{"title":"利用贝叶斯估计法确定哪些患者需要采集两点血样的峰值和谷值,而不是采集一点血样的谷值来评估万古霉素的 AUC。","authors":"Ayako Suzuki, Masaru Samura, Tomoyuki Ishigo, Satoshi Fujii, Yuta Ibe, Hiroaki Yoshida, Hiroaki Tanaka, Fumiya Ebihara, Takumi Maruyama, Yukihiro Hamada, Hisato Fujihara, Fumihiro Yamaguchi, Fumio Nagumo, Toshiaki Komatsu, Atsushi Tomizawa, Akitoshi Takuma, Hiroaki Chiba, Yoshifumi Nishi, Yuki Enoki, Kazuaki Taguchi, Kazuaki Matsumoto","doi":"10.1007/s11095-024-03781-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>It is recommended to adjust the dose of vancomycin (VCM) with a target area under the concentration-time curve (AUC) of 400-600 μg·h/mL. Factors that affect the deviation between AUCs are estimated from the trough value alone and the trough and peak values using practical AUC-guided therapeutic drug monitoring (PAT) for vancomycin. In this study, factors that affect AUC were evaluated.</p><p><strong>Methods: </strong>AUCs were estimated from a single trough value and trough and peak values, and the patients were classified into those who showed a 10% or greater deviation (deviation group) and those in whom the deviation was less than 10% (no-deviation group). Risk factors related to ≥ 10% deviation of AUC were identified by univariate and multivariate analysis.</p><p><strong>Results: </strong>As a result of univariate and multivariate analysis of 30 patients in the deviation group and 344 patients in the no-deviation group, a creatinine clearance (CLcr) of ≥ 110 mL/min (odds ratio (OR) = 3.697, 95% confidence interval (CI) = 1.616-8.457, p = 0.002), heart failure with a brain natriuretic peptide (BNP) of ≥ 300 pg/mL (OR = 4.854, 95%CI = 1.199-19.656, p = 0.027), and the concomitant use of angiotensin converting enzyme inhibitor or angiotensin II receptor blocker (ACE-I/ARB) (OR = 2.544, 95%CI = 1.074-6.024, p = 0.034) were identified as risk factors of ≥ 10% deviation of AUC.</p><p><strong>Conclusions: </strong>Estimation of AUC by two-point blood sampling for the trough and peak values rather than one-point blood sampling for the trough value is suggested to improve the prediction accuracy in patients with enhanced renal function, severe heart failure, and patients using ACE-I/ARB.</p>","PeriodicalId":20027,"journal":{"name":"Pharmaceutical Research","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Patients Who Require Two-Point Blood Sampling for the Peak and Trough Values Rather Than One-Point Blood Sampling for the Trough Value for the Evaluation of AUC of Vancomycin Using Bayesian Estimation.\",\"authors\":\"Ayako Suzuki, Masaru Samura, Tomoyuki Ishigo, Satoshi Fujii, Yuta Ibe, Hiroaki Yoshida, Hiroaki Tanaka, Fumiya Ebihara, Takumi Maruyama, Yukihiro Hamada, Hisato Fujihara, Fumihiro Yamaguchi, Fumio Nagumo, Toshiaki Komatsu, Atsushi Tomizawa, Akitoshi Takuma, Hiroaki Chiba, Yoshifumi Nishi, Yuki Enoki, Kazuaki Taguchi, Kazuaki Matsumoto\",\"doi\":\"10.1007/s11095-024-03781-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>It is recommended to adjust the dose of vancomycin (VCM) with a target area under the concentration-time curve (AUC) of 400-600 μg·h/mL. Factors that affect the deviation between AUCs are estimated from the trough value alone and the trough and peak values using practical AUC-guided therapeutic drug monitoring (PAT) for vancomycin. In this study, factors that affect AUC were evaluated.</p><p><strong>Methods: </strong>AUCs were estimated from a single trough value and trough and peak values, and the patients were classified into those who showed a 10% or greater deviation (deviation group) and those in whom the deviation was less than 10% (no-deviation group). Risk factors related to ≥ 10% deviation of AUC were identified by univariate and multivariate analysis.</p><p><strong>Results: </strong>As a result of univariate and multivariate analysis of 30 patients in the deviation group and 344 patients in the no-deviation group, a creatinine clearance (CLcr) of ≥ 110 mL/min (odds ratio (OR) = 3.697, 95% confidence interval (CI) = 1.616-8.457, p = 0.002), heart failure with a brain natriuretic peptide (BNP) of ≥ 300 pg/mL (OR = 4.854, 95%CI = 1.199-19.656, p = 0.027), and the concomitant use of angiotensin converting enzyme inhibitor or angiotensin II receptor blocker (ACE-I/ARB) (OR = 2.544, 95%CI = 1.074-6.024, p = 0.034) were identified as risk factors of ≥ 10% deviation of AUC.</p><p><strong>Conclusions: </strong>Estimation of AUC by two-point blood sampling for the trough and peak values rather than one-point blood sampling for the trough value is suggested to improve the prediction accuracy in patients with enhanced renal function, severe heart failure, and patients using ACE-I/ARB.</p>\",\"PeriodicalId\":20027,\"journal\":{\"name\":\"Pharmaceutical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmaceutical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11095-024-03781-4\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmaceutical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11095-024-03781-4","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Identification of Patients Who Require Two-Point Blood Sampling for the Peak and Trough Values Rather Than One-Point Blood Sampling for the Trough Value for the Evaluation of AUC of Vancomycin Using Bayesian Estimation.
Objectives: It is recommended to adjust the dose of vancomycin (VCM) with a target area under the concentration-time curve (AUC) of 400-600 μg·h/mL. Factors that affect the deviation between AUCs are estimated from the trough value alone and the trough and peak values using practical AUC-guided therapeutic drug monitoring (PAT) for vancomycin. In this study, factors that affect AUC were evaluated.
Methods: AUCs were estimated from a single trough value and trough and peak values, and the patients were classified into those who showed a 10% or greater deviation (deviation group) and those in whom the deviation was less than 10% (no-deviation group). Risk factors related to ≥ 10% deviation of AUC were identified by univariate and multivariate analysis.
Results: As a result of univariate and multivariate analysis of 30 patients in the deviation group and 344 patients in the no-deviation group, a creatinine clearance (CLcr) of ≥ 110 mL/min (odds ratio (OR) = 3.697, 95% confidence interval (CI) = 1.616-8.457, p = 0.002), heart failure with a brain natriuretic peptide (BNP) of ≥ 300 pg/mL (OR = 4.854, 95%CI = 1.199-19.656, p = 0.027), and the concomitant use of angiotensin converting enzyme inhibitor or angiotensin II receptor blocker (ACE-I/ARB) (OR = 2.544, 95%CI = 1.074-6.024, p = 0.034) were identified as risk factors of ≥ 10% deviation of AUC.
Conclusions: Estimation of AUC by two-point blood sampling for the trough and peak values rather than one-point blood sampling for the trough value is suggested to improve the prediction accuracy in patients with enhanced renal function, severe heart failure, and patients using ACE-I/ARB.
期刊介绍:
Pharmaceutical Research, an official journal of the American Association of Pharmaceutical Scientists, is committed to publishing novel research that is mechanism-based, hypothesis-driven and addresses significant issues in drug discovery, development and regulation. Current areas of interest include, but are not limited to:
-(pre)formulation engineering and processing-
computational biopharmaceutics-
drug delivery and targeting-
molecular biopharmaceutics and drug disposition (including cellular and molecular pharmacology)-
pharmacokinetics, pharmacodynamics and pharmacogenetics.
Research may involve nonclinical and clinical studies, and utilize both in vitro and in vivo approaches. Studies on small drug molecules, pharmaceutical solid materials (including biomaterials, polymers and nanoparticles) biotechnology products (including genes, peptides, proteins and vaccines), and genetically engineered cells are welcome.