Impacts of age and BMI on vancomycin model choice in a Bayesian software: Lessons from a very large multi-site retrospective study.

IF 2.9 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Pharmacotherapy Pub Date : 2024-10-01 Epub Date: 2024-10-09 DOI:10.1002/phar.4613
Maria-Stephanie A Hughes, Tiffany Lee, Jonathan D Faldasz, Jasmine H Hughes
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引用次数: 0

Abstract

Background: Model-informed precision dosing (MIPD) optimizes drug doses based on pharmacokinetic (PK) model predictions, necessitating careful selection of models tailored to patient characteristics. This study evaluates the predictive performance of various vancomycin PK models across diverse age and BMI categories, drawing insights from a large multi-site database.

Methods: Adults receiving vancomycin intravenous therapy at United States health systems between January 1, 2022, and December 31, 2023, were included. Patient demographics, vancomycin administration records, and therapeutic drug monitoring levels (TDMs) were collected from the InsightRX database. Age and body mass index (BMI)-based subgroups were formed to assess model performance, with predictions made iteratively. The optimal model for each age-BMI subgroup was chosen based on predefined criteria: models were filtered for mean percentage error (MPE) ≤ 20% and normalized root mean squared error (RMSE) < 8 mg/L, and then the most accurate among them was selected.

Results: A total of 384,876 treatment courses across 155 US health systems were analyzed, contributing 841,604 TDMs. Eleven models were compared, showing varying accuracy across age-BMI categories (41%-73%), with higher accuracy observed once TDMs were available for Bayesian estimates of individual PK parameters. Models performed more poorly in younger adults compared to older adults, and the optimal model differed depending on age-BMI categories and prediction methods. Notably, in the a priori period, the Colin model performed best in adults aged 18-64 years across most BMI categories; the Goti/Tong model performed best in the older, non-obese adults; and the Hughes model performed best in many of the obese categories.

Conclusion: Our study identifies specific vancomycin PK models that demonstrate superior predictions across age-BMI categories in MIPD applications. Our findings underscore the importance of tailored model selection for vancomycin management, especially highlighting the need for improved models in younger adult patients. Further research into the clinical implications of model performance is warranted to enhance patient care outcomes.

贝叶斯软件中年龄和体重指数对万古霉素模型选择的影响:一项大型多地点回顾性研究的启示。
背景:基于模型的精准用药(MIPD)是根据药代动力学(PK)模型的预测来优化药物剂量的,这就需要根据患者的特点仔细选择模型。本研究评估了各种万古霉素 PK 模型在不同年龄和体重指数类别中的预测性能,并从一个大型多站点数据库中汲取了灵感:研究纳入了 2022 年 1 月 1 日至 2023 年 12 月 31 日期间在美国医疗系统接受万古霉素静脉注射治疗的成人。从 InsightRX 数据库中收集了患者的人口统计学特征、万古霉素用药记录和治疗药物监测水平 (TDM)。以年龄和体重指数 (BMI) 为基础建立分组,评估模型性能,并进行反复预测。根据预先设定的标准为每个年龄-体重指数分组选择最佳模型:筛选平均百分比误差 (MPE) ≤ 20% 和归一化均方根误差 (RMSE) 的模型 结果:共分析了 155 个美国医疗系统的 384,876 个疗程,提供了 841,604 个 TDM。对 11 个模型进行了比较,结果显示,不同年龄-体重指数类别的模型准确率各不相同(41%-73%),一旦有了用于贝叶斯法估计单个 PK 参数的 TDM,准确率会更高。与老年人相比,模型在年轻人中的表现更差,最佳模型因年龄-体重指数类别和预测方法而异。值得注意的是,在先验期,Colin 模型在大多数 BMI 类别的 18-64 岁成人中表现最佳;Goti/Tong 模型在非肥胖的老年成人中表现最佳;Hughes 模型在许多肥胖类别中表现最佳:结论:我们的研究确定了万古霉素 PK 模型,这些模型在 MIPD 应用中对不同年龄-体重指数类别的预测效果都很好。我们的研究结果强调了在万古霉素治疗中选择有针对性的模型的重要性,尤其突出了对年轻成年患者改进模型的需求。有必要进一步研究模型性能的临床意义,以提高患者的治疗效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Pharmacotherapy
Pharmacotherapy 医学-药学
CiteScore
7.80
自引率
2.40%
发文量
93
审稿时长
4-8 weeks
期刊介绍: Pharmacotherapy is devoted to publication of original research articles on all aspects of human pharmacology and review articles on drugs and drug therapy. The Editors and Editorial Board invite original research reports on pharmacokinetic, bioavailability, and drug interaction studies, clinical trials, investigations of specific pharmacological properties of drugs, and related topics.
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