Exposure-response analyses of tigecycline efficacy in patients with complicated intra-abdominal infections.

Exposure-response analyses were performed to test the microbiological and clinical efficacies of tigecycline in complicated intra-abdominal infections where Escherichia coli and Bacteroides fragilis are the predominant pathogens. Data from evaluable patients enrolled in three clinical trials were pooled. Patients received intravenous tigecycline (100-mg loading dose followed by 50 mg every 12 h or 50-mg loading dose followed by 25 mg every 12 h). At the test-of-cure visit, microbiological and clinical responses were evaluated. Patients were prospectively classified into cohorts based on infection with a baseline pathogen(s): E. coli only (cohort 1), other mono- or polymicrobial Enterobacteriaceae (cohort 2), at least one Enterobacteriaceae pathogen plus an anaerobe(s) (cohort 3), at least one Enterobacteriaceae pathogen plus a gram-positive pathogen(s) (cohort 4), and all other pathogens (cohort 5). The cohorts were prospectively combined to increase sample size. Logistic regression was used to evaluate ratio of steady-state 24-hour area under the concentration-time curve (AUC) to MIC as a response predictor, and classification-and-regression-tree (CART) analyses were utilized to determine AUC/MIC breakpoints. Analysis began with cohorts 1, 2, and 3 pooled, which included 71 patients, with 106 pathogens. The small sample size precluded evaluation of cohorts 1 (34 patients, 35 E. coli pathogens) and 2 (16 patients, 24 Enterobacteriaceae). CART analyses identified a significant AUC/MIC breakpoint of 6.96 for microbiological and clinical responses (P values of 0.0004 and 0.399, respectively). The continuous AUC/MIC ratio was also borderline predictive of microbiological response (P = 0.0568). Cohort 4 (21 patients, 50 pathogens) was evaluated separately; however, an exposure-response relationship was not detected; cohort 5 (31 patients, 60 pathogens) was not evaluated. The prospective approach of creating homogenous populations of pathogens was critical for identifying exposure-response relationships in complicated intra-abdominal infections.

Exposure-response analyses of tigecycline efficacy in patients with complicated skin and skin-structure infections.

Exposure-response analyses were performed for the microbiological and clinical efficacy of tigecycline in the treatment of complicated skin and skin-structure infections, where Staphylococcus aureus and streptococci are the predominant pathogens. A prospective method was developed to create homogeneous patient populations for PK-PD analyses. Evaluable patients from three clinical trials were pooled for analysis. Patients received a tigecycline 100-mg loading dose/50 mg every 12 h or a 50-mg loading dose/25 mg every 12 h. At the test-of-cure visit, microbiologic and clinical responses were evaluated. Patients were prospectively evaluated and classified into cohorts based on baseline pathogens: S. aureus only (cohort 1), monomicrobial S. aureus or streptococci (cohort 2), two gram-positive pathogens (cohort 3), polymicrobial (cohort 4), or other monomicrobial infections (cohort 5). A prospective procedure for combining cohorts was used to increase the sample size. Logistic regression evaluated steady-state 24-h area under the concentration-time curve (AUC(24))/MIC ratio as a predictor of response, and classification and regression tree (CART) analyses were utilized to determine AUC/MIC breakpoints. Analysis began with pooled cohorts 2 and 3, the focus of these analyses, and included 35 patients with 40 S. aureus and/or streptococcal pathogens. CART analyses identified a significant AUC/MIC breakpoint of 17.9 (P = 0.0001 for microbiological response and P = 0.0376 for clinical response). The continuous AUC/MIC ratio was predictive of microbiological response based on sample size (P = 0.0563). Analysis of all pathogens combined decreased the ability to detect exposure-response relationships. The prospective approach of creating homogeneous populations based on S. aureus and streptococci pathogens was critical for identifying exposure-response relationships.