Drug design, development and therapy · 2026
Creatinine Clearance, Ceftazidime-Avibactam Exposure, and Clinical Outcomes in a Real-World TDM Cohort: A Retrospective Observational Study.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Yang Bo, Meng Jianbiao, Zheng Bei, Wang Juan, Chen Nanmei, Zhang Mingwan, Xin Chuanwei, Zhang Meiling, Tu Yuexing
Аннотация
PURPOSE: Ceftazidime-avibactam (CAZ-AVI) is a key option for carbapenem-resistant Enterobacterales (CRE) infections, but whether creatinine clearance (CrCL) independently predicts outcomes or reflects disease severity is unclear. We investigated CrCL, drug exposure, and outcomes in patients with severe Gram-negative infections receiving CAZ-AVI with therapeutic drug monitoring (TDM).
PATIENTS AND METHODS: This retrospective study included 224 patients receiving CAZ-AVI TDM at a tertiary hospital in China (May 2024-May 2025). Three cohorts were defined: trough-concentration (n=224) for factors influencing trough concentrations; concentration-outcome (n=194) for concentration-outcome associations using LASSO; and stable-dose (n=165) for baseline CrCL and outcomes. CrCL was analysed using restricted cubic splines and five prespecified analysis CrCL strata. Multivariable adjustment, E-values, LASSO, and bootstrap-validated ROC were used to separate CrCL from disease severity.
RESULTS: CrCL was the dominant determinant of ceftazidime and avibactam trough concentrations (β = -0.224 and -0.047; q = 0.040 and 0.033, respectively). The unadjusted CrCL-28-day mortality association (OR 0.993, P = 0.030) was attenuated after adjusting for SOFA and APACHE II (OR 0.996, P = 0.285; E-value = 1.07) and after full adjustment (OR 0.996, P = 0.468; E-value = 1.06). LASSO retained SOFA (OR 2.18), CRRT (OR 1.88), age (OR 1.13), and ICU admission (OR 1.03), excluding CrCL. SOFA stratification showed minimal incremental prognostic value for CrCL. The exploratory multivariable model yielded an AUC of 0.760 vs 0.571 for CrCL alone (optimism-corrected AUC: 0.793 vs 0.577).
CONCLUSION: CrCL drives CAZ-AVI trough-concentration variability but appears to be a marker of disease severity rather than an independent predictor of outcomes. Given the observational design and absence of individual MIC data, these findings should be interpreted cautiously. TDM may be best targeted at patients with extreme pharmacokinetic phenotypes, pending prospective validation. Prospective studies with MIC data are needed to define pathogen-specific targets.
PATIENTS AND METHODS: This retrospective study included 224 patients receiving CAZ-AVI TDM at a tertiary hospital in China (May 2024-May 2025). Three cohorts were defined: trough-concentration (n=224) for factors influencing trough concentrations; concentration-outcome (n=194) for concentration-outcome associations using LASSO; and stable-dose (n=165) for baseline CrCL and outcomes. CrCL was analysed using restricted cubic splines and five prespecified analysis CrCL strata. Multivariable adjustment, E-values, LASSO, and bootstrap-validated ROC were used to separate CrCL from disease severity.
RESULTS: CrCL was the dominant determinant of ceftazidime and avibactam trough concentrations (β = -0.224 and -0.047; q = 0.040 and 0.033, respectively). The unadjusted CrCL-28-day mortality association (OR 0.993, P = 0.030) was attenuated after adjusting for SOFA and APACHE II (OR 0.996, P = 0.285; E-value = 1.07) and after full adjustment (OR 0.996, P = 0.468; E-value = 1.06). LASSO retained SOFA (OR 2.18), CRRT (OR 1.88), age (OR 1.13), and ICU admission (OR 1.03), excluding CrCL. SOFA stratification showed minimal incremental prognostic value for CrCL. The exploratory multivariable model yielded an AUC of 0.760 vs 0.571 for CrCL alone (optimism-corrected AUC: 0.793 vs 0.577).
CONCLUSION: CrCL drives CAZ-AVI trough-concentration variability but appears to be a marker of disease severity rather than an independent predictor of outcomes. Given the observational design and absence of individual MIC data, these findings should be interpreted cautiously. TDM may be best targeted at patients with extreme pharmacokinetic phenotypes, pending prospective validation. Prospective studies with MIC data are needed to define pathogen-specific targets.