Multistate modeling for survival analysis in critically ill patients treated with meropenem

This study investigated predictors of in-hospital mortality in critically ill patients treated with meropenem by pharmacometric multistate modeling. A multistate model compris ing five states (ongoing meropenem treatment, other antibiotic treatment, antibiotic treatment termination, discharge, and death) was developed to capture the transitions in a cohort of 577 critically ill patients treated with meropenem. Various factors were investigated as potential predictors of t he transitions, including patient demographics, creatinine clearance calculated by Cockcroft–Gault equation (CLCRCG), time that unbound concentrations exceed the minimum inhibitory concentration (fT>MIC), and microbiology-related measures. The probabilities to transit to other states from ongoing meropenem treatment increased over time. A 10  mL/min decrease in CLCRCG was found to elevate the hazard of transitioning from states of ongoing meropenem treatment and antibiotic treatment termination to the death state by 18%. The attainment of 100%fT>MIC significantly increased the transition rate from ongoing meropenem treatment to antibiotic treatment termination (by 9.7%), and was associated with improved survival outcome. The multistate model prospectively assessed predictors of death and can serve as a useful tool for survival analysis in different infection scenarios, particularly when competing risks are present.
Source: CPT: Pharmacometrics and Systems Pharmacology - Category: Drugs & Pharmacology Authors: Tags: ARTICLE Source Type: research