Unraveling Ceftriaxone Dosing: Free Drug Prediction, Threshold Optimization, and Model Validation.

Abstract

Ceftriaxone is pivotal in treating severe infections; however, predicting unbound plasma ceftriaxone (CEF_u) from total ceftriaxone (CEF_tot) remains challenging. This study aimed to (1) predict CEF_u from CEF_tot, (2) determine optimal target for CEF_tot trough concentration in plasma, (3) perform an external validation of published models, and (4) to ascertain whether the CEF dosing regimen was sufficient to achieve the therapeutic objectives. CEF_u predictions based on CEF_tot were evaluated using previously published models. Optimal CEF_tot targets for an MIC of 1mg/L were calculated to achieve CEF_u concentrations above MIC and 4xMIC 100% of the time. External validation was conducted assessing serum albumin, CEF_tot and CEF_u and comparing predicted CEF_u across models. Retrospective data, comprising 408 CEF_tot from 222 patients, were analyzed to assess the probability of target attainment (PTA) based on model predicted CEF_u. CEF_u predictions based on CEF_tot were evaluated using previously published models. Optimal CEF_tot targets for an MIC of 1mg/L were calculated to achieve CEF_u concentrations above MIC and 4xMIC 100% of the time. External validation was conducted assessing serum albumin, CEF_tot and CEF_u and comparing predicted CEF_u across models. Retrospective data, comprising 408 CEF_tot from 222 patients, were analyzed to assess the probability of target attainment (PTA) based on model predicted CEF_u. Optimal CEF_tot trough concentration targets ranged from 2.0 mg/L to 16.9 mg/L (1xMIC) and from 7.9 mg/L to 56.2 mg/L (4xMIC) across models. Some models accurately predicted CEF_u obtained from prospective external validation. In the retrospective cohort, PTA ranged from 94.4% to 98.7% for 1xMIC and from 66.9% to 97.3% for 4xMIC. Modeling or direct quantification of CEF_u may improve patient outcomes, but achieving this requires standardized analytical approaches and further research to assess the ability of published models to accurately predict CEF_u.