VanquishThyTroughs:Targeting AUC/MIC …sites.utexas.edu/pharmacotherapy-rounds/files/2018/...VanquishThyTroughs:Targeting AUC/MIC forVancomycinDosing ) Jasmin)Badwal,)PharmD) PGYE1Pharmacy)Resident)

Vanquish Thy Troughs: Targeting AUC/MIC for Vancomycin Dosing

Jasmin Badwal, PharmD PGY-‐1 Pharmacy Resident

Department of Pharmacotherapy and Pharmacy Services, University Health System Pharmacotherapy Division, The University of Texas at Austin College of Pharmacy

Pharmacotherapy Education and Research Center, UT Health San Antonio March 9, 2018

At the end of this session, the learner will be able to: 1. Summarize pharmacokinetic and pharmacodynamic parameters of vancomycin2. Analyze current guideline recommendations for vancomycin dosing and monitoring3. Evaluate the utility and effectiveness of AUC/MIC vs trough guided vancomycin dosing and

monitoring on safety and clinical outcomes

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Assessment Questions

1. Which of the following describes the mechanism leading to vancomycin resistance?A. Target alteration B. Beta-‐lactamase production C. Increased cell wall thickness D. All of the above E. A and C only

2. Which pharmacodynamic parameter best correlates with vancomycin clinical efficacy?A. T>MIC B. AUC/MIC C. Cmax/MIC D. Cmax

3. True/False: Current guidelines recommend targeting vancomycin troughs of 15-‐20 mg/L forMRSA bacteremia.

A. True B. False

4. Which of the following is NOT a potential benefit of targeting AUC/MIC when dosingvancomycin?

A. Lower risk of nephrotoxicity B. Reduced vancomycin exposure C. Lower risk of resistance D. More efficient serum concentration sampling

*** To obtain CE credit for attending this program please sign in. Attendees will be emailed a link to an electronic CE Evaluation Form. CE credit will be awarded upon completion of the electronic form. If you do not receive an email within 72 hours, please contact the CE Administrator at ana.franco-‐martinez@uhs-‐sa.com ***

Faculty (Speaker) Disclosure: Jasmin K. Badwal has indicated she has no relevant financial relationships to disclose relative to the content of her presentation

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Background

I. Discovery1

a. Eli Lilly based program in 1950s with goal of discovering antibiotics against penicillin-‐resistant staphylococcus

b. Compound “05865” i. Discovered in dirt sample sent from Borneo in 1952 ii. Produced by Streptomyces orientalis iii. Dubbed “Mississippi mud” due to characteristic brown color and required significant

purification prior to use in clinical trials iv. Resulting drug was named “vancomycin” from the word “vanquish”

c. Approved by the Food and Drug Administration (FDA) in 1958 II. Delayed use1

a. Methicillin was preferred over vancomycin due to safety and efficacy concerns i. Initial use reserved for resistance or severe beta lactam allergy

b. Dramatic increase in vancomycin was seen in the 1980s with its role in pseudomembranous enterocolitis and the emergence of methicillin-‐resistant Staphylococcus aureus (MRSA)

c. Now one of the most widely used antibiotics for the treatment of serious gram-‐positive infections

III. Rate of MRSA at University Hospital2

Vancomycin overview

I. Class and chemical structure3

a. Large, tricyclic glycopeptide (molecular weight 1485.73 Da) II. Mechanism of action (MOA)3-‐5

a. Bacterial cell wall synthesis inhibitor i. Forms complexes with two peptidoglycan precursors

(D-‐alanyl-‐D-‐alanine) via 5 hydrogen bonds ii. Blocks incorporation (transpeptidation) of these

subunits into peptidoglycan

Figure 2. Chemical structure of vancomycin3

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Figure 1. MRSA Rates at University Hospital 1999-‐20162

Figure 3. MOA of vancomycin5

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Red man syndrome Nephrotoxicity Ototoxicity Local phlebitis Hypersensitivity Thrombocytopenia

III. Spectrum of activity3 a. Gram positive organisms

b. Gram negative organisms: nongonococcal Neisseria spp., Chryseobacterium meningosepticum c. Intrinsically resistant organisms: Leuconostoc spp., Pediococcus spp., Erysipelothrix

rhusiopathiae, Lactobacillus spp. IV. Mechanism of resistance (MOR)3,5-‐7

a. Alteration of target i. D-‐alanyl-‐D-‐alanine à -‐D-‐lactate or -‐D-‐serine ii. Results in loss of H-‐bond and decreased vancomycin binding affinity iii. Examples: vancomycin-‐resistant enterococcus (VRE) and S. aureus (VRSA)

b. Increased thickness of cell wall i. Excessive production of D-‐alanyl-‐D-‐alanine ii. Vancomycin trapped by excess and cannot reach target site (division septum) iii. Example: vancomycin-‐intermediate S. aureus (VISA)

c. Concern of increased incidence of resistance due to extensive use

V. Adverse effects4

VI. Vancomycin induced nephrotoxicity8-‐11 a. Generally mild-‐moderate and reversible b. Controversy whether cause or effect of impaired renal function c. Infectious Diseases Society of America (IDSA): ≥ 2 consecutive documented increases in

serum creatinine (of ≥ 0.5 mg/dL or ≥ 50% from baseline) after several days of vancomycin therapy

d. Zasowski EJ, et al. (2017) i. Nephrotoxicity was significantly higher in patients with greater area under the curve

(AUC) and trough values 1. AUC0-‐48 ≥ 1218 mg⋅h/L, AUC0-‐24 ≥ 677 mg⋅h/L, and trough24 ≥ 18.8 mg/L

Staphylococcus Enterococcus Streptococcus Bacillus Corynebacterium

Clostridium Pepto-‐streptococcus Actinomyces Propioni-‐

bacterium Nocardia

Figure 4. MORs of vancomycin5,7

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ii. Daily AUC values between 600-‐800 mg⋅h/L during the first 48 hours were associated with a 3-‐4 x increased risk of nephrotoxicity

VII. Common clinical uses3

Skin and soft tissue Endocarditis Meningitis Pseudomembranous colitis

Bacteremia Pneumonia Ventriculitis Osteomyelitis

Vancomycin pharmacokinetics

I. Pharmacokinetics (PK)4,9,12

a. Absorption i. Poor systemic absorption with oral administration ii. Time to peak: immediate after intravenous infusion

b. Distribution i. Volume of distribution (Vd): 0.4 – 1 L/kg ii. Cerebrospinal fluid (CSF) concentrations increase with inflammation iii. Distribution phase: 30 minutes – 1 hour iv. Protein binding: ~50 -‐ 55%

c. Metabolism: potential increased half-‐life and decreased clearance in impaired liver function d. Half-‐life elimination

i. Adults: 6-‐12 hours (prolonged with renal impairment) ii. End-‐stage renal disease (ESRD): 7.5 days

e. Excretion: glomerular filtration (75% as unchanged drug) Vancomycin pharmacodynamics

I. General pharmacodynamic (PD) properties13,14

a. Area under the curve (AUC) vs trough i. AUC: cumulative exposure of agent over a defined time

period ii. Trough: single point exposure measurement at the end of the dosing interval

b. MIC: lowest concentration of antimicrobial that will visually inhibit growth after 18-‐24 hours of incubation i. Breakpoint is determined by the Clinical and Laboratory Standards Institute (CLSI)

c. Concentration vs time dependent killing

i. Three major measures of efficacy 1. T>MIC: time above MIC 2. AUC/MIC: area under the curve over MIC 3. Cmax/MIC: maximum concentration over MIC

AUC = F x D / Cl F = bioavailability, D = Dose,

Cl =clearance

Susceptible

• Isolates inhibited by usually achievable concentrations• Likely clinical efficacy

Intermediate

• Isolates with MICs that approach attainable blood and tissue levels• Response rates may be lower• Clinical efficacy varies dependingon site and dose

Resistant

• Isolates not inhibited by usually achievable concentrations• MICs or diameters in range where resistance mechanisms are likely• Clinical efficacy not likely

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II. Vancomycin specific pharmacodynamics a. Method of action à “slowly” bactericidal9,10

i. Dependent on site of infection, bacterial inoculum size, MIC, and organism

b. Optimal parameter8-‐10 i. AUC/MIC shown to be best predictor of

clinical outcomes ii. In-‐vitro studies showed that increasing 24-‐

hour AUC/MIC values had the highest correlation with decreasing bacterial counts

c. MIC breakpoints6,14-‐16 i. Lowering of S. aureus susceptibility breakpoints in 2006 due to:

1. Association between higher vancomycin MICs with treatment failure 2. Increased incidence of heteroresistant strains

ii. Heterogenous vancomycin-‐intermediate S. aureus (hVISA) 1. MIC is within susceptibility range but some of the cells present are in the

intermediate range iii. MIC creep

1. Increasing vancomycin MICs over time however exact mechanism is unknown 2. Associated with poor outcomes, even with susceptible MICs

iv. MIC > 1 of S. aureus has been reported as independent predictor of treatment failure, however this is controversial

d. Controversy in susceptibility testing17 i. Significant concern with ability to differentiate MIC 1 vs 2 ii. Standard used by CLSI is the broth microdilution (BMD) reference method iii. Comparison vs BMD testing

1. Etest® and Microscan systems are more likely to overcall MICs 2. BD Phoenix™ and Vitek® 2 systems are more likely to under-‐call MICs

Current guideline recommendations

I. Background8

a. First and only guideline on vancomycin therapeutic dose monitoring (TDM) published in 2009 b. Supported by American Society of Health System Pharmacists (ASHP), Infectious Diseases

Society of America (IDSA), and Society of Infectious Disease Pharmacists (SIDP) c. Guideline is currently in the process of being updated

Susceptible (S) Intermediate (I) Resistant (R) S. aureus ≤ 2 µg/mL 4-‐8 µg/mL ≥ 16 µg/mL Coagulase negative Staphylococcus ≤ 4 µg/mL 8-‐16 µg/mL ≥ 32 µg/mL Enterococcus spp. ≤ 4 µg/mL 8-‐16 µg/mL ≥ 32 µg/mL

Etest MicroScan Vitek 2 Phoenix Absolute agreement 36.7% 61.8% 54.3% 66.2%

Vancomycin Pharmacokinetics/Pharmacodynamics • CID 2006:42 (Suppl 1) • S37

Figure 2. Relationship between pharmacokinetic/pharmacodynamic indices for vancomycin and bacteriologic efficacy against methicillin-susceptibleStaphylococcus aureus. This plot, which delineates the change in colony-forming units (cfu) in an experimental mouse infection model 3 differentways, suggests that the area under the curve divided by the MIC (AUC/MIC) is the most valuable pharmacokinetic/pharmacodynamic parameter forpredicting the activity of vancomycin against methicillin-susceptible S. aureus. Peak/MIC, peak serum concentration divided by the MIC. Data are fromEbert [23].

Moise-Broder et al. [26] examined the relationship between thevancomycin AUC/MIC and the outcomes of 108 patients withmethicillin-resistant S. aureus pneumonia. An AUC/MIC valueof !400 was associated with a successful outcome, whereas anAUC/MIC value of !400 was associated with a lower eradi-cation rate and a higher mortality rate ( ) [26]. A recentP p .005study examined the relationship between the AUC/MIC valueand a successful outcome in 168 patients with S. aureus bac-teremia. The MIC50 was 0.5 mg/L (range, 0.25–1.0 mg/L), andthe median AUC/MIC value was 1072. Overall, in this study,no relationship was found between successful outcome and aspecific AUC/MIC value [27].

The development of staphylococcal resistance to vancomycinhas been associated with prolonged exposure to low serumconcentrations of the drug. GISA infection and subsequentfailure of vancomycin therapy have been reported since themiddle of the 1990s. By definition, these strains have a van-comycin MIC of 8–16 mg/L. The majority of cases of GISAinfection have occurred among patients receiving peritonealdialysis or hemodialysis who had received suboptimal, pro-longed, and repeated courses of vancomycin [28]. Most casesof GISA infection have involved serum concentrations of van-comycin that were consistently "10 mg/L. Although the num-ber of cases of GISA infection has remained low, there appearsto be some evidence that this type of resistance has occurredin the past but may have been underreported because of ourinability to detect these strains in the clinical laboratory [29].The Centers for Disease Control and Prevention recommendsthe use of vancomycin screening plates of 6 mg/L, which mayincrease our ability to detect these strains [30]. S. aureus strains

that display heteroresistance to glycopeptides (i.e., heterores-istant GISA strains) have also been reported to be associatedwith vancomycin therapy failure [30, 31]. These strains typicallyhave an MIC of 1–4 mg/L but contain a subpopulation of cellsthat exhibit higher MIC values when plated onto agar platescontaining vancomycin or when tested with a heavy inoculaby use of the Etest (AB BIODISK) methods for antimicrobialsusceptibility. Similar to GISA strains, these organisms are dif-ficult to detect in the clinical laboratory, and their prevalencemay be underreported [32]. Recent in vitro evaluations havedemonstrated a relationship between exposure to low vanco-mycin serum concentrations and the development of hetero-resistant GISA [33]. However, because of the difficulty in de-tecting these strains clinically, the overall prevalence and clinicalsignificance of heteroresistant GISA have not been established[32, 34].

TOXICITY

In recent years, there appears to be less controversy with regardto the relationship between serum vancomycin concentrationsand toxicity. Historically, vancomycin toxicities were related toimpurities in the manufacturing process [1]. Although mostanimal studies have not found that vancomycin causes ne-phrotoxicity, there have been a number of studies involvinghumans that have attempted to link elevated serum vancomycinserum concentrations with renal damage [35–39]. Most of thesestudies are retrospective, and definitions for nephrotoxicity arehighly variable. In many cases, serum vancomycin concentra-tions were measured after an elevation in serum creatinine

Downloaded from https://academic.oup.com/cid/article-abstract/42/Supplement_1/S35/275535by gueston 15 January 2018

Figure 5. Vancomycin bacteriologic efficacy against MSSA8

Table 1. 2016 CLSI MIC breakpoints for vancomycin14

Table 2. MIC testing comparison17

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II. Dosing and monitoring recommendations8

Evidence basis for dosing and monitoring recommendations

I. Clinical effectiveness of AUC/MIC ≥ 400 target

II. Troughs as “surrogate markers”

a. Many studies have shown that lower troughs (< 15 mg/L) are able to achieve goal AUC/MIC ≥ 400 mg⋅h/L

b. Targeting AUC/MIC ≥ 400 mg⋅h/L may reduce unnecessary vancomycin exposure and lower nephrotoxicity risk

Study Design Results Moise-‐Broder PA, et al. (2004)18

Retrospective review n = 108 patients S. aureus respiratory tract infection

• AUC/MIC ≥ 400 associated with superior clinical and bacteriological response (p = 0.0046), and more rapid bacterial eradication (p = 0.0402) vs % time/MIC

Holmes NE, et al. (2013)19

Observational study n = 182 patients S. aureus bacteremia

• AUC/MIC > 373 (not ≥ 400) using BMD was associated with reduced mortality (P = 0.043)

Prybylski JP, et al. (2015)20

Meta-‐analysis – 14 cohort studies n = 1677 patients S. aureus bacteremia

• Higher AUC/MIC associated with reduced treatment failure (OR 0.41, CI 0.31–0.53), persistent bacteremia (OR 0.53, CI 0.33–0.86), and mortality (OR 0.47, CI 0.33–0.65)

• Troughs ≥ 15 mg/L were not associated with the above • Regression analysis mean AUC/MIC = 418

Men P, et al. (2016)21

Meta-‐analysis – 9 cohort studies S. aureus infections High (≥ 400) vs low (<400) AUC/MIC

• Lower mortality [RR = 0.47 (95% CI 0.31 – 0.70), p < 0.001] and treatment failure [RR = 0.39(0.28–0.55), p = 0.001] with high AUC/MIC

• Optimal PD parameter is AUC/MIC, however lack of consensus on ideal calculation• Troughs recommended as "surrogate" markers for AUC

TDM parameters

• Obtained at steady state (prior to 4th dose)• Monitoring recommended for patients with high risk of nephrotoxicity, unstable renal function, or receiving prolonged courses of therapy ( > 3-‐5 days)• Once-‐weekly monitoring recommended in stable patients with long-‐term treatment

Trough monitoring

• Troughs should always be > 10 mg/L to avoid development of resistance• If MIC = 1 mg/L, minimum trough concentration should be at least 15 mg/L to achieve target AUC/MIC• Trough concetrations of 15-‐20 mg/L are recommended in complicated infections

Optimal trough concentration

• Loading dose (LD) = 25-‐30 mg/kg x 1; Maintenace dosing (MD) = 15-‐20 mg/kg every 8-‐12 hours• All dosing based on actual body weight (ABW)

Adult dosing regimen

Table 3. Literature review of outcomes associated with AUC/MIC target

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III. Support for suggested targets a. Troughs < 10 mg/L are associated with increased resistance development

b. Very limited clinical data to support the goal range of 15-‐20 mg/L à goal is to have a higher likelihood of achieving target AUC/MIC

c. Even when targeting troughs of 15-‐20 mg/L, PK data has shown that AUC/MIC > 400 mg⋅h/L is not likely to be achieved if MIC ≥ 2 mg/L for S. aureus22

Study Design Results Patel N, et al. (2011)22

Monte Carlo simulation Probability of target attainment (PTA) of AUC/MIC ≥ 400

• With troughs 15-‐20, all regimens produced PTA of 100% at MIC ≤ 1 • With trough 10-‐15, all three regimens of 1g, 1.5g, and 2g every 12 hrs

produced PTA > 70% when MIC ≤ 1

Neely MN, et al. (2014)23

Pharmacokinetic data analysis from 3 studies n = 47 patients

• Trough-‐only and peak-‐trough data sets underestimated true AUCs vs full data set: 23% (11-‐33%; P = 0.0001) and 14% (7-‐19%; p < 0.0001)

• Normal renal function, therapeutic AUC of ≥ 400, and MIC = 1 o ~ 60% were expected to have a trough < 15 vs ~ 32% a trough < 10

Bel Kamel A, et al. (2017)24

Retrospective analysis n = 88 elderly patients Assumed MIC = 1

• AUC24 and Cmin correlation (R2 = 0.51)

• AUC24 was ≥ 400 in 95% (53/88) of cases when Cmin ≥ 15, 37% (35/88) when Cmin < 15, and 76% (81/88) when Cmin ≥ 10

• Logistic regression: Cmin of 10.8 mg/L optimal predictor of AUC24 > 400

Study Design Results Howden BP, et al. (2004)25

Retrospective review n = 25 reduced vancomycin susceptibility S. aureus (SA-‐RVS)

• Vancomycin failure: 16 patients (76%) • 80% patients with recorded vancomycin levels had a low trough

(<10 mg/L) during the first week of therapy Charles PG, et al. (2006)26

Retrospective review MRSA (n = 53) vs hVISA (n = 5) bacteremia

• hVISA group was more likely to have: • High bacterial load infections (p = 0.001), vancomycin treatment

failure (p <0.001), initial trough levels <10 µg/mL (p = 0.006)

Study Design Results0 Kullar R, et al. (2011)15

Retrospective review Single-‐center n = 320 with MRSA bacteremia

• Vancomycin failure = 52.5% • Troughs 15-‐20 associated with lower failure rates (39.5% vs 57.8%) • CART analysis: higher failure with AUC24 < 421 (61.2% vs 48.6%, p = 0.038) • Independent predictors of failure: endocarditis, initial trough < 15, and

MIC > 1 by E test Zelenitsky S, et al. (2013)27

Retrospective review Multicenter n = 35 with MRSA septic shock

• Survival rate was 2.5x higher with initial troughs ≥ 15 [70.6% (12/17) vs. 27.8% (5/18); p = 0.001]

• CART analysis: greater survival seen with AUC24/MIC ≥ 451 (p = 0.006) and ≥ 578 (p = 0.012)

≤1 mg/L. However, while trough concentrations of 15–20 mg/L ensureAUC values of at least 400 mg∗L/h, there is considerable variability inthe upper range of AUC values. This can be shown through a MonteCarlo simulation (n = 5000) of the vancomycin concentration-timeprofile based on the administration of a 1 g every 8 hour regimenusing a well-established population PKmodel [13,24,25].When one ex-amines the relationship between the trough concentration after thethird dose and AUC24 (Fig. 2), a trough concentration will not explainmore than approximately 50% of the inter-individual variability in theAUC (R2= 0.409). Therefore, one cannot rely solely on the vancomycin“15–20 mg/L” trough concentration range to achieve an AUC/MICBMD

ratio ≥400 for S. aureus isolates with MIC values in excess of 1 mg/L.

4. Concerns of acute kidney injury with trough vancomycinconcentrations of 15–20 mg/L

Due to the reluctance to estimate AUC values at the bedside, the lim-ited data in support of the 15–20 mg/L range for vancomycin serumtrough concentrations has raised the question of whether we need tomaintain even higher trough values in clinical practice. There are twothings to consider when evaluating drug therapy. First, the drug mustbe efficacious. Second, the drug must be non-toxic. While maintenance

of trough concentrations in excess of 20mg/Lwill ensure a higher prob-ability of achieving anAUC/MICBMD ratio N400 for S. aureus isolates withMIC values N1 mg/L, this may not be possible without subjectingpatients to an increased risk of vancomycin-related toxicities, mostnotably AKI [6–9,11,19,20,26–55]. Nephrotoxicity is a long-standing,yet highly debated, adverse effect associatedwith vancomycin adminis-tration [56,57]. To date, 14 studies [6–9,11,20,22,26,27,30,32–34,36,47]of note have comparatively assessed the AKI potential of maintaininghigher vancomycin trough concentrations (N15 mg/L) relative tolower troughs (b15 mg/L) in clinical practice and the results of thesestudies are well summarized in the systematic literature review byVan Hal et al. [12]. Overall, maintaining trough concentrations in excessof 15mg/L was found to substantially increase the risk of a nephrotoxicevent (OR 2.74; 95% CI 1.94–3.88, p b 0.01) relative to trough concentra-tionsb15mg/L. The probability of a nephrotoxic eventwas also found toincrease as a function of treatment duration, with most episodes occur-ring after seven days of therapy [12]. Collectively, these data stronglysuggest that adherence to the recommendations for vancomycinserum trough concentrations in recent expert guidelines [3,4] may re-sult in an elevated risk of vancomycin-induced AKI.

As noted above, there is a high degree of inter-individual variabilitybetween a measured trough concentration and the actual AUC value[13]. Therefore, it is difficult to estimate the degree of AKI associatedwith a given trough concentration due to the wide range of AUC valuesassociated with it. There have been limited attempts in the literature toquantify the relationship between AUC and the probability of AKI [32,58]. While data are scant, an AUC range of 700–1300 mg h/L has beensuggested to increase the risk of nephrotoxicity [14,32,58,59]. Suzukiet al. [58], compared the mean vancomycin AUC in patients who werenephrotoxic and non-nephrotoxic in a recent case–control study. Mostpatients in the nephrotoxic group had AUC24 values between 600 and800 mg∗h/Lwhile thosewho remained non-nephrotoxic were between400 and 600 mg∗h/L (p= 0.014). Our group also recently examined therelationship between AUC and occurrence of AKI among hospitalizedpatients receiving vancomycin [32]. In contrast to Suzuki et al. [58],we found that the probability of AKI increased 2.5-fold among patientswith AUCs above 1300 mg∗h/L compared with those below (30.8% vs.13.1%, p = 0.02) [32]. Interestingly, although AUC values in excess of1300 mg∗h/L were associated with a substantial increase in AKI, anAUC exposure-response relationship appeared to exist (Fig. 3) [59]. Inparticular, the probability of a nephrotoxic event increased as a functionof the AUC and patient's body weight [59]. Collectively, these limiteddata suggest that vancomycin-induced AKI occurs along a continuumand that certain populations may be at particular risk.

Fig. 1. Probability of achieving an AUC/MIC ratio≥400 for vancomycin dosing regimens ofvarying intensity when trough vancomycin concentrations are between 15 and 20 mg/L.

Fig. 2. Scatter and linear fit plot of vancomycin area under the curve over 24 h (AUC24)versus trough vancomycin concentration from 5000 subject Monte Carlo simulation.

Fig. 3. Probability of nephrotoxicity versus vancomycin area under the curve from time 0to 24 h (AUC0–24) by body weight breakpoint.

52 M.P. Pai et al. / Advanced Drug Delivery Reviews 77 (2014) 50–57

Table 5. Literature review of trough levels associated with resistance

Table 6. Literature review of trough goal 15-‐20 mg/L

Table 4. Literature review of trough and AUC/MIC correlation

Figure 6. PTA of AUC/MIC > 400 with target troughs 15-‐20 in S. aureus infections22

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Calculation methodologies for AUC/MIC

I. Equation-‐based approach28

a. Methods i. Based on first-‐order pharmacokinetic equations to estimate the AUC value ii. Requires collection of two timed steady-‐state vancomycin concentrations iii. No consensus recommendation on single, validated method iv. Trapezoidal equations are one of the most commonly used methods (Appendix B)

b. Availability à Free online calculators (Appendix C)

II. Bayesian approach23,28,29 a. Methods

i. Software based program using population modeling to optimize vancomycin dosing ii. Only one vancomycin concentration required (not at steady state) iii. Based on Bayes’ theorem

1. Patient’s PK parameter values (volume or clearance) prior to administering the drug based on how drug has behaved in prior patients (“Bayesian prior”)

2. Measured drug concentrations collected from patient after administration of drug regimen

3. Revised probability distribution of patient’s PK based on their dosing and drug concentration data (“Bayesian conditional posterior”) a. Allows estimation of vancomycin AUC value with low bias and computes

further AUC-‐optimized dosing recommendations b. Availability

i. “BestDose” program from University of Southern California ii. Free online download for Windows only (Appendix D) iii. In process of updating to new web-‐based program

III. Correlation between methods

a. Neely MN, et al. (2014)23 i. Pharmacokinetic data analysis from combination of three studies (total n = 47 adults) ii. Bayesian vs trapezoidal

1. Use of trough-‐only data to calculate AUC with Bayesian program allowed for 97% (95% CI 93 – 102%, p = 0.23) accurate estimation

Pros Cons Manually and/or electronically calculated Can be programed into Microsoft Excel or EMR Allows prediction of next dose

Complex formulas Population-‐based assumptions Time and workflow commitment Non-‐adaptive to physiologic changes Requires 2 levels at steady state

Pros Cons Free, available software Only one level required (no steady state requirement) Adaptive to physiologic changes Quick prediction of next dose and level

Electronic calculation only Training, time, and workflow commitment Patient data security Unknown cost/extent of next update

Table 7. Application of equation-‐based approach

Table 8. Application of Bayesian approach

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b. Kishk OA, et al. (2017)29

i. Study comparing three different AUC calculation methods (Trapezoidal, Chang, and Le)in pediatric patient population1. Likelihood of achieving AUC/MIC > 400 varied from 16.4% to 90.9%2. Trapezoidal method: r2 = 0.59, median AUC/MIC 447.4 (IQR 296.56-‐619.01)3. Chang method: median AUC/MIC 160.81 (IQR 97.98-‐291.96)4. Le method: median AUC/MIC 743.29 (IQR 586.65-‐950.2)

Clinical Question

I. Hale CM, et al. (2017)30 Are vancomycin trough concentrations of 15-‐20 mg/L associated with increased attainment of an AUC/MIC ≥ 400 in patients with presumed MRSA infection? Objective To determine whether there is an association between different target ranges of

vancomycin trough concentrations and attainment of a calculated AUC/MIC ≥ 400 Methods

Design • Retrospective chart analysis• 472-‐bed, tertiary care academic medical center (November 2013 – January 2015)

Patient population

• 100 patients• Stratified by their initial troughs (<10, 10-‐14.9, 15-‐20, and >20 mg/L)

Inclusion criteria Exclusion criteria • Positive MRSA culture• Steady state vancomycinconcentration

• Inappropriately timed troughs• Unstable renal function or HD• Vancomycin doses based on each level

Outcomes Primary Secondary • Association between goal trough andreaching calculated AUC/MIC ≥ 400

• Corrected average trough associatedwith development of acute kidney injury

Calculations and definitions

• AUC = TDDvanc /Clvanc• Estimated Clvanc = (CrCl x 0.79 + 15.4) x 0.06• CrCl = creatinine clearance (mL/min)o Cockcroft-‐Gault equation on date of admit (capped at 120 mL/min)

• AUC/MIC = calculated AUC divided by MIC of isolated MRSA (by VITEK® 2)• Acute kidney injury (AKI) = increase in SCr by 0.5 mg/dL or a 50% increase frompretreatment levels

• Average vancomycin trough = ([trough 1 x number of days] + [trough 2 x number ofdays] + [trough n x number of days]) / (total number of days on vancomycin)

Statistics • Categorical variables à Chi-‐square test or Fisher exact test• Continuous variables à Student t test or Mann-‐Whitney U test• All tests were two-‐tailed and p < 0.05 was considered significant

Results Baseline characteristics

Characteristic Value Characteristic Value Mean age, years (SD) 59.2 (17.1) MIC = 1, n(%) 94 (94) Non-‐ICU, n(%) 86 (86) MIC = 2, n(%) 1 (1)

Should AUC/MIC be the preferred method for vancomycin therapeutic drug monitoring?

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Median SCr, (IQR) 0.7 (0.5 – 0.9) Median AUC/MIC (IQR) 378 (305 –472) Median CrCl, (IQR) 102 (74.5 – 120) Mean weight-‐based dose,

mg/kg/day (SD) 26.3 (9.4)

Mean 24-‐hour dose, mg/day (SD) 2133.7 (820.3) Mean weight-‐based dose,

mg/kg (SD) 15.3 (3.1)

Culture source Value Culture source Value Wound, n(%) 32 (32) Biopsy/tissue, n(%) 18 (18) Sputum, n(%) 23 (23) Blood, n(%) 13 (13)

Primary outcome

• Patients that met goal AUC/MIC (%) = 42 (42%) • Troughs < 10 mg/L had 73% decreased likelihood of attaining goal vs troughs ≥ 10 mg/L (OR 0.27, 95% CI: 0.01-‐0.75, P = 0.018)

• Statistically significant difference between trough < 10 mg/L and ≥ 10 mg/L groups for median AUC/MIC (367 [IQR 303.5-‐384.5] vs 404.5 [IQR 305.5-‐509.5]; P = 0.041)

• No difference in target attainment between troughs 10-‐14.9 mg/L and 15-‐20 mg/L • Trough >20 mg/L group had significantly lower mean age, higher mean weights, and higher median CrCl

Secondary outcomes

• Only 97/100 patients had assessable renal function • AKI analysis: 9/97 (9.3%) developed AKI within first 10 days of treatment

o Corrected average vancomycin trough was significantly higher in patients who developed AKI (19.5 +/-‐ 3.6 vs 14.5 +/-‐ 4.2 mg/L, P < 0.001)

Author’s conclusions

• Limited association between higher serum vancomycin trough concentrations and attaining goal AUC/MIC ≥ 400 when troughs are above 10 mg/L

• Findings consistent with current recommendations of maintaining troughs above 10 mg/L to achieve target

• Significantly higher correct average vancomycin troughs were associated with development of AKI, however other causes of nephrotoxicity were not assessed

Reviewer’s critique Strengths • Outcome comparison between different trough ranges

• All levels at steady state • Variety of infection sites

Limitations • Retrospective study • Limited patient population • Trough timing and dosing deviations • Exclusion of patients with AKI/renal dysfunction

• Non-‐standardized AUC/MIC calculation • Majority skin and soft tissue infections • Majority non-‐critically ill patients • No analysis of concomitant nephrotoxins • No analysis of clinical outcomes

Overall conclusion

• Overall higher likelihood of achieving goal AUC/MIC with troughs > 10 mg/L, but troughs in 15-‐20 mg/L range were not associated with increased target attainment as suggested by guidelines

• No direct comparison of dosing methodologies on clinical outcomes à unable to recommend AUC/MIC based dosing over trough based, however general trough goal > 10 mg/L may be appropriate

Abbreviations: MRSA = methicillin resistant Staphylococcus aureus, SCr = serum creatinine, AUC = area under the curve, MIC = minimum inhibitory concentration; TDDvanc = total daily dose of vancomycin, Clvanc = estimated vancomycin clearance, CrCl = creatinine clearance (mL/min), AKI = acute kidney injury, HD = Hemodialysis, SD = standard deviation, IQR = interquartile range, CI = confidence interval

Badwal 12

II. Neely MN, et al. (2017)31

A prospective trial on the use of trough concentration versus area under the curve (AUC) to determine therapeutic vancomycin dosing Objective To test hypothesis that dosing vancomycin to target troughs > 15 mg/L leads to more

overdosing in adult patients compared to AUC-‐guided dosing Methods

Design • 3 year, prospective, serial cohort study • Los Angeles County – University of Southern California Medical Center

Patient population

• 252 adult patients (n) à Year 1 (n = 75); Year 2 (n = 88); Year 3 (n = 89) Inclusion criteria Exclusion criteria

• ≥ 18 years old • IV vancomycin with ≥ 1 concentration • Therapy ≥ 48 hours

• Any form of renal replacement • Expected survival of < 72 hours

Intervention • Controls = Year 1 = dosing on targeted troughs of 10-‐20 mg/L • Cohort = dosing based on target AUC/MIC ≥ 400 to max 800

o Year 2 = use of BestDose Bayesian software (MM BestDose) o Year 3 = use of BestDose Bayesian software (MMopt BestDose)

§ Additional functionality to calculate most optimal date/time for next level Calculations • Site-‐specific validated non-‐parametric population model

• BestDose Bayesian software à trapezoidal approximation to calculate AUC Outcomes Primary Secondary

• Proportion of all available troughs that were therapeutic vs proportion of all corresponding AUCs

• Vancomycin TDM • Treatment outcomes • Nephrotoxicity

Statistics • Alpha = 5% and power = 80% à required sample size of 90 patients in each group • Univariate analysis à Mann-‐Whitney test and Student’s t-‐test • Multivariate analysis à Kruskal-‐Wallis test and linear regression • Categorical data à Fisher’s exact or chi-‐square tests • All tests were two-‐tailed and p < 0.05 was considered significant


• No significant differences in age, weight, serum creatinine, or CrCl • Most common infection = SSTIs (46%) • Year 3 had more pneumonia (6% vs 10% vs 27%, p = 0.0002) and bacteremia (5% vs 8% vs 19%, p = 0.006)

• Most common isolated organism = S. aureus (n = 54) • MRSA isolates à88% had MIC ≤ 1 mg/L

Primary outcome

• 19% of troughs vs 70% of associated AUCs were therapeutic (P < 0.001) • 40/128 (31%) AUCs ≥ 400 mg⋅h/L were associated with trough concentration < 10 mg/L, and 87/128 (68%) were associated with troughs <15 mg/L o Close to simulation in previous study28

Year 1 (n = 233) Year 2 (n = 189) Year 3 (n = 201) p-‐value “Appropriate” trough 84 (36%) 87 (46%) 43 (21%) 0.02 # per conc range (mg/L)

<10 10 -‐ <15 15-‐20 >20

40 (47%) 14 (17%) 22 (26%) 8 (10%)

61 (70%) 19 (22%) 5 (6%) 2 (2%)

17 (40%) 20 (46%) 4 (9%) 2 (5%)

< 0.0001

Badwal 13

% within target trough Overall

Target 10-‐<15 Target 15-‐20

28% 13% 15%

13% 11% 2%

15% 9% 6%

0.04

% within target AUC/MIC Overall

≥ 400 and <800 300-‐400 and <800

75% 68% 7%

63% 56% 7%

73% 70% 3%

0.21

Secondary outcomes

Vancomycin therapy: mean (min – max) or median (IQR = 25th, 75th percentile)Year 1 (n = 75) Year 2 (n = 88) Year 3 (n = 89) p-‐value

Avg daily dose (mg) 1818 (275–2760) 1750 (700–3360) 1577 (750–4300) 0.46 Year 1 (n = 44) Year 2 (n = 51) Year 3 (n = 56) p-‐value

Days of vancomycin 7.8 (4.1, 14.3) 5.4 (4, 8.6) 4.7 (3.2, 8.7) 0.05 # samples/patient 3.6 (1-‐15) 2.1 (1-‐8) 2.4 (1-‐12) 0.007 Trough conc (mg/L) 14.4 (3.8 – 27.2) 9.7 (4.5 – 29.6) 10.9 (3.5 – 25.8) 0.005 Daily AUC (mg⋅h/L) 510 (160 – 1050) 459 (154 – 975) 459 (194 – 890) 0.29 Treatment outcomes • Resolved: 59 (71%) vs 60 (67%) vs 66(74%)

• Relapsed: 1 (1%) vs 0 vs 0

• Toxicity: 2 (2%) vs 0 vs 0• Failure or Death: 0 vs 0 vs 0

Nephrotoxicity • Mean SCr in each arm was 0.76, 1.05, and 1.2 (p < 0.0001)• Vancomycin-‐associated nephrotoxicity: 6 (8%) vs 0 vs 2 (2%) (p = 0.01)o Median concentration was 15.7 mg/L in nephrotoxicity group vs 8.7 mg/Lo Median length of stay was higher in nephrotoxicity group (20 vs 6 days, p = 0.002)


• More patients achieved “therapeutic success” when AUC/MIC was targeted• Trough targeting was associated with a higher risk of nephrotoxicity• No difference in clinical treatment outcomes between any of the groups• Trough-‐guided dosing should be replaced by Bayesian AUC-‐guided dosing

Reviewer’s critique Strengths • Direct comparison between trough vs AUC targeted dosing

• Similar results with trough and AUC association as seen in prior studyLimitations • Single-‐center

• Unclear trough-‐based dosing• Did not meet sample size requirement• Creators of Bayesian dosing program• Multiple MIC methodologies

• No comparison of baseline severity ofillness or concomitant nephrotoxins

• Less than half of patients haddocumented positive cultures

• Conclusions not supported by outcomesOverall conclusion

• There was no difference in target AUC obtainment nor treatment outcomesbetween all three groups

• In most cases goal AUC can be achieved with troughs < 15 mg/L• Nephrotoxicity conclusions based on limited occurrence and no in depth of analysisof any concomitant causes

• Bayesian methodology was associated with lower average duration and decreasednumber of blood samples however not clinically significant

• Final conclusion was not supported by any primary or secondary endpointsAbbreviations: conc = concentrations, TDM = therapeutic drug monitoring, h = hours, SCr = serum creatinine, CrCl = creatinine clearance, VAN = vancomycin, d/c = discharge, # = number, SSTI = skin and soft tissue infections, IQR = interquartile range

Badwal 14

III. Finch NA, et al. (2017)32

A quasi-‐experiment to study the impact of vancomycin area under the concentration-‐time curve-‐guided dosing on vancomycin-‐associated nephrotoxicity Objective To assess the impact of switching from trough to AUC-‐guided dosing

Methods Design • Single-‐center, retrospective quasi-‐experiment

• Detroit Medical Center (DMC) à January 2014 – December 2015 • Recent switch to target AUC24 of 400-‐600 mg⋅h/L

Patient population

• 1280 patients • 546 patients in trough group vs 734 patients in AUC group

Inclusion criteria Exclusion criteria • Documented or suspected infection • IV vancomycin for ≥ 72 hours and level drawn ≤ 96 hours of therapy

• Trough group: ≥ 1 near steady state • AUC group: ≥ 2 concentrations

• Treatment of meningitis, SSTIs without concomitant bacteremia, UTIs, or surgical prophylaxis

• Concomitant piperacillin-‐tazobactam (pip-‐tazo)

Calculations • Trapezoidal Rule AUC Calculations o AUCinf = [(Cmax+ Cmin)/2] x time of infusion; AUCelim = (Cmax + Cmin)/Ke o AUCdose = AUCinf + AUCelim; AUC24 = AUCdose x Number of daily doses

Outcomes Primary Secondary • Incidence of nephrotoxicity (3 different definitions)

• Impact on vancomycin exposures (dose, AUC, and troughs)

Statistics • Chi-‐square/Fisher exact test or the Student t test/Mann-‐Whitney U test • Multivariable logistic and Cox proportional hazards regression • Model fit was assessed with the Hosmer-‐Lemeshow goodness-‐of-‐fit test • All tests were two-‐tailed and p ≤ 0.05 associated with significance


• No difference in age, SCr, or CrCl Variable Trough (n = 546) AUC (n = 734) p-‐value

Median (IQR) APACHE II score 12 (7—17) 14 (9-‐22) <0.001 Nephrotoxins, n (%) 324 (59.4) 476 (64.9) 0.048

IV contrast 46 (8.4) 93 (12.7) 0.016 Furosemide 187 (34.4) 309 (42.1) 0.004

Indication, n (%) Pneumonia 198 (36.3) 369 (50.3) <0.001 Bacteremia 77 (14.1) 88 (12) 0.264

Sepsis of unknown source 70 (12.8) 107 (14.6) 0.368 Bone/joint 68 (12.5) 83 (11.3) 0.529

Other 86 (15.8) 50 (6.8) <0.001 Outcomes Trough (n = 546) AUC (n = 734) p-‐value

Vancomycin exposure (median (IQR)) Median (IQR) cumulative vancomycin dose (mg)

0 – 24 h 0 – 48 h 0 – 72 h

3250 (2438–4250) 5250 (4000–7500) 7500 (5438-‐10250)

3000 (2000–3750) 5000 (3750–6500) 7000 (5000–9250)

<0.001 <0.001 <0.001

Median (IQR) days of VAN 5.6 (4.1–7.3) 5.3 (4.0–7.1) 0.076 Median (IQR) trough conc (mg/L) 15.0 (10.8–19.5) 12.0 (8.4–15.7) 0.076 Median (IQR) AUC24 (mg⋅h/L) Not calculated 471.5 (361.5–576.7) -‐-‐-‐

Badwal 15

Nephrotoxicity, n(%) 2009 guideline definition 54 (9.9) 54 (5.4) 0.107

Akin Stage 1 or worse 2 or worse

3

106 (19.4) 64 (11.7) 17 (3.1)

132 (18) 65 (8.9) 22 (3)

0.515 0.092 0.905

Rifle category

Risk or worse Injury or worse

Failure

99 (18.1) 38 (7) 17 (3.1)

139 (18.9) 43 (5.9) 22 (3)

0.714 0.423 0.905

Time to nephrotoxicity by Cox proportional hazards regression Multivariable logistic regression

• Adjustments for severity of illness, comorbidity, duration of therapy, concomitant receipt of nephrotoxins on guideline-‐defined nephrotoxicity

• After correction, AUC-‐guided dosing was associated with less frequent nephrotoxicity (adjusted OR 0.514; 95% CI 0.332-‐0.794, [p = 0.0013])

Bayesian estimated vancomycin exposure profile (subgroup analysis)

Variable Trough (n = 150) (median, IQR)

AUC (n = 150) (median, IQR) p-‐value

AUC0-‐24 (mg⋅h/L) 705 (540-‐883) 474 (360-‐611) <0.001 AUC24-‐48 (mg⋅h/L) 663 (538-‐857) 532 (406-‐667) <0.001


• AUC-‐guided dosing was associated with significantly reduced nephrotoxicity after controlling for clinical differences

• AUC-‐guided dosing was associated with lower total daily vancomycin doses, AUC values, and trough concentrations

• This approach shows promise in reducing vancomycin-‐associated nephrotoxicity, however additional studies are required to examine impact on clinical efficacy against invasive S. aureus infections

Reviewer’s critique Strengths • Well defined nephrotoxicity outcomes and comparisons of different definitions

• Analysis of concomitant nephrotoxins • Assessment and correction of differences in baseline characteristics • Greater sample size than previous studies

Limitations • Single-‐center • Limited external validity -‐-‐ exclusion of pip/tazo and SSTIs

• No assessment of clinical outcomes • Baseline MICs not reported • Non-‐standardized AUC calculation

Overall conclusion

• Supports idea that current trough-‐based goals increase vancomycin exposure and further increase risk of nephrotoxicity à troughs >15 mg/L not required to reach goal AUC/MIC

• AUC/MIC targeted dosing was associated with less nephrotoxicity after adjusting for baseline characteristics

• Agree with final conclusion that additional studies are required to compare clinical success as primary outcome

Abbreviations: inf = infusion, elim = elimination, conc = concentration, SCr = serum creatinine (mg/dL), CrCl = creatinine clearance (mL/min), VAN = vancomycin, pip/tazo = piperacillin/tazobactam, SSTI = skin and soft tissue infections, IQR = interquartile range, CI = confidence interval

Badwal 16

Summary

Conclusions

I. Correlation

a. Troughs ≥ 15-‐20 are not more likely to achieve goal AUC/MIC than troughs ≥ 10-‐15 b. Limited evidence behind maintaining higher trough concentration for extended duration even

in the most invasive infections II. Importance of reaching target AUC/MIC

a. Mortality benefit only assessed with MRSA bacteremia and pneumonia b. Unclear applicability to other organisms and sites of infection

III. Practicality a. New online programs add simplicity to AUC/MIC calculations b. Significant variation in calculation methodologies still exist c. Switch to AUC/MIC-‐targeted dosing would require significant workflow changes and

education IV. Safety

a. Trough-‐targeted dosing associated with higher risk of nephrotoxicity vs AUC/MIC b. Vancomycin-‐induced nephrotoxicity is controversial, yet can be managed with simple dose

adjustments c. Dependent on concomitant nephrotoxins and duration of therapy, which majority of studies

did not assess V. Efficacy

a. Only one study attempted assessing treatment success as a secondary endpoint and found no significant differences between different targets

b. Future studies need to be designed to evaluate this as a primary outcome

Hale 2017 Neely 2017 Finch 2017 Design Retrospective

Single-‐center Prospective, Serial cohort

Single-‐center Retrospective, Quasi

Single-‐center Population n = 100 patients

Stratified based on trough level

n = 252 patients Years 1 (n=75), 2 (n=88),

3 (n= 89)

n = 1280 patients Trough (n=546) vs

AUC (n=734) Baseline 86% non-‐ICU

94% MIC = 1 50% SSTI, 13% bacteremia

88% MIC ≤ 1 46% SSTI

Higher APACHE II score, furosemide use, and

pneumonia in AUC group Outcomes

Correlation % @goal AUC/MIC ≥ 400: Troughs 10-‐14.9 = 51.6% Troughs 15-‐20 = 45.7% No significant difference

% @goal AUC/MIC ≥ 400: Troughs < 15 = 68%

No significant difference

Median trough of 12 associated with median AUC

471.5 mg⋅h/L

Nephrotoxicity Higher troughs associated with increased AKI risk Trough > AUC/MIC Trough > AUC

Clinical Efficacy -‐-‐ No difference in resolution,

relapse, failure, or death -‐-‐

Badwal 17

Final recommendations

I. AUC/MIC-‐targeted dosing should not yet replace all trough-‐based guideline recommendations

a. No validated calculation method b. Unclear recommendations for non-‐studied indications and non-‐MRSA organisms c. Difference in clinical outcomes not supported by current studies

II. Future studies are still needed before current vancomycin dosing protocols are changed III. Recommended trough goal adjustment

a. General trough target of 10-‐20 mg/L is appropriate for most patients regardless of indication b. If patient is not clinically improving on vancomycin, then trough target should be reassessed

or alternative therapies should be evaluated

Badwal 18

Appendices

Appendix A. Abbreviations AUC area under the curve mg milligrams AUCinf area under the curve for infusion MIC minimum inhibitory concentration AUCelim area under the curve for elimination MOA mechanism of action avg average MOR mechanism of resistance BMD broth microdilution MRSA methicillin resistance S. aureus CART classification and regression tree analysis MSSA methicillin susceptible S. aureus Cmax maximum concentration PD pharmacodynamics Cmin minimum concentration PK pharmacokinetics Conc concentration PTA probability of target attainment CrCl creatinine clearance (mL/min) S. aureus Staphylococcus aureus CSF cerebrospinal fluid SCr serum creatinine d/c discharge SSTI skin and soft tissue infection ESRD end stage renal disease T time h or hrs hours TDM therapeutic drug monitoring HD hemodialysis UTI urinary tract infection hVISA heterogeneous vancomycin-‐intermediate

S. aureus VAN vancomycin

g grams Vd volume of distribution kg kilograms VISA VAN-‐intermediate S. aureus L liters VRE VAN-‐resistant enterococcus LD loading dose VRSA VAN-‐resistant S. aureus MD maintenance dosing # number

Appendix B. Trapezoidal AUC calculation formulas28 1. Calculation of elimination rate constant (Ke)

o C1 = peak, C2 = trough o t = difference in time between C1 and C2

2. Back-‐ extrapolation and forward-‐extrapolation to compute theoretical concentrations o Ceoi’ = concentration at end of infusion = Cmax o Csoi ‘= concentration at start of infusion o Ct = trough concentration = Cmin o t’ = infusion time, t1 = time of end of infusion, t2 = time of end of dosing interval

3. AUC calculation o Scenario 1: estimating Ceoi’ and assuming Csoi’= Ct, or samples can be collected prior to dose (trough) and after dose (peak)

§ Under-‐predicts true AUC at end of infusion and ignores alpha-‐phase

o Scenario 2: back-‐extrapolate the concentration to Csoi’ § Slightly over-‐predicts true AUC at start of infusion

o Final AUC calculation:

relies on fewer assumptions and provides a “real world” snapshot of thepatient-level information for rapid clinical translatability. The majorlimitation of this approach is that it is not adaptive like the Bayesianapproach, and can only provide a snapshot of the AUC for the samplingperiod. This AUC calculation will not be correct if a physiologic changesuch as renal dysfunction occurs during or after the sampling period.

The equations to compute AUC from two samples are based in parton an original approach proposed by Begg, Barclay, and Duffull for ami-noglycosides [66] and modified by Pai and Rodvold [15]. This approachhas recently been validated for computation of daptomycin AUC [65].However, these previous investigations are based on the assumptionthat these agents are administered using a once-daily approach. This isoften not the case for vancomycin because twice daily and thrice dailydosing in patients with good kidney function is common. The AUCcomputation may be modified based on two concentrations as follows.

Fig. 4 reflects the concentration-timeprofile of vancomycin based onthe administration of 1000 mg every 8 h (1-hour infusion) and focuseson theprofilewhere TDM is often employed (around the3rd or 4th dose[at 24 h to 32 h time points of therapy]). As illustrated, the “true” vanco-mycin concentration follows at least a bi-exponential decline (2-compartment model). It is not possible to accurately characterize theinitial (α-phase) concentration-time profile without measurement ofa concentration between the end of infusion and the moment in thecurve that occurs 2–3 h from the start of infusion. Because two concen-trations may be measured during the same phase (β-phase) of theconcentration–time decline, it is possible to fit a mono-exponentialdecline function to characterize this profile from the start of infusion(artificial time) to the end of the dosing interval. This fit is also illustratedin Fig. 4.

The Sawchuk–Zaske method [67] can be used for this mono-exponential fit by computing the elimination rate constant (Ke) usingthe following equation.

Ke ¼Ln

C1C2

! "

tð1Þ

where, C1 is thefirst concentration after the dose thatmay be referred toas the “peak” concentration, C2 is the second concentration collectedtoward the end of the dosing interval or “trough” concentration, and tis the difference in time between these two concentrations. Once theKe is computed, this information can be used to compute theoreticalconcentrations through back-extrapolation (end of infusion or start of

infusion value). This method can also be used to forward-extrapolateconcentrations to the “true” trough concentration (Ct) at the end ofthe dosing interval. This may be necessary because it is often not clini-cally possible to measure the trough concentration exactly at the endof the dosing interval.

Once the theoretical (i.e., notmeasured) concentrations at the end ofinfusion (Ceoi), start of infusion (Csoi), and Ct are known, AUC can becalculated using arithmetic functions. In the first scenario (Fig. 5), theend of infusion concentration is estimated. The start of infusion andtrough concentration can be assumed to be the same because they areat near-steady state (Fig. 4), which permits superposition. Alternatively,samples may be collected prior to the dose (trough) and after the dose(peak) to expedite AUC calculation (instead of waiting until the end ofthe dosing interval).

The area between the start (same as Ct) and theoretical end ofinfusion (Ceoi′) for a given infusion time (t′) can be related as the areaof a trapezoid:

AUCt0−t1 ¼ Ceoi 0 þ Ct# $

% 0:5% t0 ð2Þ

The area under a mono-exponential curve from the time of the endof infusion (t1) to the time of the end of the dosing interval (t2) is:

AUCt1−t2 ¼Z infinity

t1Ceoi0 & e−Ke& tð Þdt−

Z infinity

t2Ct & e−Ke& tð Þdt

AUCt1−t2 ¼ Ceoi0− CtKe

:

ð3Þ

So the area under scenario 1 can be simplified to

AUCt0−t2 ¼t0 % Ceoi 0 þ Ct

# $

2þ Ceoi 0−Ct

Ke: ð4Þ

As shown by Fig. 5, this approach captures a majority of the area butwill under-predict the true AUC as the rise in concentration to the end ofinfusion is not entirely linear and theα-phase is ignored by thismethod.An alternative to overcome this limitationwould be to back-extrapolatethe concentration to the theoretical start of infusion (Csoi′). Under thissecond scenario (Fig. 6), the equation can be simplified to:


t0Csoi0 & e−Ke& tð Þdt−

Z infinity


AUCt0−t2 ¼ Csoi 0− CtKe

ð5Þ

Fig. 4. Expected concentration-time profile after administration of the 4th dose of a 1000mg every 8 hour regimen of vancomycin with a peak and trough concentration fit with amono-exponential decline function.

Fig. 5. Expected area under the curve captured using Eq. (4) based on an expected vanco-mycin concentration time profile.






Ke ¼Ln

C1C2

! "

tð1Þ






% 0:5% t0 ð2Þ




Z infinity



:

ð3Þ



# $

2þ Ceoi 0−Ct

Ke: ð4Þ




Z infinity



ð5Þ








Ke ¼Ln

C1C2

! "

tð1Þ






% 0:5% t0 ð2Þ




Z infinity



:

ð3Þ



# $

2þ Ceoi 0−Ct

Ke: ð4Þ




Z infinity



ð5Þ




Cp = C0 x e(-‐kt) Ct = Ceoi x e-‐k (T – t)

AUC24 = AUCt0-‐t2 x (# doses/day)

Badwal 19

Appendix C. Vancomycin AUC/MIC online calculators

1. https://www.vancomycin-‐calculator.com/ 2. http://clincalc.com/vancomycin/ 3. https://www.pharmacyjoe.com/vancomycin-‐aucmic-‐estimator/

Appendix D. Bayesian AUC/MIC online program

1. http://www.lapk.org/bestdose.php#top Appendix E. Nephrotoxicity outcome definitions32

necessary. In January 2015, the institutional guidelines for vancomycin dosing for the treatment ofinvasive infections were revised to target an AUC24 of 400 to 600 mg · h/liter. The upper end of the AUC24

target range was selected on the basis of data suggesting an association between an AUC24 of !600 mg ·h/liter and an increased risk of nephrotoxicity (11). In order to calculate patient-specific AUC24 values, twopostinfusion serum vancomycin concentrations were measured. AUC24 was calculated by estimating theAUC during the infusion by use of the trapezoidal rule (AUCinf " Cmax # Cmin/2 · time of infusion, whereAUCinf is the AUC from time zero to infinity and Cmax is the maximum concentration) and the AUC duringthe elimination phase (AUCelim) via the logarithmic trapezoidal rule (AUCelim " Cmax $ Cmin/eliminationrate constant). The AUC for a given dose was then calculated by adding AUCinf and AUCelim. Finally, AUC24

was calculated by multiplying this number by the number of daily doses.Outcomes. The primary outcome in this analysis was the comparative rate of acute kidney injury,

assessed by three different definitions of vancomycin nephrotoxicity (Table 4). The baseline SCr wasdefined as the SCr immediately preceding the first dose of vancomycin, if available. In cases in which thesample in which SCr was determined was drawn after the first vancomycin dose, the first SCr immediatelyafter the initial vancomycin dose was considered the baseline SCr. Secondary endpoints were measuresof vancomycin exposure, including the total daily vancomycin dose, AUC, and trough concentration.

Data analysis. In the primary analysis, the independent association between the vancomycin dosingstrategy and nephrotoxicity, as defined by the vancomycin consensus guidelines, was examined. Patientswho developed acute kidney injury were first compared to those who did not in a bivariate analysis usingthe chi-square/Fisher exact test or the Student t test/Mann-Whitney U test as appropriate. Multivariablelogistic regression analysis was then used to evaluate the independent predictors of nephrotoxicity. Thevariables associated with nephrotoxicity with biological plausibility in bivariate analysis (P % 0.1) weresimultaneously entered into candidate regression models and removed individually using a backwardelimination procedure until only variables with an adjusted P value of %0.1 remained. Vancomycinexposure variables (total daily dose, AUC, trough concentration) were not candidates for the regressionanalysis because they lie in the causal pathway between the monitoring strategy and nephrotoxicity.Model fit was assessed with the Hosmer-Lemeshow goodness-of-fit test; models with a nonsignificantresult were considered adequate. The multicolinearity of candidate regression models was assessed byuse of the variance inflation factor, with values of %3 considered acceptable. The association betweenthe monitoring approach and the time to nephrotoxicity was also assessed via Cox proportional hazardsregression, constructed in the same backward elimination approach as the logistic regression. Due tounanticipated differences in the severity of illness between the treatment groups, post hoc matchedanalyses were also performed with patients matched on APACHE II score &3.

As a secondary analysis, the vancomycin exposures achieved with the two monitoring approacheswere compared. First, the total daily vancomycin dose and clinically measured steady-state troughconcentrations were compared between the two groups in the entire cohort. AUC24 values could not bedirectly calculated for the trough concentration-guided dosing period due to a lack of multiple serumvancomycin concentrations per dose interval. As such, it was not possible to directly compare thecalculated AUC24 values for the entire cohort. In order to allow a comparison of AUC exposures betweenthe two dosing strategies, a subgroup analysis was performed using a Bayesian estimation on 300patients with a bacteremia or pneumonia indication. Patients with these indications from each groupwere first matched on indication and APACHE II score &3. One hundred fifty pairs were then randomlyselected for comparison. The concentration-time profiles for these patients were estimated via themaximum a posteriori probability (MAP) Bayesian function of the ADAPT V program using a previouslypublished 2-compartment population pharmacokinetic model as the Bayesian prior (32, 33). Thisapproach has been previously validated for estimation of the vancomycin AUC using trough-only serumconcentration sampling (3). Day 1 and 2 AUC values (AUC0 –24 and AUC24 – 48, respectively) and day 1 and2 trough concentrations ([Cmin24] and [Cmin48], respectively) were then compared between groups usingthe Mann-Whitney U test.

All statistical tests were two-sided, and P values of !0.05 were considered statistically significant.Statistical analyses were performed using SPSS (version 24.0) software (SPSS, Armonk, NY).

TABLE 4 Nephrotoxicity outcome definitionsa

Outcome Definition2009 vancomycin consensus guideline SCr increase of "0.5 mg/dl and "50% the baseline SCr for "2 consecutive measurements

Akin stage1 SCr increase of "0.3 mg/dl or "1.5 times baseline SCr2 SCr increase of "0.5 mg/dl or "2 times baseline SCr3 SCr increase of "3 times baseline SCr or acute increase of 0.5 mg/dl if SCr is "4 mg/dl

Rifle categoryRisk SCr increase of "1.5 times baseline SCr or CLCR decrease of !25%Injury SCr increase of "2 times baseline SCr or CLCR decrease of !50%Failure SCr increase of "3 times baseline SCr or CLCR decrease of !75%

aThe baseline SCr was defined as the SCr value immediately preceding the first dose of vancomycin, if available. In cases in which SCr was determined after the firstvancomycin dose, the first SCr value immediately after the initial vancomycin dose was considered the baseline SCr.

Finch et al. Antimicrobial Agents and Chemotherapy

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References

1. Levine DP. Vancomycin: a history. Clin Infect Dis. 2006;42 Suppl 1:S5-‐12.2. University Health System. Inpatient antibiogram. Rates of MRSA (1999 -‐ 2016). Accessed February 5, 2018.3. Murray BE, Arias CA, Nannini EC. Glycopeptides (vancomycin and teicoplanin), streptogramins (quinupristin-‐dalfopristin), lipopeptides

(daptomycin), and lipoglycopeptides (telavancin). In: Mandell GL, Bennett JC, Dolin R, editors. Principles and practice of infectious diseases. 8th ed. Philadelphia, PA: Elsevier/Saunders; 2015. ClinicalKey website. Available at: https://www-‐clinicalkey-‐com.proxy.lib.wayne.edu/#!/content/book/3-‐s2.0-‐B9780323401616000309?scrollTo=%23hl0000114. Accessed January 7, 2018.

4. Vancomycin. Lexi-‐Drugs Online™. Lexi-‐Comp Online™. Wolters Kluwer Health, Inc. Riverwoods, IL. Availableat: http://online.lexi.com. Accessed January 7, 2018.

5. Lowy FD. Antimicrobial resistance: the example of Staphylococcus aureus. J Clin Invest. 2003;111(9):1265-‐73.6. Howden BP, Davies JK, Johnson PD, et al. Reduced vancomycin susceptibility in Staphylococcus aureus, including vancomycin-‐intermediate

and heterogeneous vancomycin-‐intermediate strains: resistance mechanisms, laboratory detection, and clinical implications. Clin Microbiol Rev. 2010;23(1):99-‐139.

7. Mirza HC. Glycopeptide Resistance in S. aureus. In: Enany S, eds. Immunology and Microbiology “The rise of virulence and antibioticresistance in staphylococcal aureus”. INTECH; 2017. Available at https://www.intechopen.com/books/the-‐rise-‐of-‐virulence-‐and-‐antibiotic-‐resistance-‐in-‐staphylococcus-‐aureus/glycopeptide-‐resistance-‐in-‐s-‐aureus. Accessed March 1, 2018.

8. Rybak M, Lomaestro B, Rotschafer JC, et al. Therapeutic monitoring of vancomycin in adult patients: a consensus review of the American Society of Health-‐System Pharmacists, the Infectious Diseases Society of America, and the Society of Infectious Diseases Pharmacists. Am JHealth Syst Pharm. 2009;66(1):82-‐98.

9. Rybak MJ. The pharmacokinetic and pharmacodynamic properties of vancomycin. Clin Infect Dis. 2006;42 Suppl 1:S35-‐9.10. Álvarez R, López cortés LE, Molina J, et al. Optimizing the clinical use of vancomycin. Antimicrob Agents Chemother. 2016;60(5):2601-‐9.11. Zasowski EJ, Murray KP, Trinh TD, et al. Identification of vancomycin exposure-‐toxicity thresholds in hospitalized patients receiving

intravenous vancomycin. Antimicrob Agents Chemother. 2018;62(1). 12. Brown N, Ho DH, Fong KL, et al. Effects of hepatic function on vancomycin clinical pharmacology. Antimicrob Agents Chemother.

1983;23(4):603-‐9. 13. Levison ME, Levison JH. Pharmacokinetics and pharmacodynamics of antibacterial agents. Infect Dis Clin North Am. 2009;23(4):791-‐815.14. CLSI. Performance standards for antimicrobial susceptibility testing. Clinical and Laboratory Standards Institute. 2016;26.15. Kullar R, Davis SL, Levine DP, et al. Impact of vancomycin exposure on outcomes in patients with methicillin-‐resistant Staphylococcus

aureus bacteremia: support for consensus guidelines suggested targets. Clin Infect Dis. 2011;52(8):975-‐81. 16. Van hal SJ, Lodise TP, Paterson DL. The clinical significance of vancomycin minimum inhibitory concentration in Staphylococcus aureus

infections: a systematic review and meta-‐analysis. Clin Infect Dis. 2012;54(6):755-‐71. 17. Rybak MJ, Vidaillac C, Sader HS, et al. Evaluation of vancomycin susceptibility testing for methicillin-‐resistant Staphylococcus aureus:

comparison of Etest and three automated testing methods. J Clin Microbiol. 2013;51(7):2077-‐81. 18. Moise-‐broder PA, Forrest A, Birmingham MC, et al. Pharmacodynamics of vancomycin and other antimicrobials in patients with

Staphylococcus aureus lower respiratory tract infections. Clin Pharmacokinet. 2004;43(13):925-‐42. 19. Holmes NE, Turnidge JD, Munckhof WJ, et al. Vancomycin AUC/MIC ratio and 30-‐day mortality in patients with Staphylococcus aureus

bacteremia. Antimicrob Agents Chemother. 2013;57(4):1654-‐63. 20. Prybylski JP. Vancomycin trough concentration as a predictor of clinical outcomes in patients with Staphylococcus aureus bacteremia: a

meta-‐analysis of observational studies. Pharmacotherapy. 2015;35(10):889-‐98. 21. Men P, Li HB, Zhai SD, et al. Association between the AUC0-‐24/MIC ratio of vancomycin and its clinical effectiveness: a systematic review

and meta-‐analysis. PLoS ONE. 2016;11(1):e0146224. 22. Patel N, Pai MP, Rodvold KA, et al. Vancomycin: we can't get there from here. Clin Infect Dis. 2011;52(8):969-‐74.23. Neely MN, Youn G, Jones B, et al. Are vancomycin trough concentrations adequate for optimal dosing? Antimicrob Agents Chemother.

2014;58(1):309-‐16. 24. Bel Kamel A, Bourguignon L, Marcos M, et al. Is Trough Concentration of Vancomycin Predictive of the Area Under the Curve? A Clinical

Study in Elderly Patients. Ther Drug Monit. 2017;39(1):83-‐87. 25. Howden BP, Ward PB, Charles PG, et al. Treatment outcomes for serious infections caused by methicillin-‐resistant Staphylococcus aureus

with reduced vancomycin susceptibility. Clin Infect Dis. 2004; 38:521-‐8. 26. Charles PG, Ward PB, Johnson PD, Howden BP, Grayson ML. Clinical features associated with bacteremia due to heterogeneous

vancomycin-‐intermediate Staphylococcus aureus. Clin Infect Dis. 2004;38(3):448-‐51. 27. Zelenitsky S, Rubinstein E, Ariano R, et al. Vancomycin pharmacodynamics and survival in patients with methicillin-‐resistant

Staphylococcus aureus-‐associated septic shock. Int J Antimicrob Agents. 2013;41(3):255-‐60. 28. Pai MP, Neely M, Rodvold KA, Lodise TP. Innovative approaches to optimizing the delivery of vancomycin in individual patients. Adv Drug

Deliv Rev. 2014;77:50-‐7. 29. Kishk OA, Lardieri AB, Heil EL, et al. Vancomycin AUC/MIC and corresponding troughs in a pediatric population. J Pediatr Pharmacol Ther.

2017;22(1):41-‐47. 30. Hale CM, Seabury RW, Steele JM, et al. Are vancomycin trough concentrations of 15 to 20 mg/L associated with increased attainment of

an AUC/MIC ≥ 400 in patients with presumed MRSA infection? J Pharm Pract. 2017;30(3):329-‐335. 31. Neely MN, Kato L, Youn G, et al. Prospective trial on the use of trough concentration versus area under the curve to determine

therapeutic vancomycin dosing. Antimicrob Agents Chemother. 2018;62(2). 32. Finch NA, Zasowski EJ, Murray KP, et al. The impact of vancomycin area under the concentration-‐time curve-‐guided dosing on

vancomycin-‐associated nephrotoxicity: a quasi-‐experiment. Antimicrob Agents Chemother. 2017;61(12).

VanquishThyTroughs:Targeting AUC/MIC …sites.utexas.edu/pharmacotherapy-rounds/files/2018/...VanquishThyTroughs:Targeting AUC/MIC forVancomycinDosing ) Jasmin)Badwal,)PharmD) PGYE1Pharmacy)Resident)

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