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Antimicrobial Agents and Chemotherapy, November 1998, p. 2848-2852, Vol. 42, No. 11
0066-4804/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
MIC-Based Interspecies Prediction of the Antimicrobial Effects of
Ciprofloxacin on Bacteria of Different Susceptibilities in an In
Vitro Dynamic Model
Alexander A.
Firsov,1,*
Sergey N.
Vostrov,1
Alexander A.
Shevchenko,1
Stephen H.
Zinner,2
Giuseppe
Cornaglia,3 and
Yury
A.
Portnoy1
Department of Pharmacokinetics, Centre of
Science & Technology LekBioTech, Moscow,
Russia1;
Division of Infectious
Diseases, Department of Medicine, Brown University, Providence,
Rhode Island2; and
Institute of
Microbiology, University of Verona, Verona, Italy3
Received 30 January 1998/Returned for modification 7 March
1998/Accepted 12 August 1998
 |
ABSTRACT |
Multiple predictors of fluoroquinolone antimicrobial effects (AMEs)
are not usually examined simultaneously in most studies. To compare
the predictive potentials of the area under the concentration-time curve (AUC)-to-MIC ratio (AUC/MIC), the AUC above MIC
(AUCeff), and the time above MIC
(Teff), the kinetics of killing and regrowth of
four bacterial strains exposed to monoexponentially decreasing concentrations of ciprofloxacin were studied in an in vitro
dynamic model. The MICs of ciprofloxacin for clinical isolates of
Staphylococcus aureus, Escherichia coli
11775 (I) and 204 (II), and Pseudomonas aeruginosa were
0.6, 0.013, 0.08, and 0.15 µg/ml, respectively. The simulated values
of AUC were designed to provide similar 1,000-fold (S. aureus, E. coli I, and P. aeruginosa) or 2,000-fold (E. coli II) ranges of
the AUC/MIC. In each case except for the highest AUC/MIC ratio, the
observation periods included complete regrowth in the time-kill curve
studies. The AME was expressed by its intensity, IE (the area between the control growth and
time-kill and regrowth curves up to the point where the viable counts
of regrowing bacteria are close to the maximum values observed without
drug). For most AUC ranges the IE-AUC curves
were fitted by an Emax (maximal effect) model,
whereas the effects observed at very high AUCs were greater than those
predicted by the model. The AUCs that produced 50% of maximal AME were
proportional to the MICs for the strains studied, but maximal AMEs
(IEmax) and the extent of sigmoidicity (s) were not related to the MIC. Both
Teff and log AUC/MIC correlated well with
IE (r2 = 0.98 in both cases) in a species-independent fashion. Unlike Teff or log AUC/MIC, a specific relationship
between IE and log AUCeff was
inherent in each strain. Although each IE and
log AUCeff plot was fitted by linear regression
(r2 = 0.97 to 0.99), these plots were
not superimposed and therefore are bacterial species dependent. Thus,
AUC/MIC and Teff were better predictors of
ciprofloxacin's AME than AUCeff. This study suggests that
optimal predictors of the AME produced by a given quinolone (intraquinolone predictors) may be established by examining its AMEs
against bacteria of different susceptibilities.
Teff was shown previously also to be the best
interquinolone predictor, but unlike AUC/MIC, it cannot be used to
compare different quinolones. AUC/MIC might be the best predictor of
the AME in comparisons of different quinolones.
| |
INTRODUCTION |
Several predictors of the
antimicrobial effect, including the ratio of the area under the
concentration-time curve (AUC) to MIC (AUC/MIC), AUC above MIC
(AUCeff), time above MIC
(Teff), etc., have been examined in many studies
published during the last decade (2, 3, 12, 14-18).
Practical recommendations for rational antibiotic dosing derived from
these studies have generally been accepted, despite some reported
contradictions among actual comparisons of the predictors. We recently
analyzed possible reasons for conflicting reports on some predictors of fluoroquinolone antimicrobial effects, including AUC/MIC,
AUCeff, and Teff (10).
Based on findings obtained with ciprofloxacin and trovafloxacin in our
in vitro dynamic model and on the data reported by other investigators,
we showed that the use of (i) inadequate experimental designs, (ii)
inappropriately combined data with different quinolones and dosing
regimens, and (iii) suboptimal quantitation of the effect itself all
have contributed to this controversy.
We have suggested that it is useful to distinguish between intra- and
interquinolone predictors of the antimicrobial effect. The
intraquinolone predictors (AUC/MIC, AUCeff, and
Teff) may be used to predict the effects of a
given drug administered at various doses. The interquinolone predictor
(Teff) predicts the effect of one quinolone
based on the predictor-response relationship established with another
quinolone (10). This in vitro study was performed with
pharmacokinetically different quinolones and discriminated between
inter- and intraquinolone predictors. However, it did not discriminate
among the several intraquinolone predictors, possibly because the
bacterial strains studied had similar susceptibilities to the tested
drugs. To verify this hypothesis, we examined the relative value of
AUC/MIC, AUCeff, and Teff as
intraquinolone predictors of the antimicrobial effect of ciprofloxacin
on differentially susceptible bacteria.
| |
MATERIALS AND METHODS |
Antimicrobial agent.
Ciprofloxacin lactate powder, kindly
provided by Bayer AG, was used in the study. Stock solutions of the
quinolone were prepared in sterile distilled water.
Bacterial strains.
The clinical isolates of
Staphylococcus aureus 452, Escherichia coli 11775 (I) and 204 (II), and Pseudomonas aeruginosa 48 were used in
the study. Susceptibility testing was performed in duplicate in
Ca2+- and Mg2+-supplemented Mueller-Hinton
broth at an inoculum size of 106 CFU/ml at 24 h
postexposure. The MICs for S. aureus, E. coli I and II, and P. aeruginosa were 0.6, 0.013, 0.08, and 0.15 µg/ml, respectively.
Simulated pharmacokinetic profiles.
A series of
monoexponential profiles mimicking the single-dose pharmacokinetics of
ciprofloxacin were simulated. The simulated half-life
(t1/2) of 4 h was consistent with values
reported in humans: 3.2 to 5.0 h (1, 13, 19).
Regardless of the bacterial strain, the simulated initial
concentrations of ciprofloxacin were designed to provide similar
1,000-fold ranges of the AUC/MIC for S. aureus,
E. coli I, and P. aeruginosa and a
2,000-fold range for E. coli II. In each case the
highest AUC/MIC provided complete bacterial killing with no regrowth.
The respective AUC ranges in the experiments with S. aureus, E. coli I and II, and P. aeruginosa were 4.6 to 4474, 0.09 to 93.1, 0.6 to 1,143, and 1.1 to 1,119 µg · h/ml.
In vitro dynamic model and operating procedure.
A previously
described dynamic model (11) was used in the study. Briefly,
the model consists of two connected flasks, one containing fresh
Ca2+- and Mg2+-supplemented Mueller-Hinton
broth and the other, the central unit, containing the same broth plus a
bacterial culture (control growth experiments) or a bacterial culture
plus antibiotic (killing and regrowth experiments). The central unit is
incubated at 37°C in a shaking water bath. Peristaltic pumps
(Minipuls 2; Gilson) circulate fresh nutrient medium to the
bacterium-containing or bacterium- and antibiotic-containing medium and
from the central 40-ml unit at a flow rate of 7 ml/h to simulate
ciprofloxacin pharmacokinetics. Hence, the clearance provided by the
designed flow rate plus the volume of the central unit ensure
monoexponential elimination of ciprofloxacin and bacteria from the
system with an elimination rate constant of 0.17 h
1
(t1/2 = 4 h). Accurate simulations of the
desired pharmacokinetic profiles are provided by maintaining constant
flow rates and a constant volume of the central unit. Validation of the
model by the determination of ciprofloxacin concentrations showed no
systematic deviation of the observed values from the expected ones
(10).
The system is filled with sterile Mueller-Hinton broth and is placed in
a temperature-regulated incubator at 37°C. The central unit is
inoculated with 18-h cultures of S. aureus,
E. coli I or II, or P. aeruginosa, and after
a further 2-h incubation, ciprofloxacin is injected into the central
unit. The resulting exponentially growing cultures approach
approximately 106 CFU/ml. The duration of the experiments
is defined in each case as the time until the antibiotic-exposed
bacteria (NA) reach the maximum numbers observed
in the absence of antibiotic (control growth
[NC]), i.e., the time when
NA becomes equal to NC.
In all cases experiments are stopped when NA
reaches 
1011 CFU/ml. Since the experiments that simulate
low AUC/MIC ratios meet this requirement earlier than those that
simulate high AUC/MIC, the duration of the former experiments is
shorter than the latter: the lower the AUC/MIC ratio, the shorter the
observation period.
Quantitation of bacterial growth and killing.
In each
experiment 0.1-ml samples are withdrawn from the bacterium-containing
media in the central unit throughout the observation period, at first
every 30 min, later hourly, then every 3 h, and, during the last 6 to 7 h, again hourly. These samples are subjected to serial
10-fold dilutions with chilled, sterile 0.9% NaCl and are plated in
duplicate on Mueller-Hinton agar. Antibiotic carryover at low counts is
avoided by washing the bacteria with 0.9% NaCl. After overnight
incubation at 37°C the resulting bacterial colonies are counted, and
the numbers of CFU per milliliter are calculated. The lower limit of
accurate detection is 102 CFU/ml. High within-day and
interday reproducibilities of the results have been reported previously
(10).
To reveal possible changes in susceptibility, the quinolone
concentrations (
Cregrowth) that correspond to
the time when numbers
of surviving organisms in the regrowth curves
reached the level
of the initial inoculum were determined in each run
(
9). The
AUC/MIC-induced systematic increase in the
Cregrowth that might
relate to resistance was
observed only with
E. coli II at the
two highest AUCs
(143 and 571 µg · h/ml). Therefore, only negligible
changes in
the susceptibilities of the ciprofloxacin-exposed bacteria
were
assumed. Moreover, the appearance of regrowth of all four
microorganisms was associated with ratios of the quinolone
concentration
to the MIC of unity. These data are consistent with
previous findings
of unchanged susceptibility of bacteria exposed to
single doses
of five fluoroquinolones in an in vitro dynamic model
(
20).
Quantitative evaluation of the antimicrobial effect and
comparison of its predictors.
The antimicrobial effect was
expressed by its intensity (IE), which describes
the area between control growth and bacterial killing and regrowth
curves from the zero point, the moment of drug input into the model, up
to the time when viable counts on the regrowth curve are close to the
maximum values observed without drug (8). The upper limit of
bacterial numbers in the regrowth and control growth curves and the
lower limit in the time-kill curve used to determine the
IE were 1011 CFU/ml (11)
and 10 CFU/ml (the theoretical limit of detection), respectively. Also,
the time to reduce the initial inoculum 100-fold (N0) 
T99% (where
T99% is the time to reduce the starting
inoculum 100-fold) and the difference between logarithms of
N0 and the numbers of surviving organisms at
24 h (N
) 
log
N were calculated in each case, if applicable.
The
IE-AUC data sets obtained with each of the
strains studied were fitted by an
Emax model:
|
(1)
|
where
IEmax is the maximal value of
IE, AUC
50 is the AUC associated with
IEmax/2, and
s is a parameter
reflecting the degree of sigmoidicity which is equivalent to the
Hill
coefficient.
To compare the predictive potentials of AUC/MIC, AUC
eff,
and
Teff, the antimicrobial effects expressed by
IE were related
to each predictor for each
bacterial strain. Nonlinear regression
analysis of the
IE-AUC data by equation 1 as well as correlation
and regression analyses of the relationships between
IE and log
AUC/MIC, log AUC
eff, or
Teff were performed with STATISTICA software
(version 4.3; StatSoft, Inc.). Statistical comparison of the
regressions
was performed at
P equal to 0.05.
| |
RESULTS |
The time courses of viable counts that reflect killing and
regrowth of S. aureus, E. coli I and
II, and P. aeruginosa exposed to monoexponentially
decreasing concentrations of ciprofloxacin as well as the respective
control growth curves are shown in Fig. 1. At all AUCs except for the maximum
values, regrowth followed a considerable reduction in bacterial
numbers. The time shift of the regrowth phase to the right along the
time axis was distinctly dependent on the simulated AUC: the higher the
AUC, the later the regrowth. Regardless of the bacterial strain,
the appearance of bacterial regrowth was associated with ciprofloxacin
concentrations which were close to the respective MICs.
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FIG. 1.
Kinetics of killing and regrowth of different
microorganisms exposed to ciprofloxacin. The simulated AUCs (in
microgram · hours per milliliter) are indicated by the numbers
at each curve. The dotted line indicates the low limit of accurate
detection.
|
|
As seen in Fig. 2, for most AUC ranges,
the IE-AUC data obtained with each organism were
properly fitted by equation 1, although one to two points in each
IE-AUC plot systematically diverged from the
respective theoretical curve. This might be interpreted as evidence for
qualitative changes in drug-pathogen interactions at high AUCs
resulting in complete killing of bacteria (IE
approaches infinity at the highest AUCs). Parameters of the
Emax (maximal effect) model are presented in
Table 1. At least one of the model parameters, the AUC that produced 50% of maximal antimicrobial effects
(AUC50), was directly proportional to the MIC,
whereas no systematic relations could be established between MIC
and IEmax or s. Therefore,
regardless of the degree of sigmoidicity, saturation of the
antimicrobial effect was observed at comparable
IEs but at distinctly different AUCs.
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|
FIG. 2.
AUC-dependent antimicrobial effects of ciprofloxacin as
described by equation 1. The systematically diverging points are
crossed out.
|
|
Model-fitted IE-AUC curves were converted into
linear IE-log AUC plots for each of the strains
studied (data not shown). Despite striking contrasts between
IE-AUC curves that reflect ciprofloxacin's effects against different organisms, the IEs
plotted against MIC-corrected AUCs appeared to be bacterial species
independent. As seen in Fig. 3, the
IE-log AUC/MIC and
IE-Teff data obtained
with the four organisms were superimposed and fitted by the same linear regressions (r2 = 0.98 in both cases).
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|
FIG. 3.
Antimicrobial effects of ciprofloxacin related to the
different predictors.  , S. aureus;  ,
E. coli I;  , E. coli II;  ,
P. aeruginosa.
|
|
Unlike AUC/MIC and Teff, AUCeff
displayed MIC-dependent IE-log
AUCeff relationships for each of the strains studied. As
seen in Fig. 3, a specific relationship was inherent in each of them with reasonably high correlation coefficients. Statistically
significant differences were established between S. aureus and E. coli I and II or P. aeruginosa in terms of the intercepts but not the regression coefficients. Moreover, the intercepts were distinctly dependent on the
MICs: the higher the MIC, the lower the intercept. No differences were
found between similarly susceptible strains of E. coli
II or P. aeruginosa.
| |
DISCUSSION |
Regardless of the susceptibility to ciprofloxacin, all four
bacterial strains used in this study displayed qualitatively similar saturable relationships between the antimicrobial effect as expressed by its intensity and the AUC of the antibiotic. For most AUC ranges studied, the IE versus AUC data were fitted by
the Emax model. However, in each case the
IEs observed at high AUCs diverged
systematically from the model-predicted values. This limitation of the
model is quite expected, since the maximal value of
IE approaches infinity when no regrowth occurs,
and therefore, it should deviate from the plateau (Fig. 2). Among
three parameters of the Emax model, IEmax, s, and AUC50,
only the last one could be related to the MIC: the higher MIC,
the higher the AUC50.
This study suggests that intraquinolone predictors of the antimicrobial
effect, AUC/MIC, AUCeff, and Teff,
may be properly distinguished by examining them in terms of their
respective IE relationships established with
bacteria of different susceptibilities. Although all three predictors
covaried strongly for each organism taken separately, only log AUC/MIC
and Teff covaried for all four organisms taken
together (r2 > 0.99). Much looser
correlations were established between AUC/MIC and
AUCeff (r2 = 0.56) or
between Teff and log AUCeff
(r2 = 0.61). Based on the data
that were obtained, AUC/MIC and Teff were
better species-independent predictors of ciprofloxacin's effects than
AUCeff. Thus, the hypothesis formulated in the
introduction appears to be true, and the approach described may be a
reliable "test system" for selection of the optimal
predictor(s) of the antimicrobial effects produced by a given fluoroquinolone.
However, AUC/MIC and Teff cannot be considered
similarly acceptable for the comparison of different quinolones. As
reported earlier (10), unlike IE-log
AUC/MIC, the IE-Teff
relationships could not distinguish pharmacokinetically different
quinolones (ciprofloxacin and trovafloxacin) and the
IE-Teff relationships cannot be used to compare them. Therefore, AUC/MIC, but not
Teff or AUCeff, might be the most
reliable predictor of the antimicrobial effects in a comparison of
different quinolones. Recently, the effects of trovafloxacin and
ciprofloxacin (4, 6, 7) and gatifloxacin and ciprofloxacin
(5) were compared on the basis of the
IE-log AUC/MIC relationships established in in
vitro dynamic models. Results similar to those reported here were observed.
The results of predictor examinations may be highly dependent on the
endpoints used to quantitate the effect (10). In this study,
the use of the intensity of the antimicrobial effect as an endpoint
provided ultimate discrimination among AUCeff and AUC/MIC
or Teff. It should be noted that more
conventional endpoints, i.e., T99% and log
N, did not properly distinguish the three
predictors. As seen in Fig. 4, both
log N and, especially,
T99% show predictor-response relationships that
are much more erratic and scattered than those established with
IE. There is no correlation between
T99% and log AUC/MIC, log AUCeff,
or Teff (r2 = 0.01 to 0.02), and only weak correlations exist between each of the
three predictors and log N
(r2 = 0.34 to 0.59).
Moreover, log N could not be
determined precisely at low values of AUC/MIC,
AUCeff, and Teff. Also, there is a
tendency toward saturation of the effect expressed by log N at high values of AUC/MIC and
Teff. The latter phenomenon was shown to be
artificial and to misrepresent the true AUC-response relationship
(11).
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|
FIG. 4.
Antimicrobial effects of ciprofloxacin expressed by
T99% and log N as
related to the different predictors. The log
N values which were near the upper (log
N  5) and lower (log
N 6) limits of accurate detection and
which were therefore ignored in the correlation analysis are indicated
by filled symbols. , S. aureus; , E. coli I; , E. coli II; , P. aeruginosa.
|
|
Overall, this and other (10) studies suggest that
optimal intra- and interquinolone predictors as well as optimal
predictors of antimicrobial effects in comparisons of different
quinolones may be established in studies performed with in vitro
dynamic models. Knowledge of optimal predictors might be useful in
comparing new quinolone compounds in terms of their antimicrobial
effect-predictor relationships.
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Pharmacokinetics, Centre of Science & Technology LekBioTech,
8 Nauchny proezd, Moscow, 117246 Russia. Phone: 7(095)332-34-35. Fax:
7(095)331-01-01. E-mail: Biotec{at}glas.apc.org.
| |
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Antimicrobial Agents and Chemotherapy, November 1998, p. 2848-2852, Vol. 42, No. 11
0066-4804/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
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Abstract
Introduction
