1 Bristol Centre for Antimicrobial Research and Evaluation, Southmead Health Services NHS Trust and University of Bristol, Department of Medical Microbiology, Southmead Hospital, Westbury-on-Trym, Bristol BS10 5NB, UK 2 Faculty of Applied Sciences, University of the West of England, Frenchay, Bristol BS16 1QY, UK
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Abstract |
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Introduction |
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The inter-relationship between AUC/MIC, Cmax/MIC and T> MIC features constantly in investigations.6,11 In some studies only one parameter has been compared with antibacterial effect, for example Cmax/MIC for enoxacin9 and AUC/MIC for ciprofloxacin and ofloxacin.12 Alternative predictors, e.g. T> MIC, are not always included.8 If AUC/MIC is the sole determinant of outcome in quinolone therapy, then the shape of the serum concentrationtime curve will have no impact on antibacterial effect, while if Cmax/MIC is dominant large infrequent doses would give the best therapeutic results.
In this study some of these issues have been explored using a dilutional in-vitro model and a dose fractionation design to compare od and bd regimens using multiple parameters to assess antimicrobial efficacy.
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Materials and methods |
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Two oral dosing regimens of ciprofloxacin (0.5 g 12-hourly bd and 1 g 24-hourly od) were simulated. The target AUC for each simulation was 24.2 mg/L.h. The time to peak concentration (Tmax) was 1 h for both dosing simulations, the target Cmax for bd dosing was 1.7 mg/L and for od dosing 3.4 mg/L. For Cmin these values were 0.3 and 0.1 mg/L, respectively.
Bacterial strains
The following clinical isolates, held at the Bristol Centre for Antimicrobial Research and Evaluation, were used: Escherichia coli SMH 5773, SMH 5774 and SMH 5311 (ciprofloxacin MICs 0.03, 0.5 and 2 mg/L, respectively); Pseudomonas aeruginosa SMH 8545 and SMH 5761 (ciprofloxacin MICs 0.09 and 1.5 mg/L), Staphylococcus aureus SMH 8546 and SMH 8548 (ciprofloxacin MICs 0.12 and 1 mg/L) plus Streptococcus pneumoniae SMH 11616 and SMH 11623 (ciprofloxacin MICs 0.5 and 2 mg/L).
Antibiotic and media
Ciprofloxacin hydrochloride was supplied by Bayer plc., 1 g/L stock solutions, dissolved in water were stored at 70°C, and a fresh aliquot used for each simulation. Stock solution was added to 32 mL Isosensitest broth (ISB) or Brain Heart Infusion broth (BHI) (Oxoid, Basingstoke, UK) containing nicotine adenine dinucleotide (NAD), haemin and histidine (10 mg/L) for bd and od simulations. Viable counts were performed on nutrient agar plates (Merck, Dorset, UK), containing 1% magnesium chloride (BDH, Newbury, Berks, UK) to neutralize the ciprofloxacin, using a spiral plater (Don Whitley, Shipley, West Yorkshire, UK). For S. pneumoniae strains nutrient agar plates containing 1% magnesium chloride supplemented with 8% whole horse blood (TCS Microbiology, Buckingham, UK) were used. Plates were incubated at 37°C in air for 18 h for E. coli, P. aeruginosa and S. aureus. S. pneumoniae plates were incubated at 37°C in 5% CO2 for 18 h.
In-vitro model description
A New Brunswick Biostat C-30 (New Brunswick, Hatfield, Hertfordshire, UK) simulating a one compartment open model for oral administration was used. The apparatus consisted of a reservoir containing diluted ISB (2% for E. coli and P. aeruginosa; 6% for S. aureus and 75% BHI supplemented with 10 mg/L haemin, NAD and L-histidine for S. pneumoniae) connected via silicon and aluminium tubing to a dosing chamber and on to a culture chamber. Medium was pumped into the chambers via a peristaltic pump (Ismatec, Bennett and Co., Weston-Super-Mare, UK) at a flow rate of 1.1 mL/min to give an elimination half-life of 230 min. The chamber was agitated at 300 rpm. The temperature of the culture chamber was maintained at 37°C. A 100µL aliquot of an overnight broth of the test organism was inoculated into the culture chamber and the model then run for 18 h to enable the organism to reach a steady state' concentration of approximately 1x 108 cfu/mL. Ciprofloxacin was then inoculated into the dosing chamber according to the dosing regimen being simulated. Aliquots were collected via the outflow tube for viable count and and assay by high pressure liquid chromatography (HPLC)13 at 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 22 and 24 h after the dose. Each simulation was performed once.
A subculture of the test organism from the beginning and the end of each simulation was stored on Dorset Egg slopes or at 70°C for MIC determination by agar incorporation technique.14
Pharmacodynamics and statistics
The parameters used to measure antibacterial effect were maximum change in viable count
(max, log cfu/mL), change in viable count at 6 h (
6, log
cfu/mL), change in
viable count
at 12 h (
12, log cfu/mL), change in viable count at 24 h (
24,
log cfu/mL), slope of
the
bacterial timekill curve between 0 and 6 h (S), time to kill 99.9% of the initial
inoculum (T99.9) and the area under the bacterial-kill curve (AUBKC, log cfu/mL.h).
The
AUBKC was calculated after the inoculum was standarized, by the log linear trapezoidal rule
(Graph
Pad PrizmTM, San Diego, CA, USA). For pharmacodynamic analysis
the
percentage of
time the concentration exceeded the MIC (T> MIC), and Cmax/MIC
and AUC/MIC ratios were calculated.
Linear regression had previously shown that the AUBKC correlated best with bacterial
killing (data
not shown), and has been used by others,8 therefore this
parameter was used to compare AUC/MIC, Cmax/MIC and T>
MIC
using a simple Emax and a sigmoidal Emax model.
AUBKC
was transformed into ln (1/AUBKC) + 6, before model fitting using WinNonlin Software
(Pharsight,
Mountain View, CA, USA) as described previously.8 The
two
different models were compared by inspection of plots of residuals versus predicted values and
Akaike
information criterion. The correlation between the pharmacodynamic variables was assessed
using
Spearman rank correlation and subsequently multiple regression analysis was used to examine
the
combined effect of AUC/MIC, Cmax/MIC and T> MIC on log
(AUBKC) and log (max + 7). Both forward and backward variable selection
methods
were
used. The antibacterial effect parameters were compared between the od and bd regimens using
the
statistical Sign test for related samples.
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Results |
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The target concentrations associated with each simulation (bd and od) are shown in Figure 1. The concentration achieved in each simulation and mean values are also shown. T> MIC (% of 24 h) ranged from 0 to 100% for bd and 18 to 100% for od, depending on the pathogen MIC; Cmax/MIC ranged from 0.9 to 58 bd and 1.8 to 117 od, while AUC/MIC ratios ranged from 12 to 808 for both simulations (Table I).
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Bacterial timekill curves for the bd and od simulations, for E. coli, P. aeruginosa, S. aureus and S. pneumoniae are shown in Figure 2 (ai). In general and as expected, bacterial killing was greater the lower the MIC for the pathogen irrespective of the simulation used. S. pneumoniae was different from the other three species tested, in that bacterial killing was noticeably poorer in comparison with E. coli strains, even for strains with the same MICs (0.5 mg/L and 2 mg/L).
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The simple Emax model best described the relationship between AUC/MIC and ln (1/AUBKC) + 6 (Figure 3), while the relationship between Cmax/MIC and ln (1/AUBKC) + 6 was best described by a sigmoid Emax model (Figure 4). The relationship between T> MIC and ln (1/AUBKC) + 6 could only be described by a sigmoid Emax model as the simple model failed to converge. However, inspection of the residuals and model r2 indicated the data did not fit well for T> MIC, suggesting that the relationship is not sigmoidal.
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Both backward and forward variable selection methods gave concordant results. AUC/MIC
was
the best single predictor of log (AUBKC) and of log (max+ 7) and no
significant
improvement
in fit was observed when Cmax/MIC or T> MIC were added.
There
was some evidence to suggest that the inclusion of the quadratic term (AUC/MIC2)
improved the fit of the model describing log (AUBKC) (P= 0.07)
but not log (
max + 7), although examination of plots of residuals versus
predicted values
suggested that the variation in log (AUBKC) and log (
max + 7) could not be
described
wholly
in terms of AUC/MIC.
Comparison of od and bd regimens using different measures of antibacterial effect
The data on od and bd regimens was assessed by comparing the occasions when od was more
bactericidal than bd (Table III). The Sign test indicated that od was
superior in
terms of max,
12 and S (P< 0.05) but not
6,
24,
AUBKC or T99.9.
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MICs performed on isolates before and after ciprofloxacin dosing showed no changes with either simulation.
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Discussion |
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In this study, a similar technique to that used by the authors in a study quoted above12 was used to relate AUC/MIC and Cmax/MIC to
antibacterial effect (AUBKC). Sigmoid models were satisfactory for the explanation of these
relationships, as either a sigmoid Emax model or a simple Emax model could describe the relationship between ln (1/AUBKC) + 6 and AUC/MIC or Cmax/MIC (Figures 3 and
4). This is not
true of T > MIC which cannot easily be related to AUBKC using sigmoidal models.
Our
study incorporated a dose fractionation design, examining a wide range of pathogens with
different
ciprofloxacin MICs. Analysis of the three major pharmacodynamic parameters (AUC/MIC, Cmax/MIC and T > MIC) indicated, with the use of multiple
regression analysis,
that AUC/MIC ratio was the main determinant of outcome. Others have used linear relationships
to
relate antibacterial effect of ciprofloxacin or trovafloxacin to AUC/MIC or T> MIC,
without performing multivariate analysis.10 In these
experiments
the antibacterial effect was calculated taking into account regrowth up to the point at which
counts
recover to near levels of the controls not exposed to the drug. This end point is significantly
different
from that used by ourselves and others.6,12 This may also explain why other authors feel that the best predictor of
quinolone
antibacterial effect is T > MIC.10 The
importance of
AUC/MIC as a determinant of outcome is supported by clinical studies in which ciprofloxacin
has been
used to treat ITU-acquired pneumonia and grepafloxacin employed in the therapy of
exacerbation
of
chronic obstructive pulmonary disease.11,15 Animal models provide additional information to support the concept that,
given
equivalent AUC/MIC ratios, regimens using infrequent dosing of ciprofloxacin are superior to
continuous infusion, when time to death is used as the outcome measure.5 These observations were explored further by Drusano et al.,6 using a rat P.
aeruginosa infection model.
Treating with high-dose
lomefloxacin, survival was found to correlate best with the Cmax/MIC ratio
and T > MIC was not an important factor. These authors also showed, in a further
series of
experiments, that smaller daily doses of lomefloxacin administered either once daily or twice
daily were
equivalent in terms of survival; that is, AUC/MIC was also related to outcome.6 In in-vitro models, for some bacterial strains, once a day dosing appeared to
be
superior to twice a day, as defined by the time to kill 99.9% of the initial inoculum.16 Our data also indicate once a day dosing is superior to twice a day,
in terms of
initial speed of killing and maximum bactericidal effect, but there was no difference in the effect
over 24
h as indicated by AUBKC and 24 antibacterial effect measures. It is possible
that initial
increased rate of kill observed in our model with od dosing is translated into survival in animal
models,
but it was not possible to show that Cmax /MIC was the best predictor of
log
(
max + 7) using multivariate analysis. Recently, based on animal and human
data, it has
been
suggested that if the Cmax/MIC ratio is>10 then this parameter is the
most
significant in determining outcome, but at lower Cmax/MIC ratios
AUC/MIC is
important.17 In this study, in 12 of 18 experiments the Cmax/MIC was<10, which may explain why AUC/MIC was found to be a
better
predictor of outcome. The comparative data for od and bd dosing indicates that, at least by some
parameters of antibacterial effect, od dosing is superior.
MIC has previously been demonstrated to correlate with bacterial killing. This was also apparent in this study. S. pneumoniae is exceptional in this respect, little or no bacterial killing being seen at MICs at which this occurs in other species. Hyatt et al.18 had previously demonstrated that at the same MICs bacterial killing was greater for P. aeruginosa than for S. aureus or S. pneumoniae. It was suggested that this could be due to the higher MBCs of the latter.
In conclusion, these data support the concept that AUC/MIC is important in determining the efficacy of quinolones, but that if AUC/MIC ratios are the same, then od produces more rapid and greater bacterial killing. While od dosing is superior to bd using some measures of antibacterial effect, bd is never superior to od. Clearly the precise relationship between AUC/MIC, Cmax/MIC and outcome remains to be finally established.
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Acknowledgments |
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Notes |
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References |
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Received 3 December 1998; returned 1 March 1999; revised 16 April 1999; accepted 14 July 1999