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Liu J, Zhang X, Liang G, Zhu J, Yang Y, Zheng Y, Han Y, Yu L, Zhao Y, Yu Z. Is it time to recommend AUC-based vancomycin therapeutic drug monitoring only? A cross-sectional survey in China. Front Pharmacol 2024; 15:1370040. [PMID: 39070794 PMCID: PMC11272526 DOI: 10.3389/fphar.2024.1370040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 07/01/2024] [Indexed: 07/30/2024] Open
Abstract
Background The latest published therapeutic drug monitoring (TDM) guidelines for vancomycin recommend changing trough-based monitoring to area under the concentration-to-time curve (AUC)-based monitoring. This study aimed to evaluate the implementation status and perceptions of vancomycin AUC-based TDM in China and to determine the challenges in performing AUC-based TDM. Methods A nationwide cross-sectional survey was conducted in China using an online questionnaire. The questionnaire comprised a total of 25 questions with open- and closed-ended answers to collect information about the current implementation of vancomycin TDM and the participants' perceptions of these practices. The questionnaire responses were collected via the Questionnaire Star platform and analyzed. Results A total of 161 questionnaires were completed by 131 hospitals and were included. Approximately 59.5% (78/131) of the surveyed hospitals conducted vancomycin TDM; however, only 10.7% (14/131) of these hospitals performed AUC-based vancomycin TDM. Of the eligible participants, 58.4% (94/161) had experience with vancomycin TDM, and only 37 participants (37/161, 23.0%) had the ability to estimate the AUC, primarily through Bayesian simulation (33/161, 20.5%). The participants considered the following challenges to implementing AUC-based monitoring: (1) the high cost of AUC-based monitoring; (2) inadequate knowledge among pharmacists and/or physicians; (3) the complexity of AUC calculations; (4) difficulty obtaining AUC software; and (5) unclear benefit of AUC-based monitoring. Conclusion The majority of surveyed hospitals have not yet implemented AUC-based vancomycin TDM. Multiple challenges should be addressed before wide implementation of AUC-based monitoring, and guidance for trough-based monitoring is still needed.
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Affiliation(s)
- Jieqiong Liu
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- The 903rd Hospital of PLA Joint Logistic Support Force, Hangzhou, China
| | - Xuan Zhang
- Northern Jiangsu People’s Hospital, Yangzhou, China
| | - Gang Liang
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianping Zhu
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yi Yang
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Zheng
- The 903rd Hospital of PLA Joint Logistic Support Force, Hangzhou, China
| | - Yun Han
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- College of Pharmaceutical Science, Zhejiang University, Hangzhou, China
- Research Center for Clinical Pharmacy, Zhejiang University, Hangzhou, China
| | - Lingyan Yu
- Research Center for Clinical Pharmacy, Zhejiang University, Hangzhou, China
- The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuhua Zhao
- Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, China
| | - Zhenwei Yu
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Research Center for Clinical Pharmacy, Zhejiang University, Hangzhou, China
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Haag H, Lau A. Correlation of Calculated Vancomycin Trough Concentrations and Exposure: A Monte Carlo Simulation. Ann Pharmacother 2023; 57:1410-1414. [PMID: 36999486 DOI: 10.1177/10600280231160571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/01/2023] Open
Abstract
BACKGROUND Current recommendations are to dose vancomycin to target 24-hour area under the curve (AUC) of 400-600 mg·h/L to optimize efficacy and safety. Limited data support AUC monitoring, and some centers continue to use trough concentrations. A target of 10-20 mg/L has been proposed to reduce nephrotoxicity risk. OBJECTIVE To use previously published pharmacokinetic equations in a Monte Carlo simulation relating AUC exposure to trough concentrations when targeting an AUC between 400 and 600 mg·h/L. METHODS Previously published pharmacokinetic data were used as input parameters for a Monte Carlo simulation using previously published formulae to correlate AUC to simulated trough concentrations. Pharmacokinetic parameters were assumed to occur in a normal distribution pattern. We excluded irrelevant simulated cases. Maintenance doses of 15 mg/kg were rounded to the nearest 250 mg. Calculated trough concentrations for AUCs of both 400 and 600 mg·h/L were evaluated in each simulation. RESULTS A total of 10 000 Monte Carlo simulations were performed. Targeting an AUC of 400 mg·h/L resulted in a mean trough concentration of 10.3 ± 0.8 mg/L. Targeting an AUC of 600 mg·h/L resulted in a mean trough concentration of 15.4 ± 1.2 mg/L. CONCLUSION AND RELEVANCE We demonstrate that a lower trough concentration range may be supported by an AUC of 400-600 mg·h/L, which may reduce risk and rates of nephrotoxicity without compromising previously established efficacious target trough concentrations.
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Affiliation(s)
- Hans Haag
- Vancouver General Hospital, Vancouver, BC, Canada
- Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, BC, Canada
| | - Anthony Lau
- Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, BC, Canada
- Emergency Medicine, Vancouver General Hospital, Vancouver, BC, Canada
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Barreto EF, Chitre PN, Pine KH, Shepel KK, Rule AD, Alshaer MH, Abdul Aziz MH, Roberts JA, Scheetz MH, Ausman SE, Moreland-Head LN, Rivera CG, Jannetto PJ, Mara KC, Boehmer KR. Why is the Implementation of Beta-Lactam Therapeutic Drug Monitoring for the Critically Ill Falling Short? A Multicenter Mixed-Methods Study. Ther Drug Monit 2023; 45:508-518. [PMID: 37076424 PMCID: PMC10348918 DOI: 10.1097/ftd.0000000000001059] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 10/02/2022] [Indexed: 04/21/2023]
Abstract
BACKGROUND Beta-lactam therapeutic drug monitoring (BL TDM; drug level testing) can facilitate improved outcomes in critically ill patients. However, only 10%-20% of hospitals have implemented BL TDM. This study aimed to characterize provider perceptions and key considerations for successfully implementing BL TDM. METHODS This was a sequential mixed-methods study from 2020 to 2021 of diverse stakeholders at 3 academic medical centers with varying degrees of BL TDM implementation (not implemented, partially implemented, and fully implemented). Stakeholders were surveyed, and a proportion of participants completed semistructured interviews. Themes were identified, and findings were contextualized with implementation science frameworks. RESULTS Most of the 138 survey respondents perceived that BL TDM was relevant to their practice and improved medication effectiveness and safety. Integrated with interview data from 30 individuals, 2 implementation themes were identified: individual internalization and organizational features. Individuals needed to internalize, make sense of, and agree to BL TDM implementation, which was positively influenced by repeated exposure to evidence and expertise. The process of internalization appeared more complex with BL TDM than with other antibiotics (ie, vancomycin). Organizational considerations relevant to BL TDM implementation (eg, infrastructure, personnel) were similar to those identified in other TDM settings. CONCLUSIONS Broad enthusiasm for BL TDM among participants was found. Prior literature suggested that assay availability was the primary barrier to implementation; however, the data revealed many more individual and organizational attributes, which impacted the BL TDM implementation. Internalization should particularly be focused on to improve the adoption of this evidence-based practice.
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Affiliation(s)
| | - Pooja N. Chitre
- School for the Future of Innovation in Society, Arizona State University, Tempe, AZ
| | - Kathleen H. Pine
- College of Health Solutions, Arizona State University, Phoenix, AZ
| | | | - Andrew D. Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
- Division of Epidemiology, Mayo Clinic, Rochester, MN
| | - Mohammad H. Alshaer
- Infectious Disease Pharmacokinetics Lab, Emerging Pathogens Institute, University of Florida, Gainesville, FL
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL
| | - Mohd Hafiz Abdul Aziz
- University of Queensland Centre for Clinical Research (UQCCR), Faculty of Medicine, The University of Queensland, Royal Brisbane and Women’s Hospital, Australia
| | - Jason A. Roberts
- University of Queensland Centre for Clinical Research (UQCCR), Faculty of Medicine, The University of Queensland, Royal Brisbane and Women’s Hospital, Australia
| | - Marc H. Scheetz
- Department of Pharmacy Practice, Chicago College of Pharmacy, Midwestern University, Downers Grove, IL
- Pharmacometrics Center of Excellence, Midwestern University, Downers Grove, IL
| | - Sara E. Ausman
- Department of Pharmacy, Mayo Clinic Health System, Eau Claire, WI
| | | | | | - Paul J. Jannetto
- Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN
| | - Kristin C. Mara
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Kasey R. Boehmer
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
- Division of Health Care Delivery Research, Mayo Clinic, Rochester, MN
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Arensman Hannan KN, Rivera CG, Fewel N. Vancomycin AUC values estimated with trough-only data: Accuracy in an adult academic medical center population. Am J Health Syst Pharm 2023; 80:452-456. [PMID: 36525590 DOI: 10.1093/ajhp/zxac372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Indexed: 12/23/2022] Open
Abstract
PURPOSE Vancomycin area under the concentration-time curve (AUC) can be calculated using steady-state serum peak and trough concentrations; however, compared to traditional trough-only monitoring, this approach requires an additional blood sample. Recently published data demonstrated vancomycin AUC estimations using trough-only data with a volume of distribution (Vd) model incorporating age and actual body weight were reasonably accurate and precise in a veteran population. This study sought to extend these methods to a Mayo Clinic adult population. METHODS A retrospective, observational cohort of adult patients with documented steady-state vancomycin peak and trough concentrations was evaluated. Vancomycin AUCs were estimated using trough-only data, and 4 Vd models were assessed for accuracy and precision. Estimated AUCs were compared to AUCs calculated using 1-compartment intermittent infusion equations and steady-state peak and trough ("peak-trough") data. RESULTS The study population (N = 95) was 46% female, with a median age of 59 years and a median weight of 97 kg. Using the VancoPK equation Vd = 0.29 (age in y) + 0.33 (actual weight in kg) + 11, the mean peak-trough and estimated trough-only AUC were 533 and 534, respectively, with a correlation of 0.936. The root mean square error was 47.7, meaning about 95% of AUCs were within 95 mg · h/L of peak-trough AUCs. CONCLUSIONS Accuracy and precision of Vancomycin AUC estimations using trough-only data and the described Vd model were demonstrated in a Mayo Clinic cohort. Targeting an estimated AUC of 500 mg · h/L using the VancoPK model would likely result in an actual AUC within 400 to 600 mg · h/L.
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Affiliation(s)
| | | | - Nathan Fewel
- Department of Pharmacy, Central Texas Veterans Health Care System, Temple, TX, USA
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Nix DE, Davis LE, Matthias KR. Response to Rybak et al. Am J Health Syst Pharm 2022; 79:1308-1311. [PMID: 35511826 DOI: 10.1093/ajhp/zxac126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.
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Affiliation(s)
- David E Nix
- Department of Pharmacy Practice & Science University of Arizona Tucson, AZ, USA
| | - Lisa E Davis
- Department of Pharmacy Practice & Science University of Arizona Tucson, AZ, USA
| | - Kathryn R Matthias
- Department of Pharmacy Practice & Science University of Arizona Tucson, AZ, USA
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