Piperacillin-Tazobactam Population Pharmacokinetic Models in Neonates: An External Validation.

作者信息

Chaudhari Bhim Bahadur, Dilli Batcha Jaya Shree, Raju Arun Prasath, Matcha Saikumar, Lewis Leslie E, Moorkoth Sudheer, Mallayasamy Surulivelrajan

机构信息

Department of Quality Assurance, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.

Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.

出版信息

Eur J Drug Metab Pharmacokinet. 2025 Jan;50(1):81-89. doi: 10.1007/s13318-024-00929-w. Epub 2024 Dec 16.

Abstract

BACKGROUND AND OBJECTIVE

Neonatal pharmacotherapy has gained attention from clinicians and regulatory agencies for optimizing the dosage of the drug which improves therapeutic outcomes in this special population. Piperacillin-tazobactam antibiotic is commonly used as a therapeutic option for treatment of severe infection in neonatal intensive care units. There are few population pharmacokinetic (PopPK) studies of piperacillin and tazobactam published for this specific population and which were not validated in other study settings. The aim of this study was to externally evaluate the published population pharmacokinetic models for piperacillin-tazobactam.

METHODS

A systematic review was conducted through Scopus, PubMed, and Embase databases to identify PopPK models. Clinical data collected in neonates treated with piperacillin-tazobactam were used for evaluation of these models. Various prediction-based metrics were used for assessing the bias and precision of PopPK models using individual predictions.

RESULTS

Three PopPK models were identified for external evaluation. A total of 53 plasma samples were collected from 46 neonates admitted in the neonatal intensive care unit. The PopPK models reported by Cohen-Wolkowiez et al. for piperacillin and Li et al. for tazobactam were able to predict well for our clinical data.

CONCLUSION

The PopPK models by Cohen-Wolkowiez et al. and Li et al. predicted our data well for piperacillin and tazobactam with the lower relative median absolute predictive error (rMAPE) of 8.61% and 16.48% and relative root mean square error (rRMSE) of 0.01 and 0.03, respectively. External evaluation of the published PopPK models of piperacillin and tazobactam resulted in enhancing their credibility to be implemented in clinical practice.

摘要

背景与目的

新生儿药物治疗已引起临床医生和监管机构的关注,以优化药物剂量,从而改善这一特殊人群的治疗效果。哌拉西林-他唑巴坦抗生素常用于新生儿重症监护病房治疗严重感染。针对这一特定人群,关于哌拉西林和他唑巴坦的群体药代动力学(PopPK)研究较少,且未在其他研究环境中得到验证。本研究的目的是对外评估已发表的哌拉西林-他唑巴坦群体药代动力学模型。

方法

通过Scopus、PubMed和Embase数据库进行系统综述,以识别PopPK模型。收集接受哌拉西林-他唑巴坦治疗的新生儿的临床数据,用于评估这些模型。使用各种基于预测的指标,通过个体预测来评估PopPK模型的偏差和精度。

结果

确定了三个PopPK模型进行外部评估。从新生儿重症监护病房收治的46名新生儿中总共收集了53份血浆样本。Cohen-Wolkowiez等人报告的哌拉西林PopPK模型和Li等人报告的他唑巴坦PopPK模型能够很好地预测我们的临床数据。

结论

Cohen-Wolkowiez等人和Li等人的PopPK模型对哌拉西林和他唑巴坦的数据预测良好,相对中位绝对预测误差(rMAPE)分别为8.61%和16.48%,相对均方根误差(rRMSE)分别为0.01和0.03。对已发表的哌拉西林和他唑巴坦PopPK模型进行外部评估,提高了它们在临床实践中应用的可信度。

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