a Micron Research Ltd, Upwell PE14 9AR; b Bristol Centre for Antimicrobial Research and Evaluation, North Bristol NHS Trust and the University of Bristol, Department of Medical Microbiology, Southmead Hospital, Bristol BS10 5NB, UK
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Abstract |
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Introduction |
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In our review of six published clinical studies in which teicoplanin serum concentrations were measured, it appeared that both serum teicoplanin concentrations and teicoplanin concentration/MIC ratios were related to clinical success.13 However, crucial information was often lacking in the published form of these studies. In our analysis, we have drawn on an extensive teicoplanin clinical trial database to establish by logistic regression what relationship, if any, exists between clinical outcome and factors such as patient demographics, dosage regimen, serum concentration and teicoplanin MIC for the infecting organism.
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Materials and methods |
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To establish which factors account for treatment success, the study population required a reasonable percentage of failures, and so descriptive statistics from the entire database were examined to determine the main failure groups present. The study database, held by Hoechst Marion Roussel (Bridgwater, NJ, USA) contained detailed information about 719 patients from a variety of studies who had been treated with teicoplanin.
The organism that accounted for the most failures was Staphylococcus aureus, with 42 (12.1%) failures from a total group of 348 patients. S. aureus was also the most frequent single organism, and although the percentage of failures was similar to those for some other species or groups (e.g. 13.0% for coagulase-negative staphylococci), no other species or group had sufficient numbers to form a clean group for more detailed analysis. Although severity of infection was not available on the database, site of infection was always recorded. When these data were tabulated it became clear that patients with S. aureus in blood cultures formed one of the largest groups, and also contained a substantial number of failures.
It was decided therefore to focus on patients who had S. aureus single organism infections and for whom the site of infection was recorded as septicaemia. Also, S. aureus is the most challenging pathogen for any antibiotic with Gram-positive activity, given its ability to cause infection in a wide range of patients either in the community or in hospital.
Patients
Ninety-two patients had been treated for septicaemia caused by S. aureus as a single infection, and of these, 80 patients had either been cured or had failed treatment. These 80 patients formed the basis of our analysis, with 78 being included in the final logistic regression model.
The remaining 12 patients, who had improved, were also considered. However, preliminary analyses in which these patients were combined with either cured or failed groups made no difference to either model and so they were excluded from further analysis.
Teicoplanin dosing
Drug dosing information included dates and quantity of every drug administration. Where the same dose had been given for several days data were entered into the database as a single record of the dose together with the start and stop dates. Where different doses were given on the same day each dose was recorded. Using these data a computer program was written to calculate duration of treatment, mean dose administered, cumulative dose and dose in mg/kg body weight, where body weight was recorded.
Mean dose was generally calculated by taking total dose and dividing by the number of days from start to finish of therapy. However, because one patient had not been treated continuously, a second mean dose (and a second mean mg/kg body weight) was calculated in which the denominator was the number of days on which treatment was actually administered. Both types of mean were included in analyses.
Serum teicoplanin concentrations
Serum concentrations of teicoplanin were recorded before commencing drug infusion (pre-dose concentration) and approximately 1 h after the infusion had been completed (post-dose concentration). Patients did not all have the same number of pre- or post-dose estimations; also, the days on which measurements were taken varied from patient to patient. Thus, although serum concentrations have been analysed day by day over the study period, it must be borne in mind that it is not the same patients who are being measured on each day.
Preliminary analysis of the serum concentration data suggested that there was greater consistency in the pre-dose data than in the post-dose data. One obvious explanation for this is that the time of the pre-dose can be defined precisely, whereas the post-dose is often less precise. As it was also considered from previous experience that pre-dose concentrations were more important biologically for teicoplanin, detailed analysis was confined to pre-dose data.11,12
Mean pre-dose serum concentrations were calculated for every patient over the first 3 days, from day 4 to day 7, from day 4 to the end of treatment and over the whole treatment period. Apart from the last of these periods (the whole treatment period) some patients were excluded from each mean value because they had no pre-dose measurements taken during the particular time period. In particular, some patients had measurements taken only during the first 3 days and none subsequently. For this reason, in the logistic regression the mean serum concentration over the period from day 4 to the end of treatment was used for all patients who had at least one value in this time period, but so as not to reduce the number of eligible patients, day 1 to day 3 data have been included for those patients who had no serum concentration assays after day 3. Four of the 11 patients who failed therapy had no trough concentration after day 4, whereas 12 of the 69 cured had no trough concentration after day 4.
Descriptive statistical analysis
The cured and failed groups were compared for baseline and demographic characteristics using a 2 or Student's t-test as appropriate.
Logistic regression
Logistic regression (PROC LOGISTIC, SAS 6.11, SAS Institute, Inc., Cary, NC, USA) was used to determine which variable(s) influenced clinical outcome. Stepwise selection was used to decrease the number of variables influencing outcome, with entry to the model set at 0.25 and removal from the model set at 0.3. Broadening these criteria made no difference to the results obtained.
Percentage success rate was calculated by
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Variables analysed were age, body weight, mean pre-dose serum concentration, mean dose (mg or mg/kg body weight), use of loading dose, combination versus monotherapy and MIC. Clinical outcomes classified as improvement were not considered in this analysis; the only clinical categories used were cure or failure because these were considered to be definite categories. For variables for which a patient had no value, the patient was rejected from that analysis completely. Within the stepwise analysis, variables that did not contribute, or that reduced the fit of the model, were removed from the model statement sequentially. Consequently, as variables were rejected, the number of patients contributing to the model, and therefore the significance of the model, increased. Eventually two variables remained with good levels of statistical significance and a satisfactory fit.
Goodness of fit of the model was assessed using the Hosmer & Lemeshow test,14 which compares actual with predicted frequencies of success' or failure' and provides an overall statistic for goodness of fit.
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Results |
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A descriptive summary of the statistical values for the variables included in the logistic regression analysis are shown in Table I.
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Logistic regression
Of the variables analysedage, body weight, mean pre-dose serum concentration, mean dose (mg or mg/kg body weight) and combination versus monotherapyonly two correlated with clinical outcome at a significance level better than 0.05. These were age (P = 0.012) and mean pre-dose serum concentration (P = 0.010) (Table II). The R2 value for the analysis was 0.31. In a jackknife test using 0.8 as a cut-off point, 52 of 67 successfully treated patients and eight of 11 treatment failures were correctly classified. This gives a sensitivity of 77.6% to identify successfully treated patients and a specificity of 72.7% to identify treatment failures. The false positive rate (patients wrongly classified as treatment success) was 5.5%. However, the false negative rate was 65.2% because 15 patients who were classified as treatment failures were successfully treated. The relationship between age, pre-dose serum concentration and clinical outcome are displayed graphically in the Figure
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To calculate the predicted success rate for a patient aged 25 with a mean pre-dose serum concentration of 6.0 mg/L teicoplanin, we calculate x by substituting from the parameter estimate (PE) column (Table II):
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From this model it is clear that the probability of successful treatment increases with mean trough serum concentration, and decreases with age.
Other variables
In a separate preliminary logistic analysis, distribution of MIC was identified as a paradoxical factor with a negative parameter estimate and with a significance level of less than 0.05. Distribution of MIC was therefore not included in overall or further logistic regression, as its inclusion masked other, more important effects.
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Discussion |
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Animal models using teicoplanin to treat rabbit infective endocarditis caused by S. aureus indicated that 4.5 mg/kg/ 24 h was less effective at sterilizing vegetation and reducing viable counts/g vegetation than 4.5 mg/kg/16 h. The 16 h dosing regimen produced higher extravascular teicoplanin concentrations than the 24 h schedule but animals that received the 16 h dosing regimen received a higher total dosage of teicoplanin over the 80 h of therapy than those receiving 24 h dosing. Nevertheless, these data indicate that more frequent dosing of teicoplanin may be optimal.11 In addition, a further study in rabbit infective endocarditis indicated that 36 mg/kg/day teicoplanin administered intramuscularly was more effective in reducing the proportion of animals infected and the mean colony counts per vegetation than the same dose given intravenously. The iv dose produced 2 h and 12 h post-dose concentrations of 168 ± 28 mg/L and 26 ± 11 mg/L, respectively, compared with 68 ± 14 mg/L and 34 ± 10 mg/L after im dosing. The serum concentrations of the animals at culling were 11 ± 9 mg/L in those treated intravenously and 16 ± 11 mg/L in those treated intramuscularly; the mean teicoplanin concentrations in the vegetation were more than twice as high in the im group as the iv group.12 These data would indicate that transient high peak serum concentrations of teicoplanin are not likely to be of benefit in killing bacteria or curing infection and that sustained concentrations over the MIC will be of benefit in terms of improving extravascular drug penetration and cure rates. Caution must be exercised, however, as there are no high-quality dose escalation or fractionation studies in either in vitro models of infection or animals to inform decisions about teicoplanin dosage.
We reported previously a descriptive statistical analysis of 42 cases of staphylococcal infection from the literature in which the clinical site of infection, species isolated, maintenance dose, MIC for the pathogen, pre- and/or post-dose teicoplanin concentration and clinical outcome (cure, fail, interminate) were given.13 Dose, MIC or site of infection were not predictive of failure but only 20% of patients were cured if trough concentrations were <5 mg/L compared with 90% if they were >25 mg/L. Similarly, for post-dose concentrations, concentrations of <12.5 mg/L were associated with only a 10% cure rate, whereas 80% of patients were cured if the post-dose concentrations were >47 mg/L. Trough concentrations of >20 mg/L were associated with a favourable outcome. Clearly, this study had numerous methodological problems: its retrospective nature; derivation of data from six separate studies; possible variation in definition of clinical cure and timings of serum concentrations; and a relatively heterogeneous range of conditions treated. Furthermore, in many patients surgery would have had a major impact on outcome; for example, in those patients with osteomyelitis, infective endocarditis and abscesses. It was not possible to control for these.13
The present study corrects some of these problems. The patients were all known to have primary S. aureus septicaemia and hence surgery would not have influenced outcome. As the patients were recruited into clinical studies, data collection was relatively uniform and more data were available than in the case series we analysed previously. For the treatment of septicaemia with teicoplanin, our analysis shows that the two most readily quantifiable factors that influence successful outcome are mean pre-dose serum concentration and patient age. The probability of successful treatment increases with pre-dose serum concentration and decreases with age. It appears that predicted clinical success follows a saturable kinetic pattern; for example, for those over 80 years old, clinical cures increase from <30% with trough concentrations of <5 mg/L to >90% with troughs of >10 mg/L (Figure). However, the maximum trough concentration in this study was only 22 mg/L and the vast majority were <15 mg/L, hence we cannot exclude that concentrations of >20 mg/L may not add further benefit. Indeed, in the only prospective analysis of the effect of serum teicoplanin concentrations on clinical outcome (protocol 102-013) it was shown that in the treatment of staphylococcal infective endocarditis in man, 6/10 patients failed if trough concentrations were <20 mg/L compared with 1/11 if the trough was >20 mg/L (P = 0.04, Fisher's Exact test).21
Theoretically, having decided what is an acceptable probability of success, the model developed here can be used to predict what trough serum concentrations are needed for efficacy. For example, for an 85-year-old patient to have a 95% chance of success, the model predicts that a mean trough serum concentration of 13.5 mg/L would be required. Clearly, however, at this preliminary stage, such an approach must be entertained with caution. The general principle is that troughs should exceed 10 mg/L, particularly in the elderly, for infection caused by S. aureus (Figure
Although an R2 value of 0.31 (indicating that 31% of the variability in outcome is explained by the model) is statistically acceptable in an analysis of real patient data, clearly other factors still account for a substantial degree of variation and the jackknife test indicates that the present model will overestimate treatment failures. The intercept term is high, as many patients' infections will resolve without treatment. We accept that factors such as co-morbidity probably play a more important role in outcome than teicoplanin serum concentrations, but the original trial data did not allow this information to be included. Only prospective trials can validate our model.
The negative correlation for distribution of MIC and successful outcome was unexpected, as it suggests that patients have a better chance of being cured if they are infected with a isolate for which the MIC is higher. Clearly, this is a nonsense, and may be explained by the skewed MIC distribution and lack of resistant isolates (MIC > 4 mg/L), which contributed to the model.
Although these data indicate that pre-dose serum concentrations are useful in predicting clinical outcome, this does not imply that all patients with S. aureus septicaemia require therapeutic drug monitoring. It is known that standard doses of 400 mg teicoplanin at times 0, 12 h and 24 h subsequently often produce serum concentrations of <10 mg/L.8,22 Additional doses at 36 h or use of higher doses, say 600 or 800 mg, will result in higher trough concentrations but will increase drug acquisition costs. To recommend therapeutic drug monitoring of all patients routinely receiving teicoplanin for S. aureus septicaemia, randomized prospective studies would have to be performed to confirm the benefits in terms of increased efficacy or reduced cost, compared with just using larger doses. Failure to do this will repeat the mistakes that occurred with vancomycin monitoring.23
In conclusion, these data confirm that pre-dose serum concentrations are a major predictor of outcome in conjunction with patient age; however, a single model based on these two factors still leaves much of the variability in outcome unexplained.
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Acknowledgments |
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Notes |
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References |
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2 . Cowling, P., Rogers, S., McMullin, C. M., White, L. O., Lovering, A. M., MacGowan, A. P. et al. (1991). The pharmacokinetics of lomefloxacin in elderly patients with urinary tract infections following daily dosing with 400 mg. Journal of Antimicrobial Chemotherapy 28, 1017.[Abstract]
3 . Körner, R. J., McMullin, C. M., Bowker, K. A., White, L. O., Holt, H. A., Reeves, D. S. et al. (1994). The serum concentrations of desmethyl ofloxacin and ofloxacin N-oxide in seriously ill patients and their possible contributions to the antibacterial activity of ofloxacin. Journal of Antimicrobial Chemotherapy 34, 3003.[ISI][Medline]
4 . Lovering, A. M., Vickery, C. J., Watkin, D. S., Leaper, D., McMullin, C. M., White, L. O. et al. (1995). The pharmacokinetics of meropenem in surgical patients with moderate or severe infection. Journal of Antimicrobial Chemotherapy 36, 16572.[Abstract]
5 . Moore, R. D., Lietman, P. S. & Smith, C. R. (1987). Clinical response to aminoglycoside therapy: importance of the ratio of peak concentration to minimum inhibitory concentration. Journal of Infectious Diseases 155, 939.[Medline]
6 . Forrest, A., Nix, D. E., Ballow, C. H., Gross, T. F., Birmingham, M. C. & Shentag, J. J. (1993). Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients. Antimicrobial Agents and Chemotherapy 37, 107381.[Abstract]
7 . Rowland, M. (1990). Clinical pharmacokinetics of teicoplanin. Clinical Pharmacokinetics 18, 184209.[ISI][Medline]
8 . MacGowan, A. P., McMullin, C. M., White, L. O., Reeves, D. S., Davies, E. & Speller, D. C. (1992). Serum monitoring of teicoplanin. Journal of Antimicrobial Chemotherapy 30, 399402.
9 . MacGowan, A., Lovering, A., White, L. & Reeves, D. (1995). Why monitor peak vancomycin concentrations? Lancet 345, 645.
10 . Reeves, D. S., MacGowan, A. P., Holt, H. A., Lovering, A. M., Warnock, D. W. & White, L. O. (1995). Therapeutic monitoring of antimicrobials: a summary of the information presented at the UK NEQAS for Antibiotic Assays Participants MeetingOctober 1993. Journal of Antimicrobial Chemotherapy 35, 21326.[ISI][Medline]
11 . Contrepois, A., Joly, V., Abel, L., Pangon, B., Vallois, J. M. & Carhon, C. (1988). The pharmacokinetic and extravascular diffusion of teicoplanin in rabbits and comparative efficacy with vancomycin in an experimental endocarditis model. Journal of Antimicrobial Chemotherapy 21, 62131.[Abstract]
12 . Chambers, H. F. & Kennedy, S. (1990). Effects of dosage, peak and trough concentrations in serum, protein binding and bactericidal rate on efficacy of teicoplanin in a rabbit model of endocarditis. Antimicrobial Agents and Chemotherapy 34, 5104.[ISI][Medline]
13 . MacGowan, A. P., White, L. O., Reeves, D. S. & Harding, I. (1998). A retrospective review of serum teicoplanin concentrations in clinical trials and their relationship to clinical outcome. Journal of Infection and Chemotherapy 2, 197208.
14 . Hosmer, D. W. & Lemeshow, S. (1980). A goodness of fit test for the multiple logistic regression model. Communication in Statistics A10, 104369.
15 . Bailey, E. M., Rybak, M. J. & Kaatz, G. W. (1991). Comparative effect of protein binding on the killing activities of teicoplanin and vancomycin. Antimicrobial Agents and Chemotherapy 35, 108992.[ISI][Medline]
16 . Ackerman, B. H., Vannier, A. M. & Eudy, E. B. (1992). Analysis of vancomycin timekill studies with Staphylococcus species by using a curve stripping program to describe the relationship between concentration and pharmacodynamic response. Antimicrobial Agents and Chemotherapy 36, 17669.[Abstract]
17 . Larsson, A. J., Walker, K. J., Raddatz, J. K. & Rotschafer, J. C. (1996). The concentration-independent effect of monoexponential and biexponential decay in vancomycin concentrations on the killing of Staphylococcus aureus under aerobic and anaerobic conditions. Journal of Antimicrobial Chemotherapy 38, 58997.[Abstract]
18 . Duffull, S. B., Begg, E. J., Chambers, S. T. & Barclay, M. L. (1994) Efficacies of different vancomycin dosing regimens against Staphylococcus aureus determined with a dynamic in vitro model. Antimicrobial Agents and Chemotherapy 38, 24802.[Abstract]
19 . Cooper, M. A., Jin, Y.-F., Ashby, J. P., Andrews, J. M. & Wise, R. (1990). In-vitro comparison of the post-antibiotic effect of vancomycin and teicoplanin. Journal of Antimicrobial Chemotherapy 26, 2037.[Abstract]
20 . Craig, W. A. & Gudmundsson, S. (1991). The post antibiotic effect. In Antibiotics in Laboratory Medicine, 3rd edn, (Lorian, V., Ed.). Williams & Wilkins, Baltimore, MD.
21 . Wilson, A. P. R., Gruneberg, R. N. & Neu, H. (1994). A critical review of the dosage of teicoplanin in Europe and the USA. International Journal of Antimicrobial Agents 4, Suppl. 1, S130.[ISI]
22 . Lortholary, O., Tod, M., Rizzo, N., Padoin, C., Biard, O., Casassus, P. et al. (1996). Population pharmacokinetic study of teicoplanin in severely neutropenic patients. Antimicrobial Agents and Chemotherapy 40, 12427.[Abstract]
23 . Cantu, T. G., Yamanaka-Yuen, N. A. & Lietman, P. S. (1994). Serum vancomycin concentrations: reappraisal of their clinical value. Clinical Infectious Diseases 18, 53343.[ISI][Medline]
Received 13 May 1999; returned 7 September 1999; revised 17 January 2000; accepted 27 January 2000