Assessment of Susceptibility, Pharmacodynamics, and Therapeutic Response for Interpretation of Piperacillin-Tazobactam in Vitro Activity in the Treatment of Pseudomonas aeruginosa Infection


Pseudomonas aeruginosa remains an important pathogen. Our purpose was to determine the minimum inhibitory con-centration (MIC) and pharmacodynamic (PD) parameters predicting a positive response to therapy with piperacil-lin-tazobactam. Medical records were retrospectively reviewed at 3 centers. Data were recorded to assess age, type of disease, renal function, weight (body mass), MIC, antimicrobial treatment, and clinical outcome. Success was response to piperacillin-tazobactam alone, or in combination with another active agent; failure was lack of response. Of 78 eva-luable patients, 63 responded (7 UTI; 56 non-UTI) and 15 did not; 26 responding received combination therapy and 37 monotherapy. Piperacillin-tazobactam treatment was successful in 53 of 63 of non-UTI disease with a MIC of ≤64/4 μg/mL, but in only 3 of 7 with a MIC of >64/4 μg/mL (P = 0.023); overall 9 of 10 infections by strains with MICs = 32 - 64 μg/mL had a successful outcome. Piperacillin estimated time above MIC at 20% separated those responding from those that did not (P = 0.019).

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T. Gonzalzles, M. Suseno, J. Gaydos, P. Schreckenberger, C. Sincak, M. Mehta and L. Peterson, "Assessment of Susceptibility, Pharmacodynamics, and Therapeutic Response for Interpretation of Piperacillin-Tazobactam in Vitro Activity in the Treatment of Pseudomonas aeruginosa Infection," Open Journal of Medical Microbiology, Vol. 2 No. 3, 2012, pp. 101-109. doi: 10.4236/ojmm.2012.23015.

1. Introduction

The global plague of antibiotic resistant infections is recognized as a serious threat to world-wide healthcare [1]. This has been accompanied by a steady decline in the research and development of new antimicrobial agents to deal with the challenge. One of the key pathogen groups included in this threat are multidrug-resistant, increasingly pan-resistant, Gram-negative bacilli [1,2]. In this group is Pseudomonas aeruginosa, which remains an important pathogen that is steadily becoming more resistant to antimicrobial agents [3,4]. Treatment options for infections with this organism are limited. Traditionally, therapy of serious infection with P. aeruginosa has been accomplished with a combination of agents owing to the frequent resistance seen in this pathogen [5].

When dealing with a pathogen such as P. aeruginosa it is clear that an evidence-based approach as to what therapy is most likely to result in clinical response will be useful for selecting a treatment strategy. In order to accumulate these data there is a need to determine the outcome of therapy in a group of patients where in vitro susceptibility and pharmacodynamic parameters can be determined. The purpose of this study was to collect data that would determine what susceptibility breakpoint reliably predicts clinical success when piperacillin-tazobactam is used for therapy of P. aeruginosa infection at adequate doses and what pharmacodynamic parameter(s) can also guide in predicting human clinical response.

2. Patients and Methods

2.1. Subject Selection and Record Review

Patients were identified by retrospective review of databases at participating laboratories, recruited from the ClinMicroNet (an electronic network of leading Clinical Microbiology laboratory directors), from January 2007 to December 2008. Medical records were reviewed and patient data were collected on: age, gender, bodyweight, laboratory studies (including white blood count and serum creatinine), site(s) of infection, antimicrobial regimen and dose, and co-morbid illnesses. Treatment outcomes were determined for patients with infection from P. aeruginosa given piperacillin-tazobactam, alone or in combination with other antimicrobials, for a minimum of 72 hours. Outcomes were assessed based on clinical and bacteriologic parameters. Success was defined as improvement in clinical status with resolution of infection when piperacillin-tazobactam was the only active agent administered (monotherapy) or when two active agents, as measured by in vitro susceptibility testing, that included piperacillin-tazobactam were given (combination therapy). Treatment failure was defined as lack of improvement, death from infection, or persistently positive cultures. Outcome of piperacillin-tazobactam treatment was compared to the in vitro susceptibility of the organism determined by the participating laboratories. If more than one potential infected body site had P. aeruginosa recovered, the sample from the most serious infection was counted for this investigation; thus, blood stream infection superseded respiratory infection that superseded wound infection, which superseded UTI.

2.2. Laboratory Testing and Pharmacodynamic Analysis

Bacterial identification was performed by conventional methods. Susceptibility testing was performed by microbroth dilution or disk diffusion, and the actual or extrapolated MIC recorded [6-9]. Percentage of time above the MIC (%T > MIC) was estimated using a formula that combines individual pharmacokinetic parameters (piperacillin-tazobactam regimen, dosing interval, and MIC) plus published values for fraction unbound (70%) drug, volume of distribution (0.15 L/kg) and t1/2 (0.75 h) of piperacillin-tazobactam: %T > MIC = ln (fu × dose/Vd × MIC) × t1/2 /ln(2) × 100/t (where ln = natural logarithm, fu = fraction unbound, Vd = volume of distribution (L/kg), t1/2 = elimination half-life (h), and t = dosing interval (h)) [10-14]. For estimating the %T > MIC renal function was taken into account in order to modify the half-life of piperacillin-tazobactam. Creatinine clearance was estimated from prediction equations that took into account the serum creatinine concentration, age, gender, and body size/weight [15]. In mild to moderate renal impairment (serum creatinine = 2.5 - 7.5 mg/dL) the half-life of piperacillin-tazobactam only increases modestly as renal function declines (mean = 3.57 ± 1.36 hours), so that considerable variation of serum creatinine has little effect on measured half-life [16]. Patients were all treated over several days with initial dosage based on presenting weight (body mass) and creatinine clearance, then adjusted for changes in renal function during hospitalization until steady state was reached; providing a reasonable estimate of piperacillin-tazobactam exposure. A one-compartment, first order, intravenous model was used to estimate %T > MIC. While there is disagreement as to the accuracy of this model for pharmacodynamic analysis [17], the infusion time of piperacillin-tazobactam is relatively uniform (30 minutes), which negates meaningful differences as this time period allows for significant diffusion to the extravascular compartment during drug administration [14,18], particularly after several doses of the drug when steady state between the intravascular and extravascular compartments has been achieved. Tazobactam exposure was estimated by calculating the area under the concentration-time curve (AUC0-24).

2.3. Statistical Methodology

A Wilcoxon two sample test was used to assess the effect of continuous covariates (Age, Weight, White Blood Count (WBC), and Maximum temperature) to the outcome. As the data were skew distributed it was evaluated by the Shaprio-Wilk’s test and histogram distribution. A Chi-square test, Fisher’s exact test or an exact Pearson’s Chi-square test was used to evaluate the association between categorical covariates and the outcome. A P < 0.05 is regarded as statistically significance. Covariates with P < 0.25 (Stay in ICU, WBC, Maximum temperature, MIC > 64 µg/mL and %T/MIC < 20) in univariate analysis (Table 1) are included in the initial multiple regression model and removed backwardly at 0.05 significance level. Note that %T/MIC < 20 is derived from MIC and therefore they are not analyzed simultaneously in one multiple regression model.

2.4. Human Subject Review

Approval for this chart review study was obtained from the NorthShore University HealthSystem Institutional Review Board.

3. Results

3.1. Overall Outcome

We identified a total of 86 patients with infections caused by P. aeruginosa that were treated with piperacillintazobactam. Of the 86 cases discovered and reviewed, 3 did not have recorded susceptibility information and were excluded from analysis. Another 5 cases were indeterminate as to outcome based on the data recorded in the medical record (2 had therapy changed because of mixed infection with another piperacillin-tazobactam resistant Gram negative organism, 1 patient expired less than two days after treatment was begun, 1 had therapy discontinued because of hospice placement, 1 had therapy changed upon recognition of prior penicillin allergy)

Table 1. Covariates by outcome in univariate analysis.

and were also excluded, leaving 78 cases for this report. The patient groups were well matched when comparing the 63 success (including both monoand combination therapy) versus 15 failure subjects. Table 1 demonstrates that in univariate analysis a MIC > 64 µg/mL and %T/MIC < 20 are positively associated with unsuccessful outcome (P = 0.023 and 0.019 respectively). Specifically, cases with MIC > 64 µg/mL were more likely to have unsuccessful outcome (odds ratio: 7.27, 95% confidence interval: 1.43 - 37.09), and cases with an estimated %T/MIC < 20 were more likely to have unsuccessful outcome (odds ratio: 5.80, 95% confidence interval: 1.42 - 23.74). Cases with an elevated maximum temperature at the start of infection are also positively associated with unsuccessful outcome but the statistical significance is marginal (P = 0.067). The association between other covariates and the outcome did not reach statistical significance at a 0.05 level. Using the chosen statistical model and selection procedure, a multiple logistic regression for outcome (unsuccessful vs. successful) was attempted but only either MIC > 64 µg/mL or %T/MIC < 20 remained significant in the model; in other words, no significant multiple logistic regression model could be constructed because the other covariates were not significant in the multiple regression model. The covariate information collected for the patients with a successful and unsuccessful outcome along with the statistical analysis are in

Table 1.

Conflicts of Interest

The authors declare no conflicts of interest.


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