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 whereEscherichia coli andBacteroides 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 polymicrobialEnterobacteriaceae (cohort 2), at least oneEnterobacteriaceae pathogen plus an anaerobe(s) (cohort 3), at least oneEnterobacteriaceae 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, 35E. coli pathogens) and 2 (16 patients, 24Enterobacteriaceae ). 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.