Rodríguez-Báez AS, Jiménez-Meseguer M, Milán-Segovia RDC, Romano-Moreno S, Barcia E, Ortiz-Álvarez A, García-Díaz B, Medellín-Garibay SE. Comparison of pharmacokinetics software for therapeutic drug monitoring of piperacillin in patients with severe infections.
Eur J Hosp Pharm 2024;
31:201-206. [PMID:
36126967 PMCID:
PMC11042351 DOI:
10.1136/ejhpharm-2022-003367]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 09/05/2022] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE
To evaluate the predictive performance of population pharmacokinetic models for piperacillin (PIP) available in the software MwPharm, TDMx and ID-ODs for initial dosing selection and therapeutic drug monitoring (TDM) purposes.
METHODS
This is a prospective observational study in adult patients with severe infections receiving PIP treatment. Plasma concentrations were quantified by ultra-high performance liquid chromatography coupled to tandem mass spectrometry. The differences between predicted and observed PIP concentrations were evaluated with Bland-Altman plots; additionally, the relative and absolute bias and precision of the models were determined.
RESULTS
A total of 145 PIP plasma concentrations from 42 patients were analysed. For population prediction, MwPharm showed the best predictive performance with a mean relative difference of 34.68% (95% CI -197% to 266%) and a root mean square error (RMSE) of 60.42 µg/mL; meanwhile TDMx and ID-ODs under-predicted PIP concentrations. For individual prediction, the TDMx model was found to be the most precise with a mean relative difference of 7.61% (95% CI -57.63 to 72.86%), and RMSE of 17.86 µg/mL.
CONCLUSION
Current software for TDM is a valuable tool, but it may also include different population pharmacokinetic models in patients with severe infections, and should be evaluated before performing a model-based TDM in clinical practice. Considering the heterogeneous characteristics of patients with severe infections, this study demonstrates the need for therapy personalisation for PIP to improve pharmacokinetic/pharmacodynamic target attainment.
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