Craig, W.A. (William)
http://repub.eur.nl/ppl/11172/
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RePub, Erasmus University RepositoryUse of pharmacodynamic indices to predict efficacy of combination therapy in vivo
http://repub.eur.nl/pub/9172/
Fri, 01 Jan 1999 00:00:01 GMT<div>Mouton, J.W.</div><div>Ogtrop, M.L. van</div><div>Andes, D.</div><div>Craig, W.A.</div>
Although combination therapy with antimicrobial agents is often used, no
available method explains or predicts the efficacies of these combinations
satisfactorily. Since the efficacies of antimicrobial agents can be
described by pharmacodynamic indices (PDIs), such as area under the
concentration-time curve (AUC), peak level, and the time that the
concentration is above the MIC (time>MIC), it was hypothesized that the
same PDIs would be valid in explaining efficacy during combination
therapy. Twenty-four-hour efficacy data (numbers of CFU) for Pseudomonas
aeruginosa in a neutropenic mouse thigh model were determined for various
combination regimens: ticarcillin-tobramycin (n = 41 different regimens),
ceftazidime-netilmicin (n = 60), ciprofloxacin-ceftazidime (n = 59),
netilmicin-ciprofloxacin (n = 38) and for each of these agents given
singly. Multiple regression analysis was used to determine the importance
of various PDIs (time>MIC, time>0.25 x the MIC, time>4 x the MIC, peak
level, AUC, AUC/MIC, and their logarithmically transformed values) during
monotherapy and combination therapy. The PDIs that best explained the
efficacies of single-agent regimens were time>0.25 x the MIC for
beta-lactams and log AUC/MIC for ciprofloxacin and the aminoglycosides.
For the combination regimens, regression analysis showed that efficacy
could best be explained by the combination of the two PDIs that each best
explained the response for the respective agents given singly. A
regression model for the efficacy of combination therapy was developed by
use of a linear combination of the regression models of the PDI with the
highest R(2) for each agent given singly. The model values for the
single-agent therapies were then used in that equation, and the predicted
values that were obtained were compared with the experimental values. The
responses of the combination regimens could best be predicted by the sum
of the responses of the single-agent regimens as functions of their
respective PDIs (e.g., time>0.25 x the MIC for ticarcillin and log AUC/MIC
for tobramycin). The relationship between the predicted response and the
observed response for the combination regimens may be useful for
determination of the presence of synergism. We conclude that the PDIs for
the individual drugs used in this study are class dependent and predictive
of outcome not only when the drugs are given as single agents but also
when they are given in combination. When given in combination, there
appears to be a degree of synergism independent of the dosing regimen
applied.