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.

Pharmacokinetic and clinical data from tigecycline-treated patients with hospital-acquired pneumonia (HAP) who were enrolled in a phase 3 clinical trial were integrated in order to evaluate pharmacokinetic-pharmacodynamic (PK-PD) relationships for efficacy. Univariable and multivariable analyses were conducted to identify factors associated with clinical and microbiological responses, based on data from 61 evaluable HAP patients who received tigecycline intravenously as a 100-mg loading dose followed by 50 mg every 12 h for a minimum of 7 days and for whom there were adequate clinical, pharmacokinetic, and response data. The final multivariable logistic regression model for clinical response contained albumin and the ratio of the free-drug area under the concentration-time curve from 0 to 24 h (fAUC(0-24)) to the MIC (fAUC(0-24):MIC ratio). The odds of clinical success were 13.0 times higher for every 1-g/dl increase in albumin (P < 0.001) and 8.42 times higher for patients with fAUC(0-24):MIC ratios of ≥0.9 compared to patients with fAUC(0-24):MIC ratios of <0.9 (P = 0.008). Average model-estimated probabilities of clinical success for the albumin/fAUC(0-24):MIC ratio combinations of <2.6/<0.9, <2.6/≥0.9, ≥2.6/<0.9, and ≥2.6/≥0.9 were 0.21, 0.57, 0.64, and 0.93, respectively. For microbiological response, the final model contained albumin and ventilator-associated pneumonia (VAP) status. The odds of microbiological success were 21.0 times higher for every 1-g/dl increase in albumin (P < 0.001) and 8.59 times higher for patients without VAP compared to those with VAP (P = 0.003). Among the remaining variables evaluated, the MIC had the greatest statistical significance, an observation which was not surprising given the differences in MIC distributions between VAP and non-VAP patients (MIC(50)and MIC(90) values of 0.5 and 0.25 mg/liter versus 16 and 1 mg/liter for VAP versus non-VAP patients, respectively; P = 0.006). These findings demonstrated the impact of pharmacological and patient-specific factors on the clinical and microbiological responses.