Isepamicin in intensive care unit patients with nosocomial pneumonia: population pharmacokinetic–pharmacodynamic study

M. Toda,*, C. Minozzib, G. Beaucairec, D. Ponsonnetb, J. Cougnardb, O. Petitjeana and the Study Group

a Departement de pharmacotoxicologie, Hôpital Avicenne, 125 route de Stalingrad, 93009 Bobigny cedex b Schering Plough, 92 rue Baudin, 92307 Levallois-Perret c Service de Réanimation Médicale, Hôpital de Tourcoing, 135 avenue du Président Coty, 59208 Tourcoing, France


    Abstract
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
A population approach was used to determine isepamicin pharmacokinetics in 196 intensive care unit patients treated for nosocomial pneumonia with isepamicin and a broad-spectrum ß-lactam. Patients were randomized in four groups with respect to the following isepamicin dosing regimens: (i) 15 mg/kg od for 5 days or (ii) 10 days, (iii) 25 mg/kg on the first day followed by 15 mg/kg od for 4 days or (iv) 9 days. A total of 1489 serum isepamicin concentrations were measured (median, eight per patient; range, 1–18). Mean ± S.D. 1 h-peak levels at day 1 were 76 ± 32 mg/L after the 25 mg/kg dose (n= 85) and 43 ± 15 mg/L after the 15 mg/kg dose (n = 99). A bicompartmental model was fitted to the data by a mixed-effect modelling approach. Isepamicin clearance was related to age, bodyweight and serum creatinine level. Central volume of distribution was related to bodyweight. Pharmacokinetic parameters were independent of the dosage in the range 15–25 mg/kg and were not different in the patients treated for 5 or 10 days. Bayesian estimates of individual pharmacokinetic parameters were used to calculate various surrogate markers of isepamicin exposure to be tentatively correlated with clinical outcome and nephrotoxicity. No correlation was found between peak, AUC or their ratio with MIC and clinical efficacy. A weak correlation was found between the increase of serum creatinine level (day 1 versus day 5) and isepamicin 24 h trough level at day 1 (R2 = 0.10). These data do not favour a systematic therapeutic monitoring of isepamicin in intensive care unit patients, at least with the doses and antibiotic combinations used in this study.


    Introduction
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Single daily dosing of aminoglycosides is a concept supported by a number of pharmacodynamic characteristics, such as concentration-dependent killing, prolonged post-antibiotic effect, prevention of the emergence of resistant organisms, avoidance of the inhibiting effect of adaptive resistance and decreased uptake into sites of toxicity. 1 However, although a greater efficacy of single daily over multiple daily dosing seems to be demonstrated by most meta-analyses published to date (e.g. Ali & Goetz 2), the gain in efficacy is relatively modest. If we assume that the efficacy versus aminoglycoside exposure relationship is sigmoidal (i.e. that no effect is observed unless a sufficient exposure is reached, and a maximal effect is reached at high exposure) and that this relationship depends on the mode of administration, then a difference in the efficacy of various dosing regimens can be observed only at medium exposure, while no difference can be observed at high exposure. However, for aminoglycosides the parameters of this relationship vary from one patient to another, according to several factors including the bacterial strain and its MIC, 3,4 the site of infection, 5,6 the host defences (immunocompromised patients require higher aminoglycoside peak levels 7), the severity of underlying illness6 and the antibiotic combination, if any. These confounding factors account in part for the discrepancies in the efficacy of single or multiple daily dosing aminoglycosides between studies. To improve the rationale of aminoglycoside dosing, one major goal is to determine the efficacy versus exposure relationship and the factors contributing to its interindividual variability.- Previous studies in this area have highlighted the role of aminoglycoside peak concentration, the area under a concentration versus time curve, or their ratio with the MIC of the causative organism as markers of exposure related to efficacy. 5,6,8 Other studies suggested that nephrotoxicity observed during aminoglycoside treatment was related, among other factors, to aminoglycoside trough concentrations.9,10,11,12Such relationships have in turn consituted a basis for the definition of ‘therapeutic ranges’ for the aminoglycosides, but these ranges and the value of monitoring serum concentrations of aminoglycosides have been questioned.13

A clinical study of the efficacy of od dosing isepamicin used for 5 or 10 days, with or without an initial loading dose in ICU ventilated patients with nosocomial pneumonia is described in the companion article. 14 Briefly, the rationale for the design was as follows: 14 since initially high serum concentrations of aminoglycosides are thought to improve the prognosis of severe Gram-negative bacilli infections and the volume of distribution of these drugs is especially increased in intensive care unit (ICU) patients, a loading dose could be recommended. With respect to duration of treatment, nephrotoxicity is related to the length of aminoglycoside therapy, while these drugs are useful only during the first 5 days in most situations. Hence, short treatment duration needs to be evaluated. This study gave us the opportunity to assess retrospectively the efficacy and nephrotoxicity versus isepamicin exposure relationships. Besides this objective, the goals were to propose an optimized isepamicin dosing regimen according to these putative relationships and to define therapeutic ranges. Since the sparse sampling schedule did not allow estimation of individual pharmacokinetic parameters by traditional methods, a population approach15 was used to compute a homogeneous set of surrogate markers of isepamicin exposure to be related to clinical outcome.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Study design

A multicentre study was conducted in 52 ICUs. Adult patients with nosocomial pneumonia caused by Gram-negative bacilli were enrolled. All patients had an infection acquired at least 3 days after hospitalization. Nosocomial pneumonia was defined by clinical (temperature), biological (leucocyte count), and microbiological (culture) criteria and chest radiograph. Patients had a simplified acute physiology score I (SAPS) of between 6 and 25 on admission. Patients were not included if serum creatinine was >120 µM, if PMN count was <500/mm3, or in cases of AIDS, cystic fibrosis or burns. Patients were randomized into one of the four following groups according to isepamicin dosing schedule: (i) 15 mg/kg iv over 30 min od for 5 days or (ii) for 10 days, (iii) 25 mg/kg iv over 30 min the first day of treatment then 15 mg/kg od for 4 days or (iv) for 9 days. Isepamicin was combined with one cephalosporin, active against Pseudomonas aeruginosa or imipenem. In case of documented or suspected associated methicillin-resistant Staphylococcus sp. infection, a glycopeptide was given.

Measurements

Blood samples were taken by a research nurse at 1, 5, 12 and 24 h after the start of the first infusion, and 1 or 24 h after the start of one or several other infusions, i.e. ‘peak’ samples were obtained 0.5 h after the end of the infusion. Serum was separated and was immediately stored at -20°C until the isepamicin concentration was determined.

Isepamicin concentrations in serum were measured in each hospital participating in the study by immunopolarization of fluorescence (TDX; Abbott, Rungis, France). The limit of quantification was 0.4 mg/L. Interrun reproducibilities were 3.7% at 5 mg/L, 2.5% at 15 mg/L and 1.8% at 25 mg/L. Concentrations below the quantification limit were recorded as 0.2 mg/L (i.e. half the limit, which is the value that minimizes the average deviation from the true concentration) in the database.

The following covariates were also recorded: group of treatment (1 to 4), sex, age, bodyweight, SAPS and MacCabe score at the day of inclusion and serum creatinine (SCR). SCR values were obtained on days 1, 2 or 3, 5, 10 and/or at the end of treatment. Since the data file required that a covariate value be recorded at each dosing or measurement event, missing SCR values were calculated by linear interpolation between known values.

Population model

The concentration versus time data for isepamicin in serum were analysed by a non-linear mixed-effect modelling approach.14 The nj concentrations measured in patient j, Cj, were described by a pharmacokinetic model f (Pj, t) which is a function of the pharmacokinetic parameters Pj and of the time t. The differences between the observations Cj and the predicted concentrations Predj = f (Pj, tj) were accounted for by an error model involving a function g (Pj, t) and a random vector {varepsilon}j:


Residual errors {varepsilon}j were assumed to follow a normal distribution with zero mean and variance-covariance matrix o2I to be estimated. The residual error model [g(.)] was the so-called power model:


where b was a parameter to be estimated. This choice implied that variance of the residual error increased as concentration increased, a behaviour commonly observed in pharmacokinetic studies. No other error model was examined.

Interindividual variability was modelled through the distribution of Pj, which was assumed to be lognormal:


where j is the typical (median) value of the pharmacokinetic parameters in the population of patients having the same covariate values Xj as patient j, {eta}j is a random vector with normal distribution, zero mean and variance-covariance matrix {Omega} to be estimated, h is the covariate model (i.e. the functional relationship between the typical values of the parameters and the covariate values), and P is a vector of fixed effects to be estimated. This random effect model implied that the variance of the {eta}s were the approximate squared coefficient of variation (CV) of the parameters. The goal of the procedure was therefore to estimate P, {sigma} and {Omega} by nonlinear regression, given f(.), g(.) and h(.). Two different pharmacokinetic models [f(.)] were tested, namely a one or a two compartment open model with zero-order infusion rate. In the latter case, the parameters of interest were the elimination clearance Cl, the volume of the central compartment Vc, the clearance of distribution Cld, and the volume of the peripheral compartment VP.

Model building and goodness-of-fit

Possible correlations between the demographic and biological indices and the parameters of the model were explored using the approach described earlier.15,16 First, the structural model was fitted to the data to obtain the population parameters. Individual pharmacokinetic parameters were estimated by using a Bayesian maximum a-posteriori estimator (‘posthoc estimates’ , denoted j). Secondly, possible relationships between posthoc estimates and covariates were explored by visual examination of their scatterplots. Appropriate relationships were then incorporated into the population model. Thirdly, the new population model was fitted to the data. Several criteria of goodness-of-fit were considered for the inclusion of a covariate in the population model. The main criterion was the likelihood ratio test17 at the 0.05 level. Other criteria were the distribution of the weighted residuals, the distribution of the {eta}s, a reduction in the residual interindividual variability of the parameters, and a reduction in the residual error variance. At later stages in model building, some covariates were tentatively removed from the model and the goodness-of-fit was reassessed. For the final assessment of the adequacy of the population model, the main criteria were the plots of predicted concentrations versus observed concentrations, and the plot of weighted residuals versus time.

Pharmacokinetic analysis

Dose dependency of isepamicin kinetics was assessed by comparing the mean dose-normalized concentrations at 1, 5, 12 and 24 h after the first dose in the two groups of patients that received 15 or 25 mg/kg at day 1. The Mann-Whitney test was used.

Time dependency of isepamicin kinetics between day 5 and day 10 was assessed by comparing the typical values of the pharmacokinetic parameters in both groups (5 versus 10 days) of patients. The likelihood ratio test was applied, by using a categorical covariate describing the duration of treatment, DT. Taking the peripheral volume as an example, the covariate model was:



where DT = 1 if the treatment duration is 5 days, DT = 0 if the treatment duration is 10 days, VP1 and VP2 are the typical values of the peripheral volume of distribution of the patients treated for 5 or 10 days, respectively. This test was applied on the whole data and was repeated for each of the parameters of the model.

Time dependency was tested further by comparing the individual posthoc estimates obtained by fitting the model to the data from 0 to 48 h (analysis 1) and by fitting the model to the whole data, i.e. from 0 to 216 h (analysis 2).

Pharmacokinetic indices

A number of pharmacokinetic indices that could be related to efficacy or nephrotoxicity of the treatment were calculated for each patient, based on the posthoc estimates j. This procedure enabled us to test a homogeneous set of indices in all patients, regardless of the quantity of data gained in each individual or missing measurements.

The ‘peak’ concentration of isepamicin at 1 h after the start of the first infusion, Peak 1, was calculated as:


with


where T was the infusion duration (0.5 h), ‘Dose’ was the dose really administered to the patient, and t = 1 h. The parameters {alpha}, ß and k21 were calculated by standard formulae18 using l, c, ld and p.

The 24 h trough concentration after the start of the first infusion, C24, was calculated by the same formula but with t= 24 h.

The steady-state ‘peak’ concentration of isepamicin was obtained as:


where {tau} was the dosing interval (24 h) and t= 1 h.

The 24 h trough concentration at steady-state, C24ss, was calculated using the same formula, but with t = 24 h.

The area under the concentration versus time curve between 0 and 24 h after the start of the first infusion was estimated according to:



The area under the curve between 0 and 24 h after the start of the infusion at steady state was determined as:


where Dosage = 15 mg/kg times bodyweight.

Total drug exposure was calculated as the sum of AUC 1 and n.AUCss where n was the duration of treatment after the first day, expressed in days (i.e. n = 4 or 9).

The length of time isepamicin concentration remained above the MIC (T> MIC) was calculated by solving Cpred = MIC for time.

Pharmacodynamic analyses

Responses to antibiotic treatment were classified as success, failure or improvement at the end of treatment, and as success or failure 7 days later. Response to treatment was tentatively correlated with the pharmacokinetic indices described above. These correlations were assessed with (i) the patients per protocole, (ii) the patients from which a strain was isolated and the MIC was determined and (iii) the patients from which an intermediate-resistant or resistant strain was isolated. Only the patients treated for more than 5 days were considered and the ratio of the pharmacokinetic indices with MIC were tentatively correlated with response to treatment. The means of the pharmacokinetic indices in each category of response were compared using the Mann-Whitney test. Probability of response as a function of pharmacokinetic indices and several covariates (severity scores, age, combination with a glycopeptide etc.) was assessed by multivariate logistic regression.

Nephrotoxicity was appreciated by SCR increase and ClCR decrease during isepamicin treatment. The differences between SCR or ClCR values measured on day 5 or day 10 and the values measured on day 1 were tentatively correlated with the pharmacokinetic indices, SCR on day 1, glycopeptide administration, age and SAPS, by multivariate linear regression with stepwise inclusion or deletion of covariates. The threshold values of the F statistics were P = 0.05 for the inclusion and P = 0.10 for the exclusion of a covariate in the model.

Programmes

Fitting of the population model, individual Bayesian estimations, hypothesis testing and calculations of goodness-of-fit criteria were made using the software NONMEM IV.19 The so-called first order method was used. The more sophisticated first order conditional estimation (FOCE) method could not be used because of rounding errors in the estimation of individual parameters in a few patients. Other statistical tests and plots were computed using SPSS for Windows (release 6.1, SPSS France, Boulogne).


    Results
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 Abstract
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 Materials and methods
 Results
 Discussion
 References
 
Patients

Among the 204 patients, 196 were considered in the pharmacokinetic analysis; the remaining eight patients were excluded because measurements or covariates were missing. Major demographic and clinical data for these 196 patients are summarized in Table I. Since the characteristics of the patients of the four groups of treatment were very similar, all the data have been combined in the table. Creatinine clearance values, which were estimated according to Cockcroft and Gault,20 were fixed to 150 mL/min for two patients whose estimate was greater than this value because higher values are not realistic.


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Table I. Characteristics of the 196 ICU patients
 
Isepamicin levels

A total of 1489 isepamicin concentrations were measured. A plot of the distribution of the concentrations versus time is shown in Figure 1. The median number of samples per patient was eight (range, 1-18). Only two patients had one measurement, two patients had two measurements, and all other patients had three measurements or more. The number of measurements below the quantification limit was 34.



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Figure 1. Plot of isepamicin concentrations in serum versus time in the 196 ICU patients.

 
Dose dependency

The dose-normalized concentrations at 1, 5, 12 and 24 h after administered doses of 15 or 25 mg/kg on day 1 showed no significant differences. Therefore, isepamicin kinetics are linear with respect to doses in the range 15–25 mg/kg, i.e. isepamicin concentrations are proportional to the dose in this range. Due to this conclusion, the hypothesis of non-linearity was not assessed in the population model.

Model building

The main steps of isepamicin population pharmacokinetic model building from the whole data were as follows. A two-compartment model was more adequate than a one-compartment model. Elimination clearance was related to the covariates of creatinine clearance (i.e. age, sex, bodyweight and serum creatinine) by a Cockcroft and Gault-like formula. However, in the final model, sex could be removed since its influence on the adequacy of the model was marginal. The volume of the central compartment, but not that of the peripheral compartment was related to bodyweight. Graphical analysis and likelihood ratio tests showed that SAPS was not a significant covariate of any pharmacokinetic parameter when the whole data were analysed. Likelihood ratio tests showed no significant differences between the typical values of the parameters of the patients treated for 5 or 10 days. The final model was written as:





The values of the parameters of the final model are given in Table II. The standard errors of the estimators were reasonably small, with the exception of the SE of Var ({eta}Cld). The interindividual variability of Cl, Vc, Cld and VP, expressed as CV and having taken into account the covariates, were 59%, 32%, 57% and 132%, respectively. The CV of residual error (calculated by using{sigma}2 and b) was 67% at 2 mg/L and 15% at 50 mg/L. Although there were a few outliers (defined as an absolute weighted residual >3) in the distribution of weighted residuals versus time, no particular trend emerged from this plot, which was considered as satisfactory (data not shown). The weighted residuals of the 34 concentrations below quantification limit were less than unity. Since the main goal of the population analysis was to provide individual pharmacokinetic indices (based on Bayesian estimates) for pharmacodynamic analysis, the most important criterion for quali-fication of the population model was the correlation between observed and predicted concentrations, with predictions based on the Bayesian estimates of individual parameters. The corresponding plot is shown in Figure 2 and demonstrated a close agreement between predicted and observed concentrations.


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Table II. Population pharmacokinetic parameters of isepamicin in 196 ICU patients, estimated from all data (see text for the population model)
 


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Figure 2. Plot of predicted versus observed isepamicin concentrations in 196 ICU patients. Predicted concentrations were calculated by using the Bayesian estimates of individual parameters.

 
Time dependency

A population model was built to fit the data gained from 0 to 48 h in the 196 patients. This model was similar to the model described above, but SAPS was found to be a significant covariate of j(with negative correlation), cj and dj (with positive correlations). Goodness-of-fit of this model was better than that of the model fitted to the whole data (data not shown). Bayesian estimates of individual parameters were obtained with both population models. The median of individual estimates for 0-48 h and 0-216 h data, respectively, were very close for Cl (4.32 versus 4.06 L/h), Vc (18.3 versus 18.6 L) and Cld(1.84 versus 1.97 L/h), but differed widely for VP (16.3 versus 33.9 L) and t 1/2ß (10.4 versus 17.5 h). VP was nearly doubled when estimated from the 0–216 h data, which resulted in a 1.7-fold increase of isepamicin elimination half-life. It was verified by simulation that the typical difference between the 216 h trough concentrations predicted by each model was 1–1.5 mg/L, i.e. the difference was not clinically relevant (data not shown).

Efficacy versus pharmacokinetic indices

The characteristics of the distributions of the pharmacokinetic indices as a function of clinical outcome 7 days after the end of treatment for the 110 patients per protocol, the 81 patients for which the MIC of the bacterial strain had been determined and the 12 patients with an isepamicin-resistant strain are summarized in Table III. Similar results were obtained when clinical outcome was evaluated at the end of treatment (data not shown). Differences between pharmacokinetic indices, age, life expectancy (according to MacCabe’s score) and SAPS of patients with success or failure of treatment were not significant. Multivariate logistic regression did not show any significant relationship between clinical outcome and pharmacokinetic indices and covariates.


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Table III. Median (5th-95th percentiles) pharmacokinetic indices as a function of clinical outcome 7 days after the end of antibiotic treatment
 
Nephrotoxicity versus pharmacokinetic indices

The characteristics of the distributions of the differences between SCR or ClCR values on day 5 or 10 versus day 1 are shown in Table IV. Mean creatinine clearance increased by 5.1 mL/min between day 1 and day 5, and by 21.6 mL/min between day 1 and day 10. However, a few patients experienced a decrease in creatinine clearance (up to 56 mL/min). Multivariate analysis showed that isepamicin 24 h trough concentrations, C24 or C24ss, were the best predictors of an increase in serum creatinine or a decrease in creatinine clearance. AUC1, AUCss and total drug exposure were also correlated with SCR or ClCR variation, but the correlation was weaker than that with C24 or C24ss, and the correlation was not significant once C24 or C24ss were included in the regression model. Age, SCR on day 1, SAPS and combination with a glycopeptide were not associated with SCR or ClCR variations. The relationships between serum creatinine, C24 and C24ss, which gave the best correlations, were: dSCR51 = 2.59 (0.40) x C24-10.7 (2.7) with r2 = 0.284, and dSCR51 = 1.97 (0.36) x C24ss-10.5 (2.9) with r2= 0.218. The S.E. of each coefficients is given in parentheses. The relationship for C24 predicts an SCR increase of 10 or 20 µM at day 5 if isepamicin 24 h trough concentrations are 8.0 and 11.9 mg/L after the first administration.


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Table IV. Differences in serum creatinine levels and creatinine clearance at day 5 or 10 versus day 1 during antibiotic treatment
 

    Discussion
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Since isepamicin pharmacokinetics in ICU patients had been studied earlier and compared with those in healthy volunteers,21 the main interest of the present study was not in pharmacokinetics per se, but in the correlation between individual pharmacokinetic indices and clinical outcome or nephrotoxicity. The population pharmacokinetic model was intended mainly to estimate individual parameters by the Bayesian method, thereby allowing computation of a homogeneous set of potential predictors to be related to clinical events in all patients, regardless of interindividual differences in the number and times of isepamicin concentration measurements. Therefore, pharmacokinetic data will be discussed briefly, while more emphasis will be given to pharmacodynamics.

The pharmacokinetic results of this study have to be compared with those of our previous publication21 in 85 ICU patients with pneumonia. The bicompartmental model was found more adequate than a one compartment model and the significant covariates were qualitatively similar. The mean isepamicin elimination clearance was 22% lower in the previous study (3.2 L/h versus 4.1 L/h), but median creatinine clearance was also 19% lower (69 ml/min versus 85 mL/min). The peripheral volume was higher in the present study (34.9 L when estimated from all data, or 17.9 L when estimated from 0–48 h data, versus 12.6 L), which resulted in a longer half-life. This discrepancy could be explained by (i) differences in the values of some unknown covariate of VP between the two populations, (ii) differences in the distribution of sampling times between the two populations (there were more steady-state samples in the present study) and (iii) differences in the estimation methods applied.

The design of the study demonstrated that isepamicin concentrations were proportional to the dosages between 15 and 25 mg/kg. Since the previous population study had demonstrated proportionality between 7.5 and 15 mg/kg, it can be concluded that isepamicin kinetics are linear with respect to dosages in the range 7.5–25 mg/kg.

The problem of the invariance of isepamicin pharmacokinetic parameters over the duration of treatment was also addressed, because some reports22 showed that the volume of distribution Vß of aminoglycosides decreased during treatment of the infection. In our study, comparisons of the typical value of each pharmacokinetic parameter in the patients treated for 5 days versus those treated for 10 days showed no significant difference, and the ratio of the typical values was close to one. Although these comparisons were not very powerful, this test supported the view that isepamicin mean parameters could be regarded as similar at day 5 and day 10. Therefore, all data were combined to assess time-invariance of isepamicin individual parameters, by comparison of the parameters estimated from the data of 0–48 h with those estimated from the complete data in each individual. This comparison, which was more powerful than the former because it was within individuals and assessed a larger time gap, demonstrated an apparent increase by a factor of 2 in isepamicin VP between day 2 and day 5 or 10, which may represent the accumulation of isepamicin in a deep compartment. However, this apparent increase might also be artefactual. Indeed, it was shown23 that isepamicin elimination kinetics was triexponential, but in our analysis, a three-compartment model could not be fitted to the data. Therefore, it is conceivable that the {alpha} and ß half-lives estimated by fitting the two-compartment model were in fact intermediate values between the true {alpha}-ß and {gamma} half-lives. From a clinical point of view the simulations that we carried out demonstrated that doubling VP had a negligible impact on the predicted accumulation of isepamicin at steady state.

A number of pharmacokinetic indices were tentatively correlated with clinical outcome. These pharmacokinetic indices were first peak serum concentration, steady-state peak, 0–24 h area under the curve on day 1, 0–24 h area under the curve at steady state and, when the MIC was known, the ratio of these quantities to MIC. The choice of these indices was based on (i) the inverse relationship between the MIC for the infective organism in vitro and the response to aminoglycoside therapy,4 (ii) the significant correlations demonstrated earlier 5 between clinical outcome and five pharmacokinetic indices, and (iii) the strong association between elevated maximal and mean peak aminoglycoside concentration/MIC ratios with clinical response.6 Since it was shown that severity of the underlying illness and/or life expectancy without infection was a major factor associated with response to aminoglycoside therapy,6 the MacCabe score and the SAP score were also considered in the analyses. The site of infection was also shown to be related to clinical outcome,5,6 but this factor was not relevant in our study since all patients had pneumonia. Finally, in the study by Moore et al.,6 infection by P. aeruginosa was an additional factor related to clinical failure. However, aminoglycosides were combined with other antibiotics which were inactive against P. aeruginosa. In contrast, in our study, isepamicin was combined with a broad-spectrum ß-lactam and/or a glycopeptide so that isepamicin was unlikely to be the only antibiotic active against the infective organism. Hence, the nature of the infective organism was not retained in the analysis.

The results of our analyses showed no significant differences between the pharmacokinetic indices and gravity scores of the patients per protocol in whom treatment failed or succeeded. This result seems to contradict earlier studies. However, there were obviously many confounding factors in our study regarding the relationship between isepamicin pharmacokinetic indices and clinical outcome. First, success might have been observed in spite of a low isepamicin peak to MIC or AUC to MIC ratio because the strain was sensitive to the other antibiotics. Secondly, failure might have been observed in spite of a high isepamicin peak to MIC or AUC to MIC ratio because the patient died from its underlying disease. Thirdly, an infective organism may not have been identified in some patients, such as anaerobes or fungi. In spite of these limitations, it is also possible that no association between pharmacokinetic indices and clinical outcome was observed because isepamicin concentrations were so high or the combination with other antibiotics so strong, that the maximal efficacy (from a microbiological point of view) was reached. The arguments supporting this view are (i) the median isepamicin peak to MIC ratio in the patients with a sensitive strain was approximately 35, (ii) the median isepamicin AUCss to MIC ratio in the same patients was approximately 280 and (iii) the area under bactericidal titre versus time curve (AUBC) of a combination of antibiotics is the sum of the AUBCs of these antibiotics if the association is additive. Moore6 showed that the maximal efficacy was reached when the peak/MIC ratio was >10, and when the aminoglycosides were given three times daily. How should we take into account the difference in dosing interval? If we consider that the primary pharmacokinetic index correlated with aminoglycoside efficacy is their AUC,8 and if adaptive resistance is neglected, then bacterial killing is approximately equivalent when the same total daily dose is given, regardless of the number of administrations per day. For the peak to be correlated with efficacy, its value has to be normalized with respect to the number of administrations per 24 h: a peak/MIC equal to 30 od should have approximately the same efficacy as a peak/MIC equal to 10 repeated three times a day. Adaptive resistance, which is less pronounced in a once daily dosing regimen,24 results however, in a somewhat better efficacy of the once daily regimen so that the maximal efficacy is reached for lower values of the peak/MIC ratio. Therefore, the median peak to MIC ratio of 35 that we observed is in favour of a maximal effect being reached in most patients. If we turn back to AUC/MIC ratios, it has been postulated that, similarly to fluoroquinolones,25 a ratio >250 is associated with maximal efficacy.26 Again, the median AUC/MIC ratio of 280 observed in our patients supports the hypothesis of a maximal effect being reached in patients infected with a sensitive strain. This is the reason that we examined the values of the pharmacokinetic indices in the patients with a strain resistant to isepamicin. Unfortunately, the MIC had not been determined in all cases. In spite of this limitation, a trend emerged toward lower index values in clinical failure. Moreover, if we fix a MIC value to 16 mg/L (the upper breakpoint value), the median Peak 1ss/MIC and AUCss/ MIC ratios are less than 2.5 and 12, respectively, in the two patients with failure. As regards the AUBC, its value is roughly equivalent to AUIC,27 so that the AUBC value for the combination of the aminoglycoside and the ß-lactam is equal to the sum of their AUIC values, or even more if the combination is synergic. In our study, the AUBC values for strains sensitive to both antibiotics were therefore >=250. Finally, the hypothesis of the maximal effect being reached could explain that no difference of efficacy was found between the patients receiving a loading dosage of 25 mg/kg and those receiving only 15 mg/kg on day 1.

A practical consequence of these findings is that isepamicin peak concentration measurement should be of little interest for therapeutic drug monitoring, when isepamicin is given (i) in combination with a broad-spectrum antibiotic, (ii) at a dosage of 15 mg/kg or higher od and (iii) to immunocompetent patients.

Individual pharmacokinetic indices were also tentatively correlated with surrogate markers of renal failure, namely serum creatinine increase or creatinine clearance decrease. These markers are neither very specific of nephrotoxicity nor very sensible, but other markers are not generally available. Likewise, different results could have been found if patients with severe renal impairment had been enrolled. Finally, the occurrence of increased serum creatinine was infrequent (12.5%). The stronger correlation was between isepamicin residual concentration C24 and serum creatinine variation between day 1 and day 5. Use of the corresponding relationship showed that a 24 h trough level equal to 8 mg/L on day 1 was associated with an increase of 10 µM in serum creatinine level on day 5. The weak correlation is not surprising, since there are many pathological factors contributing to the development of renal failure in ICU patients.28 Conversely, it is interesting to note that in contrast to previous studies,10 age and high initial level of serum creatinine were not associated with a greater risk of developing renal impairment. Therefore, in our study, a high initial trough level of isepamicin was (retrospectively) an independent factor of development of a rise in serum creatinine level. A similar conclusion had been reached by Schentag et al.9 However, it should not be inferred that monitoring serum isepamicin concentrations will result in a lower incidence of nephrotoxicity. Flint 29 showed in a prospective study that aminoglycoside monitoring neither prevented nor predicted nephrotoxicity. Another argument invoked to support aminoglycoside monitoring is that the trough concentration of aminoglycosides changes more rapidly than does serum creatinine. However, in ICU patients with normal renal function, isepamicin half-life is two-to three-times higher than that of creatinine. Therefore, creatinine level will change more quickly than isepamicin level when renal function will vary.

Finally, the results of our study support the concept that the maximal antimicrobial effect is reached when isepamicin is given at 15 mg/kg od for 5 days combined with a broad-spectrum ß-lactam in immunocompetent ICU patients in order to treat a sensitive strain. Clinical failure is not associated with low isepamicin concentration, but rather with the underlying disease, and peak monitoring seems unwarranted. Serum creatinine increase was retrospectively associated with isepamicin trough concentration on day 1, but the correlation was weak and the rate of renal impairment was low, owing to the short duration of isepamicin treatment. Therefore, relevance and clinical interest of monitoring of isepamicin trough level remain speculative. Isepamicin monitoring could be of interest only when patients are immunosuppressed, or likely to be treated for >10 days, or the MIC for the causative strain is in the intermediate range (8–16 mg/L). Target concentrations could be higher than 48 mg/L for the peak (i.e. six times the lower breakpoint) and <5 mg/L for C24 (to ensure an expected rise in serum creatinine of less than 10 µM).


    Notes
 
Corresponding author. Tel: +33-1-48-95-56-61; Fax: +33-1-48-95-56-59; E-mail: michel.tod{at}avc.ap-hop-paris.fr Back


    References
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
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Received 25 March 1998; returned 17 August 1998; revised 18 September 1998; accepted 19 February 1999





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