Vancomycin Therapy in Secondary Care;Investigatingfactors That Impact Therapeutic Target

Vancomycin therapy in secondary care;investigatingfactors that impact therapeutic target attainment

Timothy M Rawson1(), Esmita Charani1(), Luke SP Moore1,2(), Pau Herrero3(),Ji Soo Baik4(), Akash Philip3(), Mark Gilchrist2(), Eimear T Brannigan2(), Pantelis Georgiou3(), William Hope5(), Alison H Holmes1,2 ()

Affiliations:

1. National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, Hammersmith Campus, Du Cane Road, London. W12 0NN. United Kingdom.
2. Imperial College Healthcare NHS Trust, Du Cane Road, London.W12 0HS. United Kingdom.
3. Department of Electrical and Electronic Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, United Kingdom
4. School of Medicine, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
5. Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, L69 3GE, United Kingdom

*Corresponding author:

Dr Timothy M Rawson, Hammersmith Hospital, Du Cane Road, London.W12 0HS. United Kingdom. Email:

Telephone: 02033132732.

Running Title:Vancomycin dosing and obesity

Search terms:Vancomycin, obesity, antimicrobial resistance, pharmacokinetic-pharmacodynamic, population modelling

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Abstract

Introduction: Achieving therapeutic vancomycin levels in individual patients ensures clinical effectiveness andminimisesthe risks of toxicity and antimicrobial resistance. We investigated clinical dosing of intermittent,intravenous vancomycin across a non-critically ill population in three University hospitals in London to explore factors influencing attainment of therapeutic targets.

Methods: Data from 30 in-patients receiving vancomycinfor suspected or confirmed staphylococcal infections was used to construct a two-compartment pharmacokinetic model. Weight and glomerular filtration rate (GFR) were incorporated as covariates. Monte-Carlo simulation (n=1000) was performed to estimate probability of target attainment (PTA, AUC:MIC>400) for a range of MICs. Ranges of total body weight (TBW) were simulated (n=2000) to investigate the effect of weight on AUC:MIC ratio.

Results: Median age was 60 (21-87) years.The majority of individuals were male (18/30, 60%). MedianBody Mass Index (BMI) was 25 (19-39) kg/m2 with six (20%) individuals classified as obese (BMI≥30kg/m2). Median (IQR) GFR was 75.85 (38.8-107.8)ml/min/1.73m2. Individual mean (SD) steady state AUC values were significantly different between obese and non-obese individuals (320(74) vs. 509(157); p<0.01).Simulation at steady state demonstrated that ≥1000mg 12-hourly was required to attain PTA of ≥80% for MIC’s of 1mg/L and≥2000mg 12-hourly attained PTA of ≥80% in MICs above 2mg/L. Simulated patients with TBW between 45-75kg had significantly higher predicted AUC:MIC ratios compared to those with TBW of 75-150kg (p<0.01).

Conclusion: Obese populations receivingintravenous vancomycin therapy may benefit from precision prescribing interventions to ensure achievement of defined pharmacodynamic indices. Vancomycin’s role in high MIC infections must be further explored.

Abstract: 250

Manuscript: 1109

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Dear editor,

We read with interest the article by Valencia-Rey and colleagues who investigated the role of vancomycin for empirical therapy in coagulase negative staphylococcal blood stream infections.1For vancomycin therapy outside of critical care there arelimited data describing vancomycin pharmacokinetics. We undertook a retrospective investigation ofdosing of vancomycin in the non-critically ill patients managed across three University hospitals in London. Using patient TDM data, the aim wasto build a population pharmacokinetic model to estimate population parameters and identify key factors associated with target attainment.

Routinely collected data from two prospective hospital wide audits of vancomycin therapy in the non-critical care settingwas included. Data on patient demographics, infection parameters, biochemical results, antimicrobial treatment, and TDM data was extracted for analysis. Patients on renal replacement therapy were excluded.Age, gender, ethnicity, total body weight (TBW), ideal body weight (IBW), lean body weight (LBW), body mass index (BMI), glomerular filtration rate (GFR;Modification of Diet in Renal Disease [MDRD] formula), and creatinine clearance (CrCL; estimated using the Cockcroft-Gault equation using TBW and IBW) were all collected or calculatedfor investigation as model covariates. An NPAG population pharmacokinetic algorithm embedded in the program;Pmetricswithin R (LAPKB, CA, USA)2, was used to estimate the population pharmacokineticsof vancomycin.

Comparison between one- and two-compartment models were performed and covariates were tested within the model. Statistical significance was assessed by comparison of twice the log-likelihood values against a chi-squared distribution with the appropriate number of degrees of freedom, depending on the number of parameter values within each model. Population parameters were estimated and assessed. Individual patient 24-hour steady state AUCwas calculated. Given a paucity of minimum inhibitory concentration (MIC) data, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints were used to estimate the mean MIC for staphylococcalinfections3. For estimates of individual AUC:MIC ratio, an MIC of 1mg/L was selected as the breakpoint. A target AUC:MIC ratio ≥400 was defined as appropriate4–6. Monte-Carlo simulation was performed (1000 patients) and probability of target attainment (PTA) estimated for eight dosing regimens commonly used in clinical practice at different MIC values (0.25 to 8). Following this, simulations were performed for different weight ranges (45-75kg & 75-150kg) to investigate the effect of weight on AUC:MIC ratios across dosing regimens (n=2000). Statistical analysis was performed in SPSS 22.0 (IBM, NY, USA). Ethical approval was not required for this study as only routinely collected data were included.

79 patients were identified on vancomycin therapy. 30 individuals receiving vancomycin therapy for known or suspected staphylococcal infectionswere selected for inclusion. Of the 49 patients excluded, 42 had covariate data missing and 7 were on renal replacement therapy. Median age (range) of the included subjects was 60 (21-87) years, with the majority being male (18/30, 60%). Table 1summarises the key population parameters and indications for therapy. Median (IQR) GFR was 75.85 (38.8-107.8)ml/min/1.73m2. Patients received a median (range) of 1500mg (500-3000mg) vancomycin 24-hourly and had a median(range) of 3.5(1-6) TDM samples taken during the observation period.Local target TDM plasma concentration (10-15mg/L or 15-20mg/L in severe or deep seated infections) was reached in 26/30 (87%) of cases. Three of the four individuals not reaching these targets were obese (BMI >30kg/m2), with the fourth classified as overweight (BMI = 26kg/m2).

A two-compartment model produced optimal observed-versus-predicted fit for the individual data extracted giving an r2 of 0.9. TBW and GFR were included as covariates to the model using an allometric scaling and linear association, respectively. These significantly improved the model (-2log likelihood = 602.4 to 590.2 and AIC = 612.9 to 600.8). Population parameter estimates and individual steady state 24-hour area under the curve (AUC) estimations are described in Table 1. Overall, mean (SD) AUC:MIC ratio was 471 (163). 19/30 (63%) patients had AUC:MIC ratio ≥400. Of these, 3/19 (16%) had AUC values >700, which has been associated with greater risk of toxicity7. Of the 11/30 (37%) not meeting the target AUC:MIC ratio, 5/11 (45%) were obese. On comparison of obese versus non-obese subjects, the AUC:MIC ratio were statistically significant (mean (SD) = 320 (74) versus 509 (157);p<0.01).The GFR of those failing to attain a AUC:MIC ratio ≥400 were similar to those attaining the target (mean (SD) = 72 (36) vs. 79 (47);p=0.70).

Monte-Carlo simulation and PTA estimation for a range of dosing schedules of vancomycin from 500mg 24-hourlyto 2000mg 12-hourly were performed (Figure 1). The PTA target was an AUC ≥400 simulated for a range of MIC values (from 0.25 to 8.0). Simulation of PTA demonstrated that for dosing regimens commonly used within our hospital guidelines, doses of 1000mg twice daily are required for greater than 80% probability of attaining a AUC:MIC ratio of >400 when the MIC is 1mg/L. Moreover, with an MIC of 2mg/L only 2000mg twice daily would achieve greater than 80% PTA. Analysis of the effect of TBW on the AUC:MIC of patients simulated across a range of dosing regimens at TBW 45-75kg (n=1000) and75-150kg (n=1000) was performed. Median (IQR) AUC:MIC was 464 (254-879) and 391 (217-748), respectively for both groups (p<0.01).

In conclusion obesity was associated with significant likelihood of failing to attain AUC:MIC ratio of >400 in this real-world cohort of non-critical care patients from secondary care. This finding was replicated on the Monte-Carlo simulation of high versus low TBW individuals receiving a range of dosing regimens. With approximately 20% of UK in-patients now classified obese, this observation warrants further investigation to define the direct clinical implications of significantly lower target attainment on patient outcomes. Furthermore, for difficult to treat infections with an organism with an MIC of 2mg/L or greater, vancomycin maynot be an effective agent, given its low likelihood of target attainment at the majority of dosing strategies modelled and the potential risks of toxicity at higher doses.The significant differences in AUC:MIC target attainmentreported within this study highlights the need to conduct in-depth analysis of similar populations to define thedirect clinical implications of significantly lower target attainment on patient outcomes. Estimation of AUC and incorporation of pharmacodynamic indices, such as AUC:MICmay be an intermediate method of optimising therapy for these individuals. However, in the long term, alternative approaches to dosing high risk individuals is required with computer assisted approaches, such as iterative learning control providing a potential solution to dose optimisation in such cases8. Research must focus on investigating novel pharmacodynamicvancomycin targetsandcombination therapy to better describe the effects of potentially synergistic regimes. We now plan to undertake larger prospective work to investigate direct patient outcomes with observed differences in PK-PD parameters within obese populations in order to review standard intravenous vancomycin dosing recommendations in infections.

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Declarations

Ethics approval

The study protocol was reviewed by the West London Regional Ethics Committee (REC) and considered to meet criteria for monitoring under service evaluation governance structures (REC 15/LO/1269 / ICHNT Service Evaluation SE113).

Funding

This report is independent research fundedby the National Institute for Health Research Invention for Innovation (i4i) programme, Enhanced, Personalized and Integrated Care for Infection Management at Point of Care (EPIC IMPOC),II-LA-0214-20008.

Acknowledgements

The authors would like to acknowledge the National Institute of Health Research Imperial Biomedical Research Centre and the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infection and Antimicrobial Resistance at Imperial College London in partnership with Public Health England and the NIHR Imperial Patient Safety Translational Research Centre. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the UK Department of Health.

Transparency declaration

TMR participated in design of methodology, data collection, analysis and drafting of the initial manuscript. EC, LSPM, JB, AP, MG, & EB participated in data collection and analysis. WH & PH participated in study design & data analysis. PG & AH participated in study design and drafting of the manuscript. All authors contributed significantly to review of the initial manuscript draft and approving this final version for submission.

Competing interests

AHH & LSPM have consulted for bioMérieux in 2013 and 2014 respectively. M.J.G. reports attending advisory boards for The Medicines Company and Cubist, and receiving educational travel and speaker grants from Eumedica Pharmaceuticals and Astellas Pharmaceuticals respectively.

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References

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2Neely Michael N, van Guilder Michael G, Yamada Walter M, Schumitzky Alan, Jelliffe Roger W. Accurate Detection of Outliers and Subpopulations With Pmetrics, a Nonparametric and Parametric Pharmacometric Modeling and Simulation Package for R. Ther Drug Monit 2012;34(4):467–76. Doi: 10.1097/FTD.0b013e31825c4ba6.

3European Committee on Antimicrobial Susceptibility Testing. Breakpoint tables for interpretation of MICs and zone diameters European Committee on Antimicrobial Susceptibility Testing Breakpoint tables for interpretation of MICs and zone diameters. Available at 2016.

4Holmes Natasha E, Turnidge John D, Munckhof Wendy J, Robinson J Owen, Korman Tony M, O’Sullivan Matthew VN, et al. Vancomycin AUC/MIC ratio and 30-day mortality in patients with Staphylococcus aureus bacteremia. Antimicrob Agents Chemother 2013;57(4):1654–63. Doi: 10.1128/AAC.01485-12.

5Rybak Michael J. The pharmacokinetic and pharmacodynamic properties of vancomycin. Clin Infect Dis 2006;42 Suppl 1(Suppl 1):S35–9. Doi: 10.1086/491712.

6Craig William A. Basic pharmacodynamics of antibacterials with clinical applications to the use of beta-lactams, glycopeptides, and linezolid. Infect Dis Clin North Am 2003;17(3):479–501.

7Neely Michael N, Youn Gilmer, Jones Brenda, Jelliffe Roger W, Drusano George L, Rodvold Keith A, et al. Are vancomycin trough concentrations adequate for optimal dosing? Antimicrob Agents Chemother 2014;58(1):309–16. Doi: 10.1128/AAC.01653-13.

8Madady Ali. PID Type Iterative Learning Control with Optimal Gains. Int J Control Autom Syst 2008;6(2):194–203.

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Table 1.Summary of population parameters and target comparisons between obese and non-obese individuals receiving vancomycin in a non-critical care setting

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Figure 1.Probability of AUC:MIC target attainment in different simulated doses of vancomycin for non-critical care patients in secondary care.

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