Area Under The Curve Monitoring Research Articles

A Multicenter, Retrospective Outcome Analysis of Vancomycin Area Under the Curve versus Trough-Based Dosing Strategies in Patients with Burn OR Inhalational Injuries (MONITOR).

Vancomycin is a glycopeptide antibiotic that requires close therapeutic monitoring. Prolonged exposure to elevated concentrations increases risk for serious adverse effects such as nephrotoxicity. However, sub-therapeutic concentrations may lead to bacterial resistance and clinical failure or death. The most recent Infectious Diseases Society of America (IDSA) publication regarding therapeutic monitoring of vancomycin recommends utilizing area under the curve (AUC)-based monitoring to maximize clinical success. Despite the guideline recommendation for AUC-guided dosing, many institutions still use trough-only monitoring in their practices, including those caring for patients with acute burn injuries. Following burn injury, patients are at a higher risk for infections, multi-organ failure, and pharmacokinetic alterations. The primary objective of this multi-center retrospective study is to determine optimal therapeutic monitoring of vancomycin by comparing clinical success between AUC vs. trough-based monitoring in burn patients. MONITOR was a multicenter, retrospective study of patients with thermal or inhalation injury admitted to one of 13 burn centers from 1/1/17 to 8/31/22 who received vancomycin. Demographic and clinical course data, including acute kidney injury (AKI) incidence and clinical success were obtained. Patients were evaluated for clinical success and grouped according to method of monitoring and adjusting doses: AUC vs. trough-based monitoring. Clinical success was a composite definition and lack of meeting any 1 of 5 criteria: 1) persistent infection, 2) relapse, 3) antibiotic failure (clinical worsening), 4) AKI, 5) death. Five-hundred seventeen vancomycin courses were assessed from 485 patients. There was no difference in the rate of clinical success between AUC monitored and the trough-only monitored groups. Incidence of AKI was higher in the trough-only group; however, was not statistically significant after controlling for renal function on admission, past medical history of chronic kidney disease (CKD), and concomitant nephrotoxins.

2877. Influence of vancomycin AUC monitoring on acute kidney injury in a large quasi-experimental study of over 3000 patients

Abstract Background Due to the inconsistent correlation of vancomycin trough concentrations with area under the curve (AUC) and increased rates of vancomycin-induced kidney injury (VIKI), an institutional practice change was implemented in 2017 to use 2-level AUC monitoring. The objective of the present study was to evaluate VIKI outcomes in a large quasi-experimental study. Methods A 4-year quasi-experimental study was performed at an academic medical center and included patients who received parenteral vancomycin for ≥ 72 hours. The primary outcome was the incidence of VIKI defined using KDIGO criteria. Secondary outcomes included inpatient all-cause mortality, median length of stay (LOS), median intensive care unit LOS, and median vancomycin trough concentration. Multivariable logistic regression analyses were used to identify primary predictors of VIKI and all-cause inpatient mortality while controlling for other significant covariates. Results The study included 3207 patients, with 1964 and 1243 in the trough and AUC groups, respectively. Similar baseline demographics (i.e., age, sex, race, weight, BMI, CrCl, Charlson Comorbidity Index) were noted between the groups. Patients in the AUC group were more likely to receive a vancomycin loading dose (32% vs 49%; p< 0.001) and have greater median trough concentrations (11.5 mg/L [8.1-16.0] vs 11.8 mg/L [8.9-16.2]; p=0.008). However, they also had lower median day 3 vancomycin exposures (3500 mg [2250-5000] vs 3250 mg [2500-4500]; p=0.008). Median AUC was 488 (396-607) in the AUC group. No significant differences were noted in the bivariate analysis of VIKI, defined as meeting criteria of any of the 3 KDIGO stages (20.5% vs 19.6%; p=0.112). The multivariable logistic regression suggested AUC monitoring was associated with a 23% decrease in VIKI (OR 0.767; 95% CI 0.621-0.947). All-cause inpatient mortality was significantly decreased in the AUC group (8.1% vs 6.3%; p=0.049). Conclusion VIKI was significantly reduced when AUC monitoring was employed in a large quasi-experimental study comprising over 3000 patients, one of the largest evaluations to date. This further strengthens the recommendation to transition to AUC monitoring for most patients receiving vancomycin for ≥ 72 hours. Disclosures All Authors: No reported disclosures

Implementing AUC Monitoring in a Pharmacist-Managed Vancomycin Dosing Protocol: A Retrospective Cohort Study.

Consensus guidelines on the therapeutic drug monitoring of vancomycin published in 2020 recognize that using the calculated area-under-the-curve (AUC) to guide dosing maximizes clinical efficacy and minimizes risk when compared to traditional trough-based dosing. The purpose of this study was to determine whether AUC monitoring results in reduced acute kidney injury (AKI) rates in adult patients receiving vancomycin for all indications. In this study, patients 18 years or older who received pharmacist-managed vancomycin therapy were selected using pharmacy surveillance software from 2 timeframes. Patients were excluded if they received less than 48 hours of therapy or had unstable renal function or hemodialysis at baseline. The primary outcome measured was the incidence of AKI in each group of patients. Data were collected for 121 patients in each group. Concomitant nephrotoxins used in each group, as well as the sources of infection, were similar between groups. AUC monitoring did not result in a significant decrease in AKI rate (16.5% in AUC group, 14.9% in trough group; P = .61). However, patients who received AUC monitoring were more likely to be therapeutic at first follow-up compared to the trough monitoring group (43.2% in AUC group, 33.9% in trough group; P = .03). AUC monitoring also resulted in lower trough levels and total daily doses, with no difference in mortality or length of stay. AUC monitoring did not result in an observed decrease in AKI rate. Despite this, the AUC monitoring protocol was effective at reaching the goal AUC of 400-600 mg*hour/L and did not increase mortality or length of stay.

Correlation of Calculated Vancomycin Trough Concentrations and Exposure: A Monte Carlo Simulation.

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. 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. 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. 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. 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.

Considerations for implementation of vancomycin Bayesian software monitoring in a level IV NICU population within a multisite health system.

The updated 2020 vancomycin therapeutic drug monitoring guideline advocates for area under the curve (AUC)-based monitoring in neonates, preferably with Bayesian estimation. This article describes the selection, planning, and implementation of vancomycin model-informed precision dosing (MIPD) software with Bayesian estimation in the neonatal intensive care unit (NICU) within an academic health system. The selection, planning, and implementation of vancomycin MIPD software was completed in approximately 6 months throughout a health system with multiple NICU sites. The chosen software captures data on medications in additional to vancomycin, provides analytics support, includes specialty populations (eg, neonates), and offers the ability to integrate MIPD into the electronic health record. Pediatric pharmacy representatives served on a system-wide project team with key responsibilities including development of educational materials, drafting changes to policies and procedures, and assistance with department-wide software training. Additionally, pediatric and neonatal pharmacist super users trained other pediatric pharmacists on software functionality, were available the week of go-live for in-person support, and contributed to the identification of pediatric and NICU-specific nuances related to software implementation. Neonatal-specific considerations when implementing MIPD software include: the selection of appropriate pharmacokinetic model(s), continued evaluation of such model(s), selection of appropriate model(s) in infants as they age, input of significant covariates, determination of the site-specific serum creatinine assay, decision of the number of vancomycin serum concentrations obtained, discernment of patients excluded from AUC monitoring, and the utilization of actual versus dosing weight. This article serves to share our experience with selecting, planning, and implementing Bayesian software for vancomycin AUC monitoring in a neonatal population. Other health systems and children's hospitals can utilize our experience to evaluate a variety of MIPD software and consider neonatal nuances prior to implementation.

Impact of Pharmacist-Led Multidisciplinary Team to Attain Targeted Vancomycin Area under the Curved Monitoring in a Tertiary Care Center in Thailand

Vancomycin Area Under the Curve (AUC) monitoring has been recommended to ensure successful clinical outcomes and minimize the risk of nephrotoxicity, rather than traditional trough concentration. However, vancomycin AUC monitoring by a pharmacist-led multidisciplinary team (PMT) has not been well established in Southeast Asia. This study was conducted at Thammasat University Hospital. Adult patients aged ≥ 18 years who were admitted and received intravenous vancomycin ≥48 h were included. The pre-PMT period (April 2020-September 2020) was defined as a period using traditional trough concentration, while the post-PMT period (October 2020-March 2021) was defined as a period using PMT to monitor vancomycin AUC. The primary outcome was the rate of achievement of the therapeutic target of an AUC/MIC ratio of 400-600. There was a significantly higher rate of achievement of therapeutic target vancomycin AUC during post-PMT period (66.7% vs. 34.3%, p < 0.001). Furthermore, there was a significant improvement in the clinical cure rate (92.4% vs. 69.5%, p < 0.001) and reduction in 30-day ID mortality (2.9% vs. 12.4%, p = 0.017) during the post-PMT period. Our study demonstrates that PMT was effective to help attain a targeted vancomycin AUC, improve the clinical cure rate, and reduce 30-day ID mortality. This intervention should be encouraged to be implemented in Southeast Asia.

Association of vancomycin-induced acute kidney injury with trough versus AUC monitoring in patients receiving extended durations of therapy.

Vancomycin therapy is associated with an increased risk of acute kidney injury (AKI). Previous studies suggest that area under the curve (AUC) monitoring reduces the risk of AKI, but literature is lacking to support this in patients receiving longer durations of vancomycin therapy. Retrospective cohort study. Patients ≥18 years old, admitted between August 2015 and July 2017 or October 2017 and September 2019, and received at least 14 days of intravenous (IV) vancomycin therapy were included in the study. Our primary outcome was the incidence of AKI between trough monitoring and AUC monitoring groups using Kidney Disease Improving Global Outcomes criteria. Secondary outcomes included inpatient mortality, median inpatient length of stay, and median intensive care unit length of stay. Overall, 582 patients were included in the study, with 318 patients included in the trough monitoring group and 264 included in the AUC monitoring group. The median duration of vancomycin therapy was 23 days (interquartile range, 16-39). Patients within the trough monitoring group had a higher incidence of AKI compared to the AUC monitoring group (45.6% vs 28.4%, p < 0.001). Furthermore, logistic regression analysis showed that AUC monitoring was associated with a 54% lower incidence of AKI (OR 0.46, 95% CI [0.31-0.69]). All-cause inpatient mortality was numerically higher in the trough monitoring group (12.9% vs 8.3%, p = 0.078). In patients who received at least 14 days of IV vancomycin therapy, AUC monitoring was associated with a lower incidence of AKI.

941. Clinical Outcomes of Vancomycin Area-Under-the-Curve Monitoring: A Quasi-Experimental Study Interim Analysis

Abstract Background The 2020 Infectious Diseases Society of America vancomycin guidelines recommend the use of area-under-the-curve (AUC) monitoring instead of trough concentration monitoring. These guidelines changed due to evidence showing decreased rates of nephrotoxicity and lack of correlation between vancomycin troughs and patient treatment outcomes. Two common methodologies of calculating AUC exist in clinical practice, including two level kinetic calculations and Bayesian software programs. Previous studies used two levels for calculating the AUC. The purpose of this study is to evaluate if the same reduction in acute kidney injury (AKI) is achieved while using a Bayesian software program. Methods This retrospective quasi-experiment was performed at two sites within the same health system. The primary objective of this study was to assess the rate of AKI, as defined by the Acute Kidney Injury Network (AKIN) criteria, between patients receiving vancomycin dosed by trough monitoring as compared to AUC monitoring. Secondary objectives include mean daily dose of vancomycin, number of vancomycin levels, and severity of AKI. Patients were included in the study if they were 18 years or older, with at least one vancomycin concentration drawn. Patients were excluded if they had a baseline serum creatine greater than 2 mg/dL, received renal replacement therapy of any type, or received &amp;gt; 1 doses of vancomycin prior to admission. After screening for inclusion criteria, patients were matched 1:1 based on APACHE II score and vancomycin indication. Results One hundred and thirty patients met inclusion criteria at the interim analysis. Overall, baseline characteristics were similar between groups. No statistical difference was detected regarding the rate of acute kidney injury between the vancomycin trough group and AUC group (12% vs 14% p=0.971). The mean total daily doses of vancomycin were 1642 mg per day in the AUC group and 1838 mg per day in the trough group (p=0.08). Conclusion No statistical difference in rates of AKI were detected at the interim analysis, likely due to small sample size. Further data collection is ongoing to meet power and full results will be presented. Disclosures All Authors: No reported disclosures.

Retrospective review of vancomycin monitoring via trough only versustwo-point estimated area under the curve in pediatric and adult patients with cystic fibrosis.

The primary objective of this study was to compare the occurrence of acute kidney injury (AKI) in patients with cystic fibrosis (CF) receiving intravenous (IV) vancomycin monitored through single serum trough concentrations and two-point estimated area under the curve (AUC). Time to next exacerbation and return to baseline lung function were also assessed. A retrospective review was conducted in patients of all ages with CF admitted to the University of Kentucky who received IV vancomycin between October 2015 and January 2021. Patients were excluded if they received less than 5 days of IV vancomycin therapy. A total of 113 adults and 42 pediatric encounters met the inclusion criteria. There was no statistically significant difference in occurrence of AKI, however, all grade 2-3 AKIs were in the serum through the monitoring group. Adult patients monitored with AUC also had a higher return to baseline lung function over trough monitoring (86% vs. 57%) (p = 0.002). There was not a statistically significant difference in time to the next exacerbation in either group. Adult patients with CF experienced less severe AKIs when monitored with AUC versus trough. The results of this study indicate that AUC monitoring may enhance the efficacy of IV vancomycin in adult patients with CF.

Methods of Therapeutic Drug Monitoring to Guide Vancomycin Dosing Regimens: Trough Concentration versus Ratio of Area Under the Curve to Minimum Inhibitory Concentration.

The most recent vancomycin monitoring guideline recommends targeting a value for area under the curve (AUC) of 400 to 600 mg*h/L, with an assumed minimum inhibitory concentration (MIC) of 1 mg/L. Few studies have investigated the effect of this method on vancomycin dosing regimens, relative to a target trough concentration of 15 to 20 mg/L. To compare vancomycin dosing regimens generated with the 2 monitoring methods. This retrospective chart review included hospitalized patients who received vancomycin between May 2019 and April 2020. The dosing regimens were compared, with the paired Student t test, in terms of unit dose, daily dose, and dosing interval. Variables of interest were collected from electronic medical charts. A pharmacy resident used first-order pharmacokinetic equations to determine dosing regimens based on AUC monitoring. Local pharmacists retrospectively determined dosing regimens for trough-based monitoring. Of 100 courses of treatment initially identified, 66 were included in the analysis. The unit dose was similar with the 2 methods (1086 mg with AUC-based monitoring versus 1100 mg with trough-based monitoring; p = 0.62). AUC monitoring was associated with a 12.8% lower daily dose (2294 mg versus 2630 mg; p < 0.001) and a 13.5% longer dosing interval (13.24 h versus 11.67 h; p < 0.001) relative to trough-based monitoring. AUC monitoring also generated a lower extrapolated trough concentration (12.90 mg/L versus 16.22 mg/L; p < 0.001). A target trough concentration of 15 to 20 mg/L was confirmed as being unnecessarily high. AUC monitoring could allow a reduction in daily vancomycin dose and an extension of the dosing interval relative to trough-based monitoring.

117 Evaluating Predicted vs. Actual Vancomycin Pharmacokinetic Target Attainment Using AUC Dosing

IntroductionVancomycin is a broad-spectrum antibiotic commonly used in burn patients. Traditionally, vancomycin has been managed with a trough level dosing strategy. However, recent literature and practice changes have encouraged utilizing an area under the curve (AUC) dosing strategy. The objective of this study was to evaluate the likelihood of attaining therapeutic targets using population kinetics in burn patients utilizing AUC.MethodsThis retrospective cohort included adult burn patients who received vancomycin dosed with an AUC strategy. Data collection covered 20 months following an institutional shift to AUC monitoring. Patients were excluded if they did not have pharmacokinetic (PK) data documented, received renal replacement therapy, or had a nonburn injury. The primary outcome was the difference between predicted and actual vancomycin AUC. Secondary outcomes included differences between additional PK parameters.ResultsThe AUC analysis included 14 patients. Mean (SD) age was 47 (12) years, 57% were male, and mean (SD) TBSA was 30 (21). The mean (SD) AUC in the predicted and actual groups was 522 (42) and 455 (122) mg*h/L, respectively (p=0.05). A total of 6 patients were evaluated for additional PK analysis, summarized in Table 1.ConclusionsActual patient-specific AUC was significantly lower than predicted AUC. This corroborates previous trough-based data indicating burn patients dosed using standard population estimates are at risk of being subtherapeutic, likely due to their hypermetabolic state. Our findings suggest AUC monitoring is an appropriate dosing strategy for burn patients and potentially more accurate than a traditional trough-based approach.

A Moving Target-Vancomycin Therapeutic Monitoring.

Therapeutic drug monitoring (TDM) has been a common practice to optimize efficacy and safety of vancomycin. While vancomycin trough-only TDM has widely been integrated into pediatric clinical practice since 2009, recently updated vancomycin TDM guidelines published in March 2020 recommend area under the curve (AUC) based TDM for vancomycin instead of trough-only TDM. In this review, we discuss the rationale behind the change in TDM recommendations, describe two approaches for calculating vancomycin AUC in clinical practice, and address considerations for integrating vancomycin AUC TDM into pediatric clinical practice. Our primary goal is to provide pediatric clinicians with a resource for implementing vancomycin AUC monitoring into clinical care.

Gap Analysis for the Conversion to Area Under the Curve Vancomycin Monitoring in a Small Rural Hospital

Consensus guidelines for vancomycin monitoring now recommend area under the curve (AUC) calculations for optimal vancomycin efficacy and safety. This will be a major practice change for many facilities. Implementation guidance is available but has not been reported in smaller, primary care hospitals. The objective of this study was to measure the uptake of AUC monitoring implementation in a rural facility. This is a gap analysis evaluating the appropriateness of vancomycin levels tests after the April 1, 2019 transition. All vancomycin levels between April 2019 and June 2019 after the go-live date were included with no exclusions in a retrospective chart review. The primary outcome was the proportion of levels in the appropriate time frame: peaks 1 to 2 hours after infusion with troughs at least 1 half-life after initial dose and prior to the next dose. Secondary outcomes included reasons identified for inappropriate levels and the proportion of AUC24 calculations within therapeutic range (400-600 mg.h/L). Descriptive statistics were used to measure the scope and outcomes of this transition. The transition was effective with 97% of cases utilizing AUC-based methods. There were 65 vancomycin levels in the 3-month study period with 86% deemed appropriate. Of the 9 inappropriate levels, 4 had to be repeated for accurate monitoring. There were 28 two-level couplets used for AUC24 calculations, 17 (61%) fell within therapeutic range. Implementation strategies for the AUC transition described in tertiary medical centers can be successfully utilized in primary facilities.

Pharmacist Survey: Pharmacist Perception of Vancomycin Area Under the Curve Therapeutic Drug Monitoring

Background: Evidence suggests the standard vancomycin trough goal of 15 to 20 mg/L for serious Staphylococcus aureus infections is associated with acute kidney injury, whereas appropriate monitoring of 24-hour area under the curve (AUC) may decrease nephrotoxicity. As a result, institutions have transitioned to AUC monitoring, the predictive pharmacokinetic/pharmacodynamic parameter of vancomycin to improve safety outcomes. However, this method may require increased pharmacist time and effort. Pharmacist perception of the practice change is largely unknown and warrants investigation. Methods: An electronic survey was disseminated via e-mail to pharmacists 5 months post-AUC implementation. Items of interest were focused on pharmacist perception, including quantity of patients monitored using AUC, justification of the practice change, differences in efficacy and safety, and changes in monitoring time requirements. Results: The pharmacist survey was distributed to 196 pharmacists and 84 responded (43% response rate). Eighty-one pharmacists had monitored patients using AUC methods. Sixty-nine percent of these respondents perceived the change to result in increased or slightly increased patient safety, 27% described no difference, and 4% stated safety was decreased or slightly decreased. Forty-two percent perceived the transition to result in increased or slightly increased efficacy, while 48% noted no difference and 10% responded that efficacy was decreased or slightly decreased. Pharmacists stated the creation of an institutional calculator decreased the time required to calculate AUC. Conclusion: After the change to AUC monitoring, pharmacists perceived improvements in safety outcomes while efficacy was at least similar if not increased.

Pilot Study of a Bayesian Approach To Estimate Vancomycin Exposure in Obese Patients with Limited Pharmacokinetic Sampling.

This study evaluated the predictive performance of a Bayesian PK estimation method (ADAPT V) to estimate the 24-h vancomycin area under the curve (AUC) with limited pharmacokinetic (PK) sampling in adult obese patients receiving vancomycin for suspected or confirmed Gram-positive infections. This was an Albany Medical Center Institutional Review Board-approved prospective evaluation of 12 patients. Patients had a median (95% confidence interval) age of 61 years (39 to 71 years), a median creatinine clearance of 86 ml/min (75 to 120 ml/min), and a median body mass index of 45 kg/m2 (40 to 52 kg/m2). For each patient, five PK concentrations were measured, and four different vancomycin population PK models were used as Bayesian priors to estimate the vancomycin AUC (AUCFULL). Using each PK model as a prior, data-depleted PK subsets were used to estimate the 24-h AUC (i.e., peak and trough data [AUCPT], midpoint and trough data [AUCMT], and trough-only data [AUCT]). The 24-h AUC derived from the full data set (AUCFULL) was compared to the AUC derived from data-depleted subsets (AUCPT, AUCMT, and AUCT) for each model. For the four sets of analyses, AUCFULL estimates ranged from 437 to 489 mg·h/liter. The AUCPT provided the best approximation of the AUCFULL; AUCMT and AUCT tended to overestimate AUCFULL Further prospective studies are needed to evaluate the impact of AUC monitoring in clinical practice, but the findings from this study suggest that the vancomycin AUC can be estimated with good precision and accuracy with limited PK sampling using Bayesian PK estimation software.

Implementation of a Vancomycin AUC Monitoring Program: Peaks and Pitfalls

Background Accuracy of vancomycin trough monitoring has come into question. We evaluated an area under the curve (AUC) monitoring protocol and 3 different dosing calculators at a single center.Methods Adult inpatients with vancomycin AUC monitoring from 5/2016–1/2017 were included. We excluded those with peaks drawn less than 1 hour after infusion. AUC was calculated with Sawchuck–Zaske (SZ) methodology. This was compared with two publicly available online calculators: ClinCalc and UCSF’s infectious disease monitoring program (IDMP). Paired t-tests were used to compare AUCs from ClinCalc and IDMP to SZ. We collected renal function, infection, microbiology, and dosing data. Clinical outcomes included survival to discharge, discharge disposition, rate of acute kidney injury (AKI) per Risk-Injury-Failure-Loss-End Stage Renal Disease criteria, and bacterial clearance.Results29 subjects were included. Median age was 48 years, 59% were male, median weight was 80.4 kg. Median daily dose was 3000 mg (32.4 mg/kg). No patient had renal impairment at baseline. Skin and soft-tissue infections were most common, 11 (38%). Six subjects had bacteremia, 2 had confirmed endocarditis. MRSA was isolated in 14 cases (48%). Median duration of vancomycin was 11 days. Mean 24 hour AUC (standard deviation) was 654 (203) mg/L for SZ, 536 (278) mg/l for ClinCalc (P = 0.02) and 556 (187) mg/L (P = 0.004) for IDMP. AUC differences of at least 30% compared with SZ were identified in 14 (48%) and 6 (21%) subjects evaluated with ClinCalc and IDMP respectively. AKI occurred in three subjects: two risk and one injury. All survived to discharge; 52% discharged home, 41% to a skilled nursing facility, 7% left against medical advice. Twenty (69%) had bacterial clearance, 2 (7%) had persistently positive cultures, 7 (24%) were treated empirically.Conclusion Vancomycin AUC varies with calculation methodology. The SZ method was impacted by dose and duration of infusion. ClinCalc showed greater variability in higher weight patients. ClinCalc and IDMP calculated lower AUCs than SZ, and recommended higher doses to target an AUC:MIC ratio of at least 400. As institutions adopt vancomycin AUC monitoring, awareness of calculator variation is critical due to impact on dose selection and risk of toxicity to patients.Disclosures All authors: No reported disclosures.

Fludarabine Busulfan Compared to Fludarabine Melphalan Is Associated with Increased Relapse Risk in Reduced Intensity Conditioning Transplant Despite Pharmacokinetic Dosing

Background: Fludarabine plus busulfan (FB) and fludarabine plus melphalan (FM) are two commonly used reduced intensity conditioning (RIC) regimens for allogeneic hematopoietic stem cell transplantation (SCT). A recent analysis showed that both regimens had similar overall survival (OS) but relapse incidence (RI) was significantly higher with FB with a trend towards higher non-relapse mortality (NRM) in FM (Baron et al., Cancer 2015). However, that cohort included patients treated with oral and intravenous busulfan without pharmakokinetic targeting of intravenous which may impact anti-leukemic activity.Aim: Compare transplant related outcomes of FB vs. FM using intravenous (IV) busulfan targeted to the area under the curve (AUC).Methods: After due IRB approval, patients with acute myelogenous leukemia (AML) and myelodysplastic syndromes (MDS) receiving RIC-SCT from 2008-2014 were identified. All baseline and laboratory features were retrospectively extracted. Busulfan dose in FB was 0.8 mg/kg IV for 10 doses with therapeutic AUC target of 900-1500 mcmol/L (min). All patients received T-cell replete grafts. Categorical and continuous variables were compared using Pearson's chi-squared and Wilcoxon/Kruskal-Wallis, respectively. Survival estimates were calculated using the Kaplan-Meier method and curves were compared using the log-rank test. Cumulative incidence was computed as competing events using Grey's model. Univariate and multivariate analyses were performed using Cox regression modeling.Results:A. Baseline characteristics and AUC monitoring: 134 pts were identified (47 FB and 87 FM). Median follow up of the entire cohort was 40 months (0-63.3) and at last follow up, 60% and 29% have died or relapsed, respectively. Baseline characteristics stratified according to conditioning regimen are shown in table 1. Younger age (60 yrs FB vs. 61 yrs FM, p = 0.015) and a trend towards a higher CMV R-/D- status (28% FB vs. 14% FM p = 0.064) were the only significant differences identified. All patients in the FB group received intravenous busulfan and 46/47 patients had evaluable AUC data with a range of 732-1354 mcmol/L (min). A total of 19 patients were outside of range, all <900 mcmol/L (min) and required a median dose increase of 28.1% (3.3-50.2%)B. Engraftment and toxicity data: The median time for platelet engraftment was 19 days (0-48) for FB vs. 16 days (14-183) for FM (p = 0.0023) whereas the median time to absolute neutrophil count (ANC) engraftment was 18 days (7-30) for FB and 15 days (11-40) for FM (p = 0.077). Cumulative incidence of grade II-IV, III-IV acute GVHD and chronic GVHD at 2-yr was 57.3%, 11% and 52.8% for FB and 48.6%, 17% and 63.4% for FM (p = 0.73, 0.4 and 0.21, respectively). Two patients in the FM group died of cardiac causes (heart failure and sudden cardiac arrest). No cases of sinusoidal obstructive syndrome were observed in either armC. Transplant outcomes: A significantly higher 2-yr relapse incidence (RI) was associated with FB vs. FM at 35.6% vs 17.3%, respectively (p = 0.0058). 2-yr progression free survival (PFS) was also significantly lower in the FB vs. FM at 51.2% vs. 65.1%, respectively (p 0.031). However, 2-yr OS and NRM was similar for FB vs. FM (53.1% and 22.9% vs 63.9% and 21.9%, respectively p = 0.26 and 0.89). Necessitating a dose adjustment based on AUC did not increase the risk for relapse or affect NRM. In multivariate analysis, FB was associated with increased RI with hazard ratio (HR) 2.29 (1.07-4.88; p = 0.033). Other factors significantly associated with RI on multivariate analysis were secondary/therapy related disease with HR 2.84 (1.34-6.02; p = 0.0067) and CR1 vs. other with HR 0.39 (0.17-5.32; p = 0.019). The significance of the results remained unchanged after exclusion of MDS patients (data not shown)Conclusion: Despite AUC dose adjustment, FB compared to FM was associated with increased RI with a similar OS and NRM. AUC dose adjustment did not impact transplant outcomes and its routine use in RIC should be further evaluated. Given the wide use of FB as a conditioning regimen, these important observations should be prospectively studied in a randomized fashion. [Display omitted] [Display omitted] [Display omitted] DisclosuresAl-Kali:Novartis: Research Funding. Wolf:Janssen Scientific Affairs, LLC: Consultancy.

A Minimally Invasive System for Glucose Area Under the Curve Measurement Using Interstitial Fluid Extraction Technology: Evaluation of the Accuracy and Usefulness with Oral Glucose Tolerance Tests in Subjects With and Without Diabetes

Recent studies have highlighted the importance of managing postprandial hyperglycemia, but adequate monitoring of postprandial glucose remains difficult because of wide variations in levels. We have therefore developed a minimally invasive system to monitor postprandial glucose area under the curve (AUC). This system involves no blood sampling and uses interstitial fluid glucose (IG) AUC (IG-AUC) as a surrogate marker of postprandial glucose. This study aimed to evaluate the usefulness of this system by comparing data with the findings of oral glucose tolerance tests (OGTTs) in subjects with and without diabetes. The glucose AUC monitoring system was validated by OGTTs in 37 subjects with and 10 subjects without diabetes. A plastic microneedle array was stamped on the forearm to extract IG. A hydrogel patch was then placed on the pretreated area to accumulate IG. Glucose and sodium ion concentrations in the hydrogel were measured to calculate IG-AUC at 2-h postload glucose. Plasma glucose (PG) levels were measured every 30 min to calculate reference PG-AUC. IG-AUC correlated strongly with reference PG-AUC (r=0.93) over a wide range. The level of correlation between IG-AUC and maximum PG level was also high (r=0.86). The painless nature of the technique was confirmed by the response of patients to questionnaires. The glucose AUC monitoring system using IG provided good estimates of reference PG-AUC and maximum PG level during OGTTs in subjects with and without diabetes. This system provides easy-to-use monitoring of glucose AUC, which is a good indicator of postprandial glucose.

Pharmacokinetics of tacrolimus in stable paediatric renal transplant recipients

Because tacrolimus (Tac) has a narrow therapeutic index and highly inter- and intra-individual variable pharmacokinetic (PK) characteristics, monitoring of drug exposure is recommended, but limited data are available on the kinetics of Tac in paediatric renal transplant recipients, especially of limited sampling strategies. To investigate the correlation between Tac trough level (TL) and the 0-12 h area under the curve (AUC), and the value of abbreviated AUC monitoring, we evaluated 12 h PK profiles in 27 children at least 1 year after transplantation. There was a significant discrepancy between Tac TLs and 0-12 h AUC (r = 0.60). Every time point, different from C(0), gave a better prediction for the drug exposure, with C(4) and C(6) as best predictors (r = 0.93 and r = 0.92, respectively). The 0-12 h AUC was estimated with great precision by the use of a two- or three-point sampling strategy, and the latter is more time-point independent. In paediatric renal transplant recipients on Tac maintenance therapy, whose condition is stable, Tac TL is not a reliable tool for the estimation of drug exposure. Abbreviated monitoring, especially at three points in time, give reliable predictions of the complete 0-12 h AUC. We suggest a 0-12 h AUC of around 150 ng x h/ml for stable paediatric renal transplant recipients 1 year after transplantation and around 100 ng x h/ml in the following years. Target AUC values should be further established for paediatric transplant recipients according to the time after transplantation.

Clinical monitoring method of area under the concentrations-time curve after the first oral tacrolimus

Objective To assess the predictability of individual tacrolimus (FK506) concentrations at different time points for the area under the curve (AUC) and to find the best sampling time for the abbreviated AUC to predict the total body exposure of tacrolimus. Methods 16 primary kidney transplant recipients were treated with methylprednisolone and antilymphocyte globulin for 3 days. The first tacrolimus oral dose, 0.075 mg/kg, was given at day 3 after transplantation. Blood samples were obtained at 0.5,1.0, 1.5, 2.0, 3.0, 5.0, 8.0, and 12.0 hours since taking the first oral dose. The tacrolimus blood concentration was measured by ELISA. Twelve-hour AUC (AUC12) for each patient was calculated using linear trapezoid rule. Associations between blood concentration at each sampling time points and the AUC12were measured by Pearson correlation coefficients. Abbreviated sampling equations were derived by multiple,stepwise regression analyses performed using AUC12 as the dependent variables. The variance in the strength of association between predicted AUC (AUCp) and AUC12 was reflected by the linear regression coefficient the minimum AUC12. The correlation between all the time points concentration, except C1.0, all the drug concentrations at different time points were significantly correlated with AUC ( all P＜0.05 ). Stepwise multiple regression showed that C5.0 might be the best predictor of the total body exposure of tacrolimus (R=0.92, R2=0.85). According to an abbreviated AUC monitoring strategy, the concentrations at hours 5 and 1.5 or hours 5, 1.5, and 3 were well correlated with AUC (R=0.97, R2=0.94 and R=0.99, R2=0.99, respectively). Conclusion Tacrolimus AUC12 shows remarkable interindividual variation after the first oral dose in Chinese renal transplant recipients. C5 may be the best predictor of the first AUC12. Twopoint sampling method using C5 and C1.5 and the three-point sampling method using C5, C1.5, and C3 may be the best abbreviated AUC to cost-effective tacrolimus monitoring strategy. Key words: Kidney transplantation; Tacrolimus ; Pharmacokinetics