Previous Article | Next Article 
Antimicrobial Agents and Chemotherapy, March 1998, p. 659-665, Vol. 42, No. 3
0066-4804/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
Inter- and Intraquinolone Predictors of Antimicrobial Effect in
an In Vitro Dynamic Model: New Insight into a Widely
Used Concept
Alexander A.
Firsov,1,*
Alexander A.
Shevchenko,1
Sergey N.
Vostrov,1 and
Stephen
H.
Zinner2
Department of Pharmacokinetics, Centre of
Science & Technology LekBioTech, Moscow 117246, Russia,1 and
Division of Infectious
Diseases, Roger Williams Medical Center, Rhode Island Hospital,
Brown University, Providence, Rhode Island2
Received 15 May 1997/Returned for modification 5 October
1997/Accepted 20 December 1997
 |
ABSTRACT |
Earlier efforts to search for pharmacokinetic and bacteriological
predictors of fluoroquinolone antimicrobial effects (AMEs) have
resulted in conflicting findings. To elucidate whether these conflicts
are real or apparent, several predictors of the AMEs of two
pharmacokinetically different antibiotics, trovafloxacin (TRO) and
ciprofloxacin (CIP), as well as different dosing regimens of CIP
were examined. The AMEs of TRO given once daily (q.d.) and CIP given
q.d. and twice daily (b.i.d.) against Escherichia coli,
Pseudomonas aeruginosa, and Klebsiella
pneumoniae were studied in an in vitro dynamic model. Different
monoexponential pharmacokinetic profiles were simulated with a TRO
half-life of 9.2 h and a CIP half-life of 4.0 h to provide
similar eightfold ranges of the area under the concentration-time
curve (AUC)-to-MIC ratios, from 54 to 432 and from 59 to 473 (µg
· h/ml)/(µg/ml), respectively. In each case the
observation periods were designed to incorporate full-term regrowth
phases in the time-kill curves, and the AME was expressed by its
intensity (IE; the area between the control growth and time-kill and regrowth curves up to the point at which the
viable counts of regrowing bacteria are close to the maximum values
observed without drug). Species-independent linear relationships were
established between IE and log AUC/MIC, log AUC
above MIC (log AUCeff), and time above the MIC
(Teff). Specific and nonsuperimposed IE versus log AUC/MIC or log AUCeff
relationships were inherent in each of the treatments: TRO
given q.d. (r2 = 0.97 and 0.96), CIP
given q.d. (r2 = 0.98 and 0.96), and
CIP given b.i.d. (r2 = 0.95 and 0.93).
This suggests that in order to combine data sets obtained with
individual quinolones to examine potential predictors, one must be sure
that these sets may be combined. Unlike AUC/MIC and AUCeff,
the IE-Teff
relationships plotted for the different quinolones and dosing regimens
were nonspecific and virtually superimposed
(r2 = 0.95). Hence, AUC/MIC,
AUCeff, and Teff were equally good
predictors of the AME of each of the quinolones and each dosing
regimen taken separately, whereas Teff was also
a good predictor of the AMEs of the quinolones and their regimens taken
together. However, neither the quinolones nor the dosing regimens could
be distinguished solely on the basis of Teff,
whereas they could be distinguished on the basis of AUC/MIC or
AUCeff. Thus, two types of predictors of the quinolone AME
may be identified: intraquinolone and/or intraregimen predictors (AUC/MIC, AUCeff and
Teff) and an interquinolone and interregimen predictor
(Teff). Teff may
be able to accurately predict the AME of one quinolone on the
basis of the data obtained for another quinolone.
| |
INTRODUCTION |
The concept of pharmacokinetic and
bacteriological predictors of the antimicrobial effect has been offered
as an alternative to the traditional concentration-response
relationships usually exploited in pharmacology. Unlike many
pharmacological effects, the antimicrobial effect depends not only on
the drug concentration but also on the exposure time. Furthermore, the
use of combined pharmacokinetic and bacteriological predictors enhances
their actual predictive potential, assuming that the predictor-response relationships are bacterial species independent. Evaluation of a
predictor(s) of the antimicrobial effect and/or clinical outcome has
generally been accepted as a useful tool in the design of optimal
dosing regimens (4). For example, if the ratio of the peak
antibiotic concentration (Cmax) to MIC
(Cmax/MIC) were shown to be the best predictor,
then intermittent drug administration at relatively high doses and
relatively long intervals might be superior to drug administration at
lower doses and shorter intervals. On the other hand, if the
antimicrobial effect correlates better with the time at which the
antibiotic concentration exceeds the MIC (time above the MIC
[Teff]), the opposite dosing strategy would be
preferable.
During the past decade the predictive potentials of parameters such as
Cmax/MIC, Teff, the area
under the concentration-time curve (AUC) related to the MIC (AUC/MIC)
or the portion of AUC/MIC that reflects only the time at which the
concentrations are above the MIC (AUIC) (18), and the AUC
above the MIC (AUCeff) have been examined for various
antimicrobial agents (5, 16, 17, 20). Due to considerable
covariance among these widely used predictors, the search for a single
optimal predictor was often futile, since one was usually required to
choose among equally good predictors, especially for
pharmacokinetically similar drugs (8).
This covariance has also been noted in in vitro and in vivo studies
with fluoroquinolones (2, 6). In this regard, the use of
only one predictor, for example, Cmax/MIC for
enoxacin (2) or AUIC for ciprofloxacin and ofloxacin
(14), does not necessarily exclude the appropriate selection
of alternative predictors. Similarly, the preference
for AUC/MIC measured within 24 h
(AUC/MIC24) over Cmax/MIC
as a potential predictor of the effects of ciprofloxacin and
ofloxacin (15), without examination of AUCeff
or Teff, might not be strictly
appropriate, since AUC/MIC24 represents the sum of AUCs
produced by the administration of repeated doses of the drug, while
Cmax/MIC reflects only the impact of the first
dose administered in the dynamic model. The infrequent attempts to directly compare several potential predictors of quinolone
antimicrobial effects have led to conflicting results. For
example, no differences were reported among
Cmax/MIC, AUC/MIC, and Teff as
predictors of the efficacy of lomefloxacin against
Pseudomonas sepsis in rats: the predictive potential of each
of these predictors was equally high (r2 = 0.98 to 0.99) (6). In another study,
Cmax/MIC, AUC/MIC, and
Teff did not predict the in vitro and in vivo
effects produced by seven antibiotics including ciprofloxacin and
fleroxacin (3). Similarly, AUIC did not predict the effects
of four quinolones in an in vitro dynamic model studied by
Wiedemann et al. (25), in contrast to the data presented by
Madaras-Kelly et al. (14).
To elucidate whether these contradictions can be rectified, several
predictors of the antimicrobial effects of pharmacokinetically different quinolones, trovafloxacin and ciprofloxacin, as well as those
of two dosing regimens of ciprofloxacin were examined on the basis of
time-kill data obtained in an in vitro dynamic model.
| |
MATERIALS AND METHODS |
Antimicrobial agents.
Trovafloxacin mesylate and
ciprofloxacin lactate powders, kindly provided by Roerig, a division of
Pfizer, and by Bayer AG, respectively, were used in the study. Stock
solutions of the quinolones were prepared in sterile distilled water.
Bacterial strains.
The clinical isolates Escherichia
coli 224, Pseudomonas aeruginosa 48, and
Klebsiella pneumoniae 121 were used in the study. Susceptibility testing was performed in triplicate at 24 h
postexposure with organisms grown in Ca2+- and
Mg2+-supplemented Mueller-Hinton broth; the inoculum size
was 106 CFU/ml. The MICs of trovafloxacin for E. coli, P. aeruginosa, and K. pneumoniae
(0.25, 0.3, and 0.25 µg/ml, respectively) were found to be comparable
to those of ciprofloxacin (0.12, 0.15, and 0.12 µg/ml, respectively).
Simulated pharmacokinetic profiles.
A series of
monoexponential profiles for trovafloxacin and ciprofloxacin were
simulated. The simulated half-lives (t1/2 s; 9.25 h for trovafloxacin and 4.0 h for ciprofloxacin) were
consistent with the values reported in humans: 7.2 to 9.9 h
(19, 27) and 3.2 to 5.0 h (1, 13, 26),
respectively. Regimens of trovafloxacin given once daily (q.d.) and
ciprofloxacin given q.d. and twice daily (b.i.d.) were used in
experiments with both E. coli and P. aeruginosa.
For studies with K. pneumoniae only regimens of
trovafloxacin given q.d. and ciprofloxacin given b.i.d. were simulated.
Regardless of the antibiotic or bacterial strain, the simulated AUCs
and the respective amounts of the drugs actually administered in the
model were chosen to provide similar eightfold ranges of the AUC/MIC.
These ratios averaged from 54 to 432 (µg · h/ml)/(µg/ml)
for trovafloxacin and from 59 to 473 (µg · h/ml)/(µg/ml) for
ciprofloxacin. For regimens of ciprofloxacin given b.i.d., the AUC/MICs
presented reflect the sum of two AUC/MICs provided by the two doses of
the quinolone administered at 12-h intervals but with the residual
concentrations at the end of the first interval taken into account. The
simulated time courses of the trovafloxacin and ciprofloxacin
concentrations related to the MIC are presented in Fig.
1.
View larger version (19K):
[in this window]
[in a new window]
|
FIG. 1.
In vitro simulated pharmacokinetic profiles of
trovafloxacin (curves labeled 1) and ciprofloxacin given q.d. (curves
labeled 2) and b.i.d. (curves labeled 3). The numbers in the upper
right corner of each plot are the average values of the simulated
AUC/MICs [in (µg · h/ml)/(µg/ml)] of
trovafloxacin/simulated AUC/MICs of ciprofloxacin.
|
|
In vitro dynamic model and operating procedure.
A previously
described dynamic model (11) was used in the study.
Briefly, the model consisted of two connected flasks, one containing fresh Mueller-Hinton broth and the other, the central unit,
containing the same type of broth plus a bacterial culture (control
growth experiments) or a bacterial culture plus antibiotic (killing and
regrowth experiments). The central unit was incubated at 37°C in a
shaking water bath. Peristaltic pumps (Minipuls 2; Gilson) circulated
fresh nutrient medium to the bacterium- or bacterium- and
antibiotic-containing medium from the central 40-ml unit at a flow
rate of 3 or 7 ml/h to simulate trovafloxacin or ciprofloxacin
pharmacokinetics, respectively. Hence, the clearances provided by the
designed flow rates plus the volume of the central unit ensure the
monoexponential elimination of both trovafloxacin or ciprofloxacin
and bacteria from the system, with elimination rate constants of
0.075 h
1 (t1/2 = 9.25 h) and
0.170 h1 (t1/2 = 4.0 h),
respectively. Accurate simulations of the desired pharmacokinetic
profiles are provided by maintaining constant flow rates and a constant
volume in the central unit.
The system is filled with sterile Mueller-Hinton broth and is placed in
a temperature-regulated incubator at 37°C. The central
unit was
inoculated with 18-h cultures of
E. coli,
P. aeruginosa,
or
K. pneumoniae, and after a further
2 h of incubation, trovafloxacin
or ciprofloxacin was injected
into the central unit. The resulting
counts of the organisms in the
exponentially growing cultures
approached approximately 10
6
CFU/ml. The duration of the experiments was defined in each case
as the
time until the antibiotic-exposed bacteria (
NA)
reached
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 the experiments were stopped when
NA reached
10
11 CFU/ml. Since the
experiments that simulated low AUC/MIC ratios
met this requirement
earlier than those that simulated high AUC/MIC
ratios, the duration of
the former experiments was shorter than
that of the latter experiments.
As illustrated in Fig.
1, the
lower the AUC/MIC ratio, the shorter the
requisite observation
period.
Validation of the model.
To validate the dynamic model,
trovafloxacin or ciprofloxacin concentrations in samples of
Mueller-Hinton broth withdrawn from the central unit were determined in
duplicate by high-performance liquid chromatography (HPLC). To
precipitate the proteins from the broth, 200 µl of acetonitrile (in
the presence of trovafloxacin) or methanol (with ciprofloxacin) was
added to a 100-µl sample. The mixture was vortexed and centrifuged at
2,000 × g for 10 min. A total of 25 µl of the upper
aqueous layer was injected into the HPLC system. Chromatography was
carried out on a reversed-phase column (Silasorb C8; 5 µm; 250 by 4.6 mm [internal diameter]). The mobile phase
consisted of acetonitrile and 0.02 M KH2PO4
solution (30:70 [vol/vol]) for trovafloxacin and an
acetonitrile, ethyl alcohol, and 0.02 M KH2PO4
solution (10:20:70 [vol/vol]) for ciprofloxacin; the mobile phase was
delivered through a Waters chromatographic pump (model 501) at flow
rates of 1.7 and 1.3 ml/min, respectively.
Trovafloxacin was detected with a Waters Lambda-Max model 481 absorbance detector at 275 nm, and ciprofloxacin was detected
with a
Waters model 420-AC fluorescence detector; the excitation
wavelength
was set at 274 nm, and the emission wavelength was
set at 418 nm. The
detection limit was 0.1 µg/ml for trovafloxacin
and 0.05 µg/ml for
ciprofloxacin, and the linearity ranged from
0.25 to 10 and from 0.1 to
4 µg/ml, respectively. The interday
coefficient of variation was
close to 8% for fluoroquinolone concentrations
of both 2 and 0.5 µg/ml. The trovafloxacin and ciprofloxacin concentrations
in the
central compartment of the model determined by the HPLC
method were
close to the designed values, with no systematic deviation
from the
expected values (Fig.
2). Hence, the
model provided reasonably
accurate simulations of the pharmacokinetic
profiles.
View larger version (16K):
[in this window]
[in a new window]
|
FIG. 2.
Observed (open symbols) and designed (lines)
concentrations of trovafloxacin and ciprofloxacin in the
central compartment of the dynamic model when simulating the same
initial concentrations (2.35 µg/ml) but different
t1/2 (9.25 and 4.0 h, respectively).
|
|
Quantitation of bacterial growth and killing.
In each
experiment 0.1-ml samples were withdrawn from the bacterium-containing
medium 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 were subjected to serial
10-fold dilutions with chilled, sterile 0.9% NaCl and were plated in
duplicate onto Mueller-Hinton agar. Antibiotic carryover at low counts
was avoided by washing the bacteria with 0.9% NaCl. After overnight
incubation at 37°C the resulting bacterial colonies were counted, and
the numbers of CFU per milliliter were calculated. The limit of
detection was 2 × 102 CFU/ml.
Preliminary experiments performed in duplicate showed good within-day
and day-by-day reproducibilities of the results. The
respective pairs
of representative time-kill curves observed in
repeated experiments
with
E. coli exposed to trovafloxacin are
shown in Fig.
3. As seen in Fig.
3, the data obtained
from each
of the paired runs were virtually superimposed.
View larger version (9K):
[in this window]
[in a new window]
|
FIG. 3.
Time courses of killing and regrowth of E. coli exposed to trovafloxacin observed in parallel runs performed
on the same day [AUC/MIC = 43 (µg · h/ml)/(µg/ml)
(A)] and on different days [AUC/MIC = 92 (µg · h/ml)/(µg/ml) (B)]. The data obtained in the respective paired
experiments are indicated by different symbols.
|
|
To reveal possible changes in susceptibility, the quinolone
concentrations corresponding to the time when the numbers of surviving
organisms in the regrowth curves reached the level of the initial
inoculum (
Cregrowth) were determined for each
run (
10). No AUC/MIC-induced
systematic differences in the
Cregrowths were documented for any
of the
regimens; moreover, the appearance of bacterial regrowth
was associated
with values of unity for ratios of quinolone concentrations
to MICs.
Quantitative evaluation of the antimicrobial effect and
comparison of its predictors.
The antimicrobial effect was
expressed by the intensity IE, which describes
the area between the control growth and bacterial killing and regrowth
curves from time zero (the moment of drug input into the model) to the
time when viable counts on the regrowth curve are close to the maximum
values observed without drug (9). The upper limit of
bacterial numbers, i.e., the cutoff level in the regrowth and control
growth curves, used to determine the IE was
1011 CFU/ml (Fig. 4).
View larger version (49K):
[in this window]
[in a new window]
|
FIG. 4.
Schematic presentation of the IE
determination applied to the kinetics of killing and regrowth of
K. pneumoniae when mimicking twice-daily ciprofloxacin
administration [AUC/MIC = 59 (µg · h/ml)/(µg/ml)].
IE describes the dashed area between the control
growth (empty triangles) and the killing and regrowth (filled
triangles) curves at a cutoff level of 1011 CFU/ml.
|
|
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 of
the treatment regimens, i.e., trovafloxacin
given q.d. and
ciprofloxacin given q.d. and b.i.d. Correlation
and regression analyses
of the relationships between
IE and log
AUC/MIC,
log AUC
eff, or
Teff were performed
by using STATISTICA
software (version 4.3; StatSoft, Inc.). Statistical
comparison
of the regressions was performed at
P < 0.05, as described elsewhere
(
22).
| |
RESULTS |
The time courses of viable counts that reflect killing and
regrowth of E. coli, P. aeruginosa, and
K. pneumoniae exposed to monoexponentially decreasing
concentrations of trovafloxacin given q.d. and ciprofloxacin given q.d.
and b.i.d. and the respective control growth curves are presented in
Fig. 5 to
7.
As seen in Fig. 5 to 7, at all the AUC/MIC ratios studied, regrowth
occurred following a considerable reduction in bacterial numbers.
Unlike the rate of killing or the minimum bacterial numbers achieved, the time shift of the regrowth phase to the right along the time axis
was distinctly dependent on the simulated AUC/MIC: the higher the
AUC/MIC, the later the regrowth. Furthermore, at every simulated AUC/MIC the time-kill curves observed for each of the quinolones and
regimens were similar for the different bacteria, whereas quinolone-induced and regimen-induced (q.d. versus b.i.d. for ciprofloxacin) differences in the appearance of bacterial regrowth were
evident. For all three bacterial species exposed to trovafloxacin, at
each AUC/MIC, regrowth was observed later than that with the regimens
of ciprofloxacin given b.i.d. and especially ciprofloxacin given q.d.
Since no substantial species-dependent effects were established,
subsequent comparison of the predictors allows the data obtained with
different microorganisms in each of the experiments with a given
quinolone or regimen to be combined.
View larger version (18K):
[in this window]
[in a new window]
|
FIG. 5.
The kinetics of killing and regrowth of gram-negative
bacteria when mimicking trovafloxacin administration q.d. for E. coli ( ), P. aeruginosa ( ), and K. pneumoniae ( ) with (filled symbols) and without (empty symbols)
quinolones. The numbers in the bottom right corner of each plot are the
simulated AUC/MICs [in (µg · h/ml)/(µg/ml)].
|
|
View larger version (16K):
[in this window]
[in a new window]
|
FIG. 6.
The kinetics of killing and regrowth of gram-negative
bacteria when mimicking ciprofloxacin administration q.d. for E. coli (), P. aeruginosa (), and K. pneumoniae () with (filled symbols) and without (empty symbols)
quinolones. The numbers in the bottom right corner of each plot are the
simulated AUC/MICs [in (µg · h/ml)/(µg/ml)].
|
|
View larger version (18K):
[in this window]
[in a new window]
|
FIG. 7.
The kinetics of killing and regrowth of gram-negative
bacteria when mimicking ciprofloxacin administration b.i.d. for
E. coli (), P. aeruginosa (), and
K. pneumoniae () with (filled symbols) and without
(empty symbols) quinolones. The numbers in the bottom right corner of
each plot are the simulated AUC/MICs [in (µg · h/ml)/(µg/ml)].
|
|
The plots of IE versus log AUC/MIC, log
AUCeff, and Teff are presented in Fig.
8. As seen in Fig. 8, a specific linear
relationship between IE and log AUC/MIC is
inherent for each of the three treatments. Moreover, the correlation
coefficients have similar high values (r2 = 0.95 to 0.98), although the slopes
of the IE-log AUC/MIC plots differed (Table
1). The slope for trovafloxacin [276 log
(CFU/ml) · h] is 1.8-fold higher than that for ciprofloxacin
given b.i.d. [151 log (CFU/ml) · h], which is in turn 2.4-fold
higher than that for ciprofloxacin given q.d. [113 log (CFU/ml)
· h] (P < 0.05).
View larger version (12K):
[in this window]
[in a new window]
|
FIG. 8.
Antimicrobial effects of trovafloxacin given q.d. ( )
and ciprofloxacin given b.i.d. (- - -) and q.d.
(... .) related to the different predictors. The three points that
departed from linear
IE-Teff plot are enclosed
in a circle (for more detailed discussion, see the text).
________, all treatments.
|
|
Similar considerations apply to a comparison of the relationships
between IE and AUCeff. As seen in
Fig. 8, the IE-log AUCeff plots
obtained for trovafloxacin and ciprofloxacin given q.d. and b.i.d.
differed. The slopes of the trovafloxacin plot [250 log (CFU/ml)
· h] are 1.8- and 2.3-fold higher than those for the plots of
ciprofloxacin given b.i.d. and q.d. [141 and 108 log (CFU/ml) · h, respectively], (P < 0.05). Again, these three plots cannot be superimposed, although IE is
highly correlated with log AUCeff for each treatment
(r2 = 0.96, 0.96, and 0.93, respectively; Table 1).
The plots of IE versus
Teff for trovafloxacin and for both
ciprofloxacin regimens are linear with the single exception of the
regimen of ciprofloxacin given b.i.d., in which the points corresponding to the lowest Teff departed from
the straight line that fits the points corresponding to the three
higher values of Teff. For this reason, only the
linear portion of the
IE-versus-Teff plots for
ciprofloxacin given b.i.d. was used for further analysis. The
IE-Teff plots for the two
quinolones and the two ciprofloxacin dosing regimens are practically
superimposed and the respective slopes are similar, with no
statistically significant differences (Table 1). As seen in Fig. 8, the
IE-Teff sets combined for
all three treatments showed a very good correlation between the effect and its predictor (r2 = 0.95) that is
comparable to the respective correlations found for the regimens of
trovafloxacin and ciprofloxacin given q.d. and b.i.d. taken separately
(r2 = 0.96, 0.98, and 0.94, respectively; Table 1).
| |
DISCUSSION |
This study suggests that the antimicrobial effect of an individual
quinolone (trovafloxacin or ciprofloxacin) or a dosing regimen
(ciprofloxacin given q.d. or b.i.d.) as expressed by its intensity
(IE) correlates equally well with each of the
three predictors (AUC/MIC, AUCeff, and
Teff). Thus, no preferences for any of them may
be supported by these data. This is consistent with the reported
similar predictive potentials of AUC/MIC and Teff applied to a single quinolone (6,
21) and is quite expected, since each of the three predictors
examined in our study covaried strongly
(r2 > 0.98 for each treatment). Similar
covariance was reported previously in studies with enoxacin
(2) and lomefloxacin (6).
Although all three predictors could be accurately related to the effect
in a similar bacterial species-independent fashion, the log
AUC/MIC-response and log AUCeff-response relationships were
specific for each drug (trovafloxacin and ciprofloxacin) and for each
of the ciprofloxacin dosing regimens. This circumstance allows
quantitative comparisons of the effects of the quinolones, as reported
recently (7, 12). Unlike AUC/MIC and AUCeff, the IE-Teff plots
obtained with trovafloxacin given q.d. and ciprofloxacin given q.d. and
b.i.d. were virtually superimposed and therefore are not specific. This
means that the effect of one quinolone may be predicted by the
IE-Teff relationship
established for another quinolone. Thus, unlike AUC/MIC and
AUCeff, which may be referred to as intraquinolone and
intraregimen predictors only, Teff may also
be considered the best interquinolone and interregimen predictor of the
antimicrobial effect. However, the
IE-Teff relationships do
not reveal obvious differences between the quinolones and/or dosing
regimens of ciprofloxacin, whereas the
IE-AUC/MIC and
IE-AUCeff relationships do
reveal such differences.
As already mentioned, a specific IE-log AUC/MIC
or IE-log AUCeff relationship
was inherent for each of the treatments. Since these plots were not
superimposed and the data could not be considered a homogeneous set,
combining them would be incorrect. For example, if the
IE-AUC/MIC data from the regimens of
trovafloxacin given q.d. and ciprofloxacin given q.d. and b.i.d. were
combined, only a loose correlation between the effect and its predictor
would be established (r2 = 0.46).
Therefore, neither AUC/MIC nor AUCeff may be considered quinolone- or regimen-independent predictors of the antimicrobial effect produced by trovafloxacin and ciprofloxacin.
This conclusion is consistent with the lack of predictability of the
effects of different quinolones taken together by using AUIC
(25) or of the effects of different antibiotics including ciprofloxacin and fleroxacin by using AUC/MIC (3). At the
same time, our data do not support recent reports of successful
prediction of the effects of two different quinolones by AUIC
(14) or the statement that AUC/MIC or AUC/MIC24
were general predictors of antimicrobial effects of the
fluoroquinolones (15). At least in part, these
contradictions are probably less than they appear, because neither AUIC
(14) nor AUC/MIC (15) was compared to alternative
predictors such as AUCeff and
Teff. Moreover, this statement was based on a
scattered AUC/MIC24-response curve
(r2 = 0.58) obtained with combined data
for ciprofloxacin and ofloxacin as well as different dosing regimens.
Perhaps these data (15) should be converted into a family of
more accurate plots for each drug and regimen taken separately.
The comparative single-dose study of Wiedemann et al. (25),
which has been performed with four gram-positive and gram-negative bacteria exposed to biexponentially decreasing concentrations of
ciprofloxacin, sparfloxacin, fleroxacin, and ofloxacin, indirectly supports this hypothesis. Those investigators stated "no clear-cut relationship between AUIC and killing activity" was found when data
for four different quinolones were combined. However, the differences
between the logarithm of the initial inoculum and the logarithm of the
minimum bacterial numbers achieved (
log Nmin)
could be related to AUIC if the data for the drugs were considered separately. For example, log Nmin
correlates with the AUIC of fleroxacin and ofloxacin taken separately
(Fig. 9), although the log
AUIC-response plots associated with the individual quinolones
are quite different and these data do not belong to the same
homogeneous set. Thus, the conclusion that similar effects are produced
by the same AUC/MICs of different fluoroquinolones (15) was
not confirmed by our current findings or by the results reported by
Wiedemann et al. (25). This analysis also suggests that
before data sets obtained with pharmacokinetically different drugs and
different dosing regimens may be combined, it is necessary to test
whether these sets are homogeneous.
View larger version (14K):
[in this window]
[in a new window]
|
FIG. 9.
AUIC-dependent antimicrobial effects of two
fluoroquinolones against different bacterial strains as expressed
by log Nmin. The figure is reconstructed from
Wiedemann et al. (25).
|
|
One more reason for apparently conflicting results from studies of
different predictors of the antimicrobial effect is the use of
different parameters to quantitate the effect. The parameters ln 1/AUEC
(AUEC may be referred to as the antilogarithm of the area under the
bacterial count-time curve [AUBC] [23]), the area
above the time-kill curve (AAC [24]), and log
Nmin used in the previously cited
studies (15, 25) were shown to be insufficiently sensitive
to the AUC/MIC of ciprofloxacin (11). Moreover, the use of
AUBC and AAC might result in degenerative AUC-response relationships.
These reasons also might contribute to the scattered plot relating ln
1/AUEC and AUC/MIC referred to above (15) and to the
uncertain relationships between AAC and AUIC which were reconstructed
for individual quinolones with data from Wiedemann et al.
(25) (data not shown). In the present study an integral
parameter of the antimicrobial effect, its intensity (IE), was related to AUC/MIC,
AUCeff, and Teff, and logical
relationships between each of them and IE were
established. By its very definition, IE includes
the evaluation of full-term killing and regrowth curves from the onset
to the end of the antimicrobial effect (9). The impact of
recording the entire regrowth phase on the evaluation of the
antimicrobial effects of quinolones has been reported recently (11).
This study, performed with bacterial strains with similar
susceptibilities, allowed the selection of the best interquinolone predictor of the antimicrobial effect (Teff),
but it did not support the choice of the best intraquinolone predictor
among AUC/MIC, AUCeff, and Teff.
Recently, such a selection was proven to be possible on the basis of
data obtained with one quinolone (ciprofloxacin) for organisms with
different susceptibilities (21). A specific IE-log AUCeff plot was inherent
for each of four strains of gram-negative and gram-positive bacteria
(MICs, 0.013 to 0.60 µg/ml), whereas the respective
IE-log AUC/MIC and
IE-Teff relationships
were bacterial species independent. From this point of view, AUC/MIC
and Teff may be preferred to
AUCeff as intraquinolone predictors.
Overall, these and other recently published (21) data
suggest that the optimal interquinolone predictors of the antimicrobial effect may be selected from studies with pharmacokinetically different drugs, and intraquinolone predictors might be selected from studies with bacteria with different susceptibilities. The concept of inter-
and intraquinolone predictors might be useful for the in vitro
evaluation of future quinolone compounds. Additional studies with other
fluoroquinolones are needed to further support this concept.
| |
ACKNOWLEDGMENTS |
This study was supported by Roerig, a division of Pfizer.
We are thankful to Yury Portnoy for assistance in computer analysis and
graphic presentation of the data.
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Pharmacokinetics, Centre of Science & Technology LekBioTech, 8 Nauchny proezd, Moscow 117246, Russia. Phone: 7 (095) 332-3435. Fax: 7 (095)
331-0101. E-mail: biotec{at}glas.apc.org.
| |
REFERENCES |
| 1.
|
Bergan, T., and S. B. Thorsteinsson.
1986.
Pharmacokinetics and bioavailability of ciprofloxacin, p. 111-121.
In
H. C. Neu, and H. Weuta (ed.), Proceedings of the 1st International Ciprofloxacin Workshop, Leverkusen, Germany, 6 to 8 November 1985. Current clinical practice series 34. Elsevier Science Publishers B. V. (Excerpta Medica), Amsterdam, The Netherlands.
|
| 2.
|
Blaser, J.,
B. B. Stone,
M. C. Groner, and S. H. Zinner.
1987.
Comparative study with enoxacin and netilmicin in a pharmacodynamic model to determine importance of ratio of antibiotic peak concentration to MIC for bactericidal activity and emergence of resistance.
Antimicrob. Agents Chemother.
31:1054-1060[Abstract/Free Full Text].
|
| 3.
|
Blaser, J.,
P. Vergères,
A. F. Widmer, and W. Zimmerli.
1995.
In vivo verification of in vitro model of antibiotic treatment of device-related infection.
Antimicrob. Agents Chemother.
39:1134-1139[Abstract].
|
| 4.
|
Craig, W. A.
1995.
Interrelationship between pharmacokinetics and pharmacodynamics in determining dosage regimens for broad-spectrum cephalosporins.
Diagn. Microbiol. Infect. Dis.
22:89-96[Medline].
|
| 5.
| Drusano, G. L. 1991. Human pharmacodynamics
of beta-lactams, aminoglycosides and their combinations. Scand. J. Infect. Dis. 74(Suppl.):235-248.
|
| 6.
|
Drusano, G. L.,
D. E. Johnson,
M. Rosen, and H. C. Standiford.
1993.
Pharmacodynamics of a fluoroquinolone antimicrobial agent in a neutropenic rat model of Pseudomonas sepsis.
Antimicrob. Agents Chemother.
37:483-490[Abstract/Free Full Text].
|
| 7.
| Firsov, A., S. Vostrov, A. Shevchenko, and S. Zinner. 1997. Trovafloxacin vs. ciprofloxacin against bacteria of
similar susceptibility to both drugs: a study with Pseudomonas
aeruginosa in an in vitro dynamic model. Clin. Microbiol. Infect.
3(Suppl. 2):85. (Abstract P382.)
|
| 8.
| Firsov, A. A. 1993. Critical reappraisal of
modern approaches to search determinants of efficacy of antimicrobials.
Eur. Bull. Drug Res. 2(Suppl. 1):33-38.
|
| 9.
|
Firsov, A. A.,
V. M. Chernykh, and S. M. Navashin.
1991.
Quantitative analysis of antimicrobial effect kinetics in an in vitro dynamic model.
Antimicrob. Agents Chemother.
34:1312-1317.
|
| 10.
|
Firsov, A. A.,
A. D. Nazarov, and V. M. Chernykh.
1989.
Pharmacokinetic approaches to rational antibiotic therapy.
In
Series: Advances in Science and Engineering, vol. 17. VINITI Publishers, Moscow, Russia. (In Russian.)
|
| 11.
|
Firsov, A. A.,
S. N. Vostrov,
A. A. Shevchenko, and G. Cornaglia.
1997.
Parameters of bacterial killing and regrowth kinetics and antimicrobial effect examined in terms of area under the concentration-time curve relationships: action of ciprofloxacin against Escherichia coli in an in vitro dynamic model.
Antimicrob. Agents Chemother.
41:1281-1287[Abstract].
|
| 12.
|
Firsov, A. A.,
S. N. Vostrov,
A. A. Shevchenko, and S. H. Zinner.
1997.
Trovafloxain vs. ciprofloxacin against Klebsiella pneumoniae in an in vitro dynamic model, abstr. 2205.
In
Final Programme and Book of Abstracts of the 20th International Congress of Chemotherapy.
|
| 13.
|
Hoffken, G.,
H. Lode,
C. Prinzing,
K. Borner, and P. Koeppe.
1985.
Pharmacokinetics of ciprofloxacin after oral and parenteral administration.
Antimicrob. Agents Chemother.
27:375-379[Abstract/Free Full Text].
|
| 14.
|
Madaras-Kelly, K. J.,
A. J. Larsson, and J. C. Rotschafer.
1996.
A pharmacodynamic evaluation of ciprofloxacin and ofloxacin against two strains of Pseudomonas aeruginosa.
J. Antimicrob. Chemother.
37:703-710[Abstract/Free Full Text].
|
| 15.
|
Madaras-Kelly, K. J.,
B. E. Ostergaard,
L. Baeker Hovde, and J. C. Rotschafer.
1996.
Twenty-four-hour area under the concentration-time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect by using three strains of Pseudomonas aeruginosa and an in vitro pharmacodynamic model.
Antimicrob. Agents Chemother.
40:627-632[Abstract].
|
| 16.
|
Mattie, H.,
W. A. Craig, and J. C. Pechère.
1989.
Determinants of efficacy and toxicity of aminoglycosides.
J. Antimicrob. Chemother.
24:281-293[Abstract/Free Full Text].
|
| 17.
| Schentag, J. J. 1991. Correlation of
pharmacokinetic parameters to efficacy of antibiotics: relationships
between serum concentrations, MIC values, and bacterial eradication in
patients with gram-negative pneumonia. Scand. J. Infect. Dis.
74(Suppl.):218-234.
|
| 18.
|
Schentag, J. J.,
D. E. Nix, and M. H. Adelman.
1991.
Mathematical examination of dual individualization principles. Relationships between AUC above MIC and area under the inhibitory curve (AUC/MIC) for cefmenoxime, ciprofloxacin, and tobramycin.
DICP Ann. Pharmacother.
25:1050-1057.
|
| 19.
|
Teng, R.,
S. C. Harris,
D. E. Nix,
J. J. Schentag,
G. Foulds, and T. E. Liston.
1995.
Pharmacokinetics and safety of trovafloxacin (CP-99,219), a new quinolone antibiotic, following administration of single oral doses to healthy male volunteers.
J. Antimicrob. Chemother.
36:385-394[Abstract/Free Full Text].
|
| 20.
|
Vogelman, B.,
S. Gudmundsson,
J. Leggett,
J. Turnidge,
S. Ebert, and W. A. Craig.
1988.
Correlation of antimicrobial pharmacokinetic parameters with therapeutic efficacy in an animal model.
J. Infect. Dis.
158:831-847[Medline].
|
| 21.
| Vostrov, S., A. Shevchenko, A. Firsov, and S. Zinner. 1997. MIC-based interspecies prediction of the
antimicrobial effect: ciprofloxacin against different bacteria in an in
vitro dynamic model. Clin. Microbiol. Infect. 3(Suppl.
2):84. (Abstract P375.)
|
| 22.
|
Weber, E.
1964.
Grundriss der biologischen Statistik, 5e auflage, p. 247-248.
VEB Gustav Fischer Verlag, Jena, Germany.
|
| 23.
| White, C. A., and R. G. Toothaker. 1985. Influence of ampicillin elimination half-life on in-vitro bactericidal
effect. J. Antimicrob. Chemother. 15(Suppl.
A):257-260.
|
| 24.
|
Wiedemann, B., and A. Jansen.
1990.
Antibacterial activity of cefpodoxime proxetil in a pharmacokinetic in-vitro model.
J. Antimicrob. Chemother.
26:71-79[Abstract/Free Full Text].
|
| 25.
| Wiedemann, B., C. Rustige-Wiedemann, and B. Kratz.
1995. Comparison of the pharmacodynamic properties of quinolones.
Drugs 49(Suppl. 2):269-271.
|
| 26.
| Wise, R., D. Lister, C. A. M. McNulty, D. Griggs, and J. M. Andrews. 1986. The comparative
pharmacokinetics of five quinolones. J. Antimicrob. Chemother.
18(Suppl. D):71-81.
|
| 27.
|
Wise, R.,
D. Mortiboy,
G. Child, and G. M. Andrews.
1996.
Pharmacokinetics and penetration into inflammatory fluid of trovafloxacin (CP-99,219).
Antimicrob. Agents Chemother.
40:47-49[Abstract].
|
Antimicrobial Agents and Chemotherapy, March 1998, p. 659-665, Vol. 42, No. 3
0066-4804/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
This article has been cited by other articles:
-
Lubenko, I. Yu., Strukova, E. V., Smirnova, M. V., Vostrov, S. N., Portnoy, Y. A., Zinner, S. H., Firsov, A. A.
(2008). Telavancin and vancomycin pharmacodynamics with Staphylococcus aureus in an in vitro dynamic model. J Antimicrob Chemother
62: 1065-1069
[Abstract]
[Full Text]
-
Firsov, A. A., Lubenko, I. Y., Smirnova, M. V., Strukova, E. N., Zinner, S. H.
(2008). Enrichment of Fluoroquinolone-Resistant Staphylococcus aureus: Oscillating Ciprofloxacin Concentrations Simulated at the Upper and Lower Portions of the Mutant Selection Window. Antimicrob. Agents Chemother.
52: 1924-1928
[Abstract]
[Full Text]
-
Firsov, A. A., Smirnova, M. V., Lubenko, I. Yu., Vostrov, S. N., Portnoy, Y. A., Zinner, S. H.
(2006). Testing the mutant selection window hypothesis with Staphylococcus aureus exposed to daptomycin and vancomycin in an in vitro dynamic model. J Antimicrob Chemother
58: 1185-1192
[Abstract]
[Full Text]
-
Ba, B. B., Arpin, C., Vidaillac, C., Chausse, A., Saux, M.-C., Quentin, C.
(2006). Activity of Gatifloxacin in an In Vitro Pharmacokinetic-Pharmacodynamic Model against Staphylococcus aureus Strains either Susceptible to Ciprofloxacin or Exhibiting Various Levels and Mechanisms of Ciprofloxacin Resistance.. Antimicrob. Agents Chemother.
50: 1931-1936
[Abstract]
[Full Text]
-
Firsov, A. A., Lubenko, I. Y., Vostrov, S. N., Portnoy, Y. A., Zinner, S. H.
(2005). Antistaphylococcal Effect Related to the Area under the Curve/MIC Ratio in an In Vitro Dynamic Model: Predicted Breakpoints versus Clinically Achievable Values for Seven Fluoroquinolones. Antimicrob. Agents Chemother.
49: 2642-2647
[Abstract]
[Full Text]
-
Firsov, A. A., Vostrov, S. N., Lubenko, I. Yu., Arzamastsev, A. P., Portnoy, Y. A., Zinner, S. H.
(2004). ABT492 and levofloxacin: comparison of their pharmacodynamics and their abilities to prevent the selection of resistant Staphylococcus aureus in an in vitro dynamic model. J Antimicrob Chemother
54: 178-186
[Abstract]
[Full Text]
-
Ba, B. B., Feghali, H., Arpin, C., Saux, M.-C., Quentin, C.
(2004). Activities of Ciprofloxacin and Moxifloxacin against Stenotrophomonas maltophilia and Emergence of Resistant Mutants in an In Vitro Pharmacokinetic-Pharmacodynamic Model. Antimicrob. Agents Chemother.
48: 946-953
[Abstract]
[Full Text]
-
Mueller, M., de la Pena, A., Derendorf, H.
(2004). Issues in Pharmacokinetics and Pharmacodynamics of Anti-Infective Agents: Kill Curves versus MIC. Antimicrob. Agents Chemother.
48: 369-377
[Full Text]
-
Schentag, J. J, Meagher, A. K, Forrest, A.
(2003). Fluoroquinolone AUIC Break Points and the Link to Bacterial Killing Rates: Part 1: In Vitro and Animal Models. The Annals of Pharmacotherapy
37: 1287-1298
[Abstract]
[Full Text]
-
Zhanel, G. G, Noreddin, A. M
(2003). Fluoroquinolone AUIC Break Points and the Link to Bacterial Killing Rates: In Vitro Models. The Annals of Pharmacotherapy
37: 1331-1334
[Full Text]
-
Firsov, A. A., Vostrov, S. N., Lubenko, I. Y., Drlica, K., Portnoy, Y. A., Zinner, S. H.
(2003). In Vitro Pharmacodynamic Evaluation of the Mutant Selection Window Hypothesis Using Four Fluoroquinolones against Staphylococcus aureus. Antimicrob. Agents Chemother.
47: 1604-1613
[Abstract]
[Full Text]
-
Firsov, A. A., Zinner, S. H., Vostrov, S. N., Portnoy, Y. A., Lubenko, I. Yu.
(2002). AUC/MIC relationships to different endpoints of the antimicrobial effect: multiple-dose in vitro simulations with moxifloxacin and levofloxacin. J Antimicrob Chemother
50: 533-539
[Abstract]
[Full Text]
-
MacGowan, A. P., Rogers, C. A., Holt, H. A., Wootton, M., Bowker, K. E.
(2001). Pharmacodynamics of Gemifloxacin against Streptococcus pneumoniae in an In Vitro Pharmacokinetic Model of Infection. Antimicrob. Agents Chemother.
45: 2916-2921
[Abstract]
[Full Text]
-
Firsov, A. A., Lubenko, I. Y., Portnoy, Y. A., Zinner, S. H., Vostrov, S. N.
(2001). Relationships of the Area under the Curve/MIC Ratio to Different Integral Endpoints of the Antimicrobial Effect: Gemifloxacin Pharmacodynamics in an In Vitro Dynamic Model. Antimicrob. Agents Chemother.
45: 927-931
[Abstract]
[Full Text]
-
Wright, D. H., Brown, G. H., Peterson, M. L., Rotschafer, J. C.
(2000). Application of fluoroquinolone pharmacodynamics. J Antimicrob Chemother
46: 669-683
[Abstract]
[Full Text]
-
Firsov, A. A., Lubenko, I. Yu., Vostrov, S. N., Kononenko, O. V., Zinner, S. H., Portnoy, Y. A.
(2000). Comparative pharmacodynamics of moxifloxacin and levofloxacin in an in vitro dynamic model: prediction of the equivalent AUC/MIC breakpoints and equiefficient doses. J Antimicrob Chemother
46: 725-732
[Abstract]
[Full Text]
-
Delacher, S., Derendorf, H., Hollenstein, U., Brunner, M., Joukhadar, C., Hofmann, S., Georgopoulos, A., Eichler, H. G., Muller, M.
(2000). A combined in vivo pharmacokinetic-in vitro pharmacodynamic approach to simulate target site pharmacodynamics of antibiotics in humans. J Antimicrob Chemother
46: 733-739
[Abstract]
[Full Text]
-
MacGowan, A., Rogers, C., Bowker, K.
(2000). The use of in vitro pharmacodynamic models of infection to optimize fluoroquinolone dosing regimens. J Antimicrob Chemother
46: 163-170
[Full Text]
-
MacGowan, A., Rogers, C., Holt, H. A., Wootton, M., Bowker, K.
(2000). Assessment of different antibacterial effect measures used in in vitro models of infection and subsequent use in pharmacodynamic correlations for moxifloxacin. J Antimicrob Chemother
46: 73-78
[Abstract]
[Full Text]
-
Vostrov, S. N., Kononenko, O. V., Lubenko, I. Y., Zinner, S. H., Firsov, A. A.
(2000). Comparative Pharmacodynamics of Gatifloxacin and Ciprofloxacin in an In Vitro Dynamic Model: Prediction of Equiefficient Doses and the Breakpoints of the Area under the Curve/MIC Ratio. Antimicrob. Agents Chemother.
44: 879-884
[Abstract]
[Full Text]
-
Bowker, K. E., Wootton, M., Rogers, C. A., Lewis, R., Holt, H. A., MacGowan, A. P.
(1999). Comparison of in-vitro pharmacodynamics of once and twice daily ciprofloxacin. J Antimicrob Chemother
44: 661-667
[Abstract]
[Full Text]
-
Firsov, A. A., Vasilov, R. G., Vostrov, S. N., Kononenko, O. V., Lubenko, I. Yu., Zinner, S. H.
(1999). Prediction of the antimicrobial effects of trovafloxacin and ciprofloxacin on staphylococci using an in-vitro dynamic model. J Antimicrob Chemother
43: 483-490
[Abstract]
[Full Text]
-
Firsov, A. A., Vostrov, S. N., Kononenko, O. V., Zinner, S. H., Portnoy, Y. A.
(1999). Prediction of the Effects of Inoculum Size on the Antimicrobial Action of Trovafloxacin and Ciprofloxacin against Staphylococcus aureus and Escherichia coli in an In Vitro Dynamic Model. Antimicrob. Agents Chemother.
43: 498-502
[Abstract]
[Full Text]
-
Firsov, A. A., Vostrov, S. N., Shevchenko, A. A., Portnoy, Y. A., Zinner, S. H.
(1998). A New Approach to In Vitro Comparisons of Antibiotics in Dynamic Models: Equivalent Area under the Curve/MIC Breakpoints and Equiefficient Doses of Trovafloxacin and Ciprofloxacin against Bacteria of Similar Susceptibilities. Antimicrob. Agents Chemother.
42: 2841-2847
[Abstract]
[Full Text]
Top
Abstract
Introduction
