Gatifloxacin and the elderly: pharmacokinetic–pharmacodynamic rationale for a potential age-related dose reduction

Paul G. Ambrose1,2,*, Sujata M. Bhavnani1,3, Brenda B. Cirincione1, Marion Piedmonte1 and Thaddeus H. Grasela1,3

1 Division of Infectious Diseases, Cognigen Corporation, Buffalo, 395 Youngs Road, Buffalo, NY 14221–5831; 2 University of the Pacific, School of Health Sciences, Stockton, CA; 3 School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA

Received 3 December 2002; returned 26 February 2003; revised 30 May 2003; accepted 16 June 2003


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion and conclusions
 References
 
Objectives: Recently, anecdotal reports via the FDA’s MedWatch reporting system have documented rare but serious hyperglycaemia in elderly patients receiving gatifloxacin. One possible factor contributing to these events may be gatifloxacin overexposure, resulting from age-related decreases in renal function in elderly patients predisposed to glycaemic alterations. These analyses examine gatifloxacin exposure in 10 patients with severe hyperglycaemia, provide a pharmacokinetic–pharmacodynamic (PK-PD) rationale for a potential age-related dose reduction to avoid high exposures, and evaluate the likely impact of such a dose reduction on clinical efficacy in this specific patient population.

Methods: First, a previously derived population pharmacokinetic model, with patient demographics, was used to estimate gatifloxacin AUC0–24 following a dosage regimen of 400 mg/24 h in 10 index patients with severe hyperglycaemia. Second, the population pharmacokinetic model and patient demographic data from 2696 patients aged >=65 years from two New Drug Application (NDA) databases were used to estimate AUC0–24 following dosage regimens for gatifloxacin of 200 and 400 mg/24 h. Finally, Monte Carlo simulation was utilized to assess the probability of achieving PK-PD target exposures against Streptococcus pneumoniae in elderly patients using these regimens.

Results: The mean estimated AUC0–24 among severe hyperglycaemia cases was 74 mg•h/L (range 57–100). Gatifloxacin AUC0–24 exposures for the 400 mg regimen were predicted to be higher in patients aged >=65 years and similar to the severe hyperglycaemia cases. The probability of AUC0–24 >=60 and >=70 in patients aged >=65 years for the 200 mg regimen was 0.03 and <0.01, respectively, versus 0.51 and 0.35 for the 400 mg regimen, respectively. The probability of achieving PK-PD target exposures against S. pneumoniae in patients aged >=65 years receiving the 200 mg regimen was 0.99.

Conclusions: The probability of a patient aged >=65 years having an AUC0–24 >=60–70 mg•h/L is markedly lower following a 200 mg regimen relative to a 400 mg regimen, suggesting a decreased risk of severe hyperglycaemia in a predisposed patient. Moreover, a dose reduction does not appear to significantly modify the likelihood of achieving the PK-PD target of gatifloxacin against S. pneumoniae.

Keywords: hyperglycaemia, pharmacokinetic model, fluoroquinolones


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion and conclusions
 References
 
Gatifloxacin is a fourth-generation fluoroquinolone antibacterial that has been shown to be safe and efficacious for the treatment of community-acquired respiratory tract infections, including pneumonia, acute bacterial exacerbations of chronic bronchitis and acute bacterial rhinosinusitis.14 Since it was introduced into clinical practice in 2000, gatifloxacin use has increased steadily in both the hospital and community settings, and is now used widely for the treatment of young and elderly patients alike (over 14 million patients worldwide).

Recently, anecdotal reports via the Food and Drug Administration’s (FDA’s) MedWatch reporting system have documented rare but serious cases of hyperglycaemia in elderly patients receiving standard dosage regimens of gatifloxacin 400 mg/day. One factor possibly involved in these events may be gatifloxacin overexposure, resulting from age-related decreases in renal function in elderly patients predisposed to glycaemic alterations. It is well established that renal function decreases with age and that differences in physiology between young and elderly patients affect the pharmacokinetics–pharmacodynamics (PK-PD) of drugs.5,6 Since gatifloxacin is eliminated primarily via renal excretion,7 it is likely that age-related changes in pharmacokinetic parameters, such as clearance, would be expected.

The purposes of these analyses were four-fold: (i) to characterize the range of exposures, as measured by the area under the serum concentration–time curve at 24 h (AUC0–24), associated with a dosage of 400 mg/24 h in patients with severe hyperglycaemia; (ii) to use a previously derived population pharmacokinetic model to predict AUC0–24 following dosage regimens of 400 and 200 mg/24 h in elderly patients from two New Drug Application (NDA) databases; (iii) to examine the range of AUC0–24 values among elderly patients, and the probability of obtaining AUC0–24 values similar to patients with severe hyperglycaemia using dosage regimens of 400 and 200 mg/24 h; and (iv) to utilize Monte Carlo simulation to assess the probability of elderly patients achieving optimal PK-PD target exposures [AUC0–24:minimum inhibitory concentration (MIC) ratio >=30] for community-acquired respiratory tract infection involving Streptococcus pneumoniae using these regimens.


    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion and conclusions
 References
 
A schematic of the analysis plan is presented in Figure 1 and discussed sequentially below.



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Figure 1. Analysis flowchart.

 
Pharmacostatistical model

The population pharmacokinetic model for gatifloxacin was derived from a Phase III study designed to assess the safety and efficacy of gatifloxacin 400 mg/24 h versus levofloxacin 500 mg/24 h for the treatment of community-acquired pneumonia.8 The study drug was administered either orally or intravenously as a 1 h infusion. At the investigator’s discretion, patients received either oral therapy alone, or intravenous therapy followed by oral therapy.

In brief, 111 gatifloxacin blood concentrations collected from 67 patients were available for model development. Two blood samples were collected between days 2 and 4, the first taken on arrival at the clinic prior to the dose, and the second taken 2 h post-dose. If the patient could not wait 2 h for the second sample to be collected, only the first was collected. However, the majority of patients had two samples collected (66%). The demographics of these 67 patients were (mean ± S.D.): age 50 ± 17 years, serum creatinine 0.81 ± 0.21 mg/dL, weight 82.5 ± 19.1 kg and estimated creatinine clearance 91.0 ± 30.3 mL/min. A one-compartment model, with first order absorption and elimination, was fitted to the data, resulting in the following equation for the prediction of gatifloxacin clearance in this Phase III patient population:


(1)

where

is the typical value of clearance in L/h for the jth patient, CrClj is estimated creatinine clearance for the jth patient in mL/min and Wt is weight in kg for the jth patient. The following exponential error model described the inter-individual variability in Cl:


(2)

where {eta}j(Cl) is the persistent difference between the true value of the Cl parameter in the jth patient and the predicted value; the {eta}j(Cl) are independent, identically distributed statistical errors with a mean of zero and a variance equal to {omega}2x. The population mean {eta}Cl expressed as %CV was 22.18 for these data.

The predictive performance of this model, stratified by patient age (<=60 versus >60 years), was evaluated by examining summary statistics of the population mean prediction errors and absolute population mean prediction errors. The relationships between Bayesian-estimated and model-predicted clearance, stratified by patient age (<=60 versus >60 years), were evaluated graphically.

Patient demographic data

For 10 patients with severe hyperglycaemia, demographic data collected via the FDA’s MedWatch reporting form, in conjunction with additional data from the reporting clinician, were used to calculate predicted clearance and AUC0–24 for gatifloxacin. Rather than using simulation techniques to describe a population of elderly patients, two NDA (gatifloxacin and garenoxacin) databases were queried, irrespective of study drug administration, for demographic data required for calculating gatifloxacin model-predicted clearance and AUC0–24 after dosage regimens of 200 and 400 mg/24 h.

Monte Carlo simulation

Simulations were carried out to assess the probability of attaining the PK-PD target (AUC0–24:MIC >= 30) for gatifloxacin at doses of 400 and 200 mg once daily against S. pneumoniae. Demographic information from the gatifloxacin and garenoxacin NDA databases was used in conjunction with equations 1 and 2 to predict population clearance and AUC0–24. Simulations utilized equation 3, and microbiological susceptibility data for gatifloxacin against S. pneumoniae from the SENTRY Antimicrobial Surveillance Program, which is described in greater detail below. The planned simulation size was 5000 patients. Sensitivity analyses were carried out to determine which input variable (pharmacokinetic data, microbiological susceptibility data) contributed most strongly to the output variable (AUC0-24:MIC ratio).

AUC0–24:MIC = (Dose/Clj)/MIC (3)

To estimate the accuracy of each 5000 patient simulation, the mean, S.D. and percentile error around the PK-PD target was calculated with 95% confidence interval.

Microbiological surveillance data

For the purpose of estimating the MIC distribution of S. pneumoniae, longitudinal data from 1997–2000 were obtained from the SENTRY Antimicrobial Surveillance Program.9 In brief, the species identity of all isolates was confirmed by the reference laboratory (University of Iowa College of Medicine) on the basis of Gram stains and colony morphology, pattern of growth on sheep blood and enriched chocolate agars, catalase reactivity and results of the sodium deoxycholate solubility tests. Gatifloxacin powder for susceptibility testing was obtained from the Bristol-Myers Squibb Company, and dispensed into dry-form broth microdilution trays (from MicroScan in 1997; from TREK/Sensititre in 1998–2000). MIC values were determined using a broth microdilution method, as described by the NCCLS.10 Trays were incubated in ambient air at 35–37°C for 20–24 h before visual determination of MIC values. A final inoculum concentration of ~5 x 105 cfu/mL was used and confirmed by colony counts. The medium used was Mueller–Hinton broth plus 3%–5% lysed horse blood. Daily quality control testing was conducted with S. pneumoniae ATCC 49619. The interpretation of results was directed by the current NCCLS standards.11


    Results
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion and conclusions
 References
 
Of the 67 patients in the Phase III population pharmacokinetic model development dataset, 24 were aged >60 years. Summary statistics of the population errors were evaluated as a measure of bias in the prediction of the gatifloxacin concentrations collected from the Phase III patient population. When stratified by age, there was a small amount of bias in the predictions as the model tended to over-predict the patients aged <=60 years (mean prediction error = –7.42%) and under-predict the patients aged >60 years (mean prediction error 14.68%). However, the precision of the estimates was comparable for both age cohorts, 28.33% and 30.19% for patients <=60 and >60 years, respectively. The small prediction error and reasonable precision found in both age cohorts indicates acceptable model performance in the aged population. The summary statistics for the precision and bias parameters are shown in Table 1.


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Table 1. Summary for the measures of bias and precision stratified by age
 
The magnitude of the inter-individual variability, as measured by coefficient of variation, in clearance for this Phase III population was 22.18%. This variability provides a measure of the persistent difference between the true and predicted clearance value for each patient. By utilizing the post hoc option in NONMEM (Nonlinear Mixed Effects Modeling Software), empirical Bayesian estimates of clearance were obtained that were conditional not only on the data, but also on the population mean parameter estimates and estimates of IIV. In order to provide a visual assessment of both the variability in true clearance at any given model-predicted clearance, and the amount of potential deviation from the mean predicted clearance, the relationship between Bayesian-estimated and model-predicted clearance, stratified by patient age, is presented in Figure 2.



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Figure 2. Plot of Bayesian-estimated versus model-predicted clearance stratified by young (<=60 years) versus elderly patients (>60 years).

 
Demographics and model-predicted AUC0–24 for patients with severe hyperglycaemia, identified in the FDA’s MedWatch database, is presented in Table 2. Of the 10 patients, four had a history of diabetes mellitus. The mean age of the 10 patients was 80 years (range, 53–98), with eight of 10 patients 74 years or older. For two patients, dosage information was not confirmed but was assumed to be 400 mg/24 h for the purpose of estimation of gatifloxacin exposure. When serum creatinine or weight was unknown, as in two and six instances, respectively, it was assumed that serum creatinine was 1.0 mg/dL and weight was 70 kg. The mean predicted AUC0–24 among these 10 patients with severe hyperglycaemia was 74 mg•h/L (range, 57–100).


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Table 2. Demographics and model-predicted AUC0–24 for patients with severe hyperglycaemia identified in the FDA’s MedWatch database
 
Summary statistics describing Bayesian-estimated AUC0–24 for all patients included in the population pharmacokinetic development dataset were: median, 46.50 mg•h/L; range, 29.59–98.22 mg•h/L; and 25th and 75th percentiles, 40.62 and 59.00 mg•h/L, respectively. For the subset of 24 patients >60 years, the summary statistics describing Bayesian-estimated AUC0–24 were: median, 62.25 mg•h/L; range, 37.84–98.22 mg•h/L; and 25th and 75th percentiles, 48.84 and 66.90 mg•h/L, respectively. Across the NDA databases for gatifloxacin and garenoxacin, there were a total of 2696 patients 65 years or older. Summary statistics describing model-predicted AUC0–24 for these patients were: median, 60.32 mg•h/L; range, 15.71–170.29 mg•h/L; and 25th and 75th percentiles, 50.45 and 72.89 mg•h/L, respectively.

Among the 6700 strains of S. pneumoniae collected in North America from the SENTRY Antimicrobial Surveillance Program (1997–2000), the MIC50 and MIC90 of gatifloxacin were 0.25 and 0.5 mg/L, respectively. The percentage of strains susceptible at the NCCLS breakpoint (1.0 mg/L) was 99.6%.

Tables 3 and 4 show the results of the Monte Carlo simulation. As expected, the percentage of patients with predicted gatifloxacin AUC0–24 greater than or equal to either 60 or 70 mg•h/L increased with age. Moreover, as expected, the probability of attaining AUC0–24 >=60 or 70 mg•h/L was markedly higher for the 400 mg regimen relative to the 200 mg regimen. For instance, for patients aged 65 years or greater, the percentage attaining an AUC0–24 >=70 for each regimen was 0.92 and 35, respectively (Table 3). These differences represent a 38-fold lower risk of attaining a gatifloxacin AUC0–24 >=70 mg•h/L for the 200 mg versus the 400 mg dosage regimen. Overall, the percentage of patients achieving an AUC0–24:MIC ratio of at least 30 was similar for the 200 mg compared with the 400 mg dosage regimen (Table 4). For instance, for patients 65 years or greater, the probability of attaining an AUC0–24:MIC ratio of at least 30 was 0.989 and 0.995 for the 200 and 400 mg dosage regimens, respectively.


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Table 3. Monte Carlo simulation results: percentage of patients attaining a given AUC0–24 stratified by age cohort and gatifloxacin dosage regimen.
 

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Table 4. Monte Carlo simulation results: percentage of patients attaining PK-PD target stratified by age cohort and gatifloxacin dosage regimen.
 

    Discussion and conclusions
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion and conclusions
 References
 
One underlying assumption of the current analyses is that an exposure–response relationship exists between the drug and hyperglycaemia. Maeda et al.12 proposed increasing insulin release via blockade of ATP-sensitive potassium channels in pancreatic ß cells as a mechanism for fluoroquinolone-associated hypoglycaemia. Until recently, similar data describing a mechanism for hyperglycaemia had been lacking. Although data in human subjects is not yet available describing the effect of fluoroquinolones on pancreatic ß cell function, in vitro data from a hamster pancreatic ß cell line model (HIT-15) for gatifloxacin, moxifloxacin, lomefloxacin, levofloxacin and ciprofloxacin is available. These data show a dose-related decrease in insulin release from ß cells in response to a glucose challenge after 7 days of exposure to a fluoroquinolone. These data are supportive of the current analysis that contends that hyperglycaemia may be the result of high drug exposures. (Personal communication, Susan Nicolson, Bristol-Myers Squibb Company.) These data are further supported by empirical evidence, namely that these severe cases of hyperglycaemia occurred in patients at risk for increased drug exposure caused by age-related decreases in renal function. Additional data are needed to describe this exposure–response relationship further.

The limitations of spontaneous adverse event reporting have been well documented in the literature.13 The current analyses are limited by the information reported, and it proved difficult to obtain additional case details from the reporting clinicians. In some instances, prediction of individual gatifloxacin exposure in those patients with severe hyperglycaemia was difficult because of incomplete demographic and laboratory information. Thus, estimation of gatifloxacin exposures associated with these clinical cases was limited. Although we cannot predict with great confidence each patient’s specific drug exposure, these data do support the conclusion that the exposures were generally large, especially when compared with healthy volunteers or infected patient cohorts described in the product label.14

Regardless of these limitations, these analyses, as expected, did demonstrate a significantly decreased probability of higher drug exposures associated with a 200 mg dose relative to a 400 mg dose in elderly patients. Whereas we can quantify the risk reduction of patients aged 65 years or greater having an AUC0–24 above a given threshold, we cannot quantify the risk reduction in terms of hyperglycaemia. Since it is likely that this adverse event is exposure-related and has been observed in elderly patients with decreased drug clearance, it is reasonable to suggest that a dose reduction in this patient population will result in a decreased risk of severe hyperglycaemia in a predisposed patient.

The PK-PD of fluoroquinolone antimicrobial agents has been well defined. These agents have concentration-dependent bactericidal effects and the AUC0–24:MIC ratio generally has the strongest correlation with outcome in non-clinical models of infection.1517 Current clinical data indicate that the PK-PD goal of therapy for Gram-positive microorganisms is different from Gram-negative microorganisms. Forrest et al.18 demonstrated that for ciprofloxacin against enteric Gram-negative pathogens and Pseudomonas aeruginosa, an AUC0–24:MIC ratio of at least 125 was associated with the highest therapeutic response rates in hospitalized patients with serious infections. Alternatively, we have demonstrated that for patients with community-acquired respiratory tract infections involving S. pneumoniae enrolled in Phase III clinical trials involving gatifloxacin or levofloxacin, an AUC0–24:MIC ratio of at least 33.7 correlated with optimal microbiological response rates.19

The probability of attaining the PK-PD AUC0–24:MIC ratio breakpoint of 30 in the present analyses was high, essentially 0.99, for the dosage regimens 200 and 400 mg/24 h in patients aged >=65 years regardless of age cohort. These observations are similar to other published reports involving younger patient cohorts, which have examined the PK-PD target attainment of gatifloxacin dosed on a 400 mg/24 h schedule against S. pneumoniae.20 Based upon these observations, it may be reasonable to suggest that a daily dose reduction from 400 to 200 mg in this patient population would have minimal impact on the therapeutic outcome of community-acquired infections involving S. pneumoniae. A dose adjustment at 65 or 70 years generally results in drug exposures consistent with current FDA labelling for this compound, which recommends dose adjustment from 400 to 200 mg/day for patients with calculated creatinine clearance values of 40 mL/min or less.14 Since this drug is used primarily on an outpatient basis and because it is not generally standard practice in the community setting for clinicians to order serum chemistry panels to estimate renal function, recommendation for a dose adjustment based upon age may be viewed as advantageous, from the clinician and outpatient perspective alike. However, it is important to remember that as the MIC value increases, the probability of attaining the PK-PD breakpoint decreases, and it is unlikely that a regimen of 200 mg/24 h would cover pneumococcal isolates at the upper margins of the MIC distribution. At the present time, these isolates are rare, as evidenced by the microbiological surveillance data utilized in these simulations, where only 0.4% of isolates had MIC values >1.0 mg/L. Additional analyses may be warranted as the MIC distribution of S. pneumoniae changes over time. Another important consideration is the impact of changes in the AUC distribution, arising from a dose reduction in this patient population on the emergence of pneumococcal resistance. To date, a minimally effective PK-PD target is only beginning to be defined for preventing the emergence of pneumococcal resistance. At this point, there are few data to suggest that such a change in AUC distribution in this patient population would have a negative or positive impact on the emergence of resistant pneumococci, especially given that the dose adjustment described herein results in AUC distributions more similar to the entire patient population.

We feel that data such as these are necessary and sufficient for risk assessment and management efforts by clinicians and regulators to optimize safety and efficacy outcomes.


    Acknowledgements
 
This work was supported in part by a grant from Bristol-Myers Squibb.


    Footnotes
 
* Corresponding author. Tel: +1-716-633-3463, ext. 302; Fax: +1-716-633-7404; E-mail: paul.ambrose{at}cognigencorp.com Back


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion and conclusions
 References
 
1 . Fogerty, C., McAdoo, R. A. & Paster, R. Z. (1999). Gatifloxacin vs clarithromycin in the management of acute sinusitis. Journal of Respiratory Diseases 20, Suppl., S17–22.

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20 . Ambrose, P. G. & Grasela, D. M. (2000). The use of Monte Carlo simulation to examine pharmacodynamic variance of drugs: fluoroquinolone pharmacodynamics against Streptococcus pneumoniae. Diagnostic Microbiology and Infectious Disease 38, 151–7.[CrossRef][ISI][Medline]