In the field of antimicrobial chemotherapy, readers are increasingly confronted with population pharmacokinetic models and the ensuing simulation results with the purpose to improve the efficiency of currently used therapeutic regimens. One such type of analysis is Monte Carlo (MC) simulations in support of dose selection. At the moment, results of these MC simulations consist of predictions for the typical individual/population only. The uncertainty associated with the parameters, from which the simulations are derived, is completely ignored. Here, we highlight the importance of and the need to include parameter uncertainty in PTA simulations.
Using MC simulation with parameter uncertainty, we estimated CIs around PTA curves. The added benefit of this approach was illustrated using, on the one hand, a population pharmacokinetic model developed in-house for a beta-lactam antibiotic and, on the other hand, results from a previously published PTA analysis.
Our examples illustrate that proper clinical decision-making requires more than the typical PTA curve. Therefore, authors should be encouraged to provide an estimate of the uncertainty along with their simulations and to take this into account when interpreting the results. We feel that CIs around PTA curves provide this information in a comprehensive manner without requiring advanced knowledge on the underlying modelling approaches from the reader.
We believe that this approach should be advocated by all stakeholders in antibiotic stewardship programmes to safeguard the quality of clinical decision-making in the future.
- CRITICALLY-ILL PATIENTS
- TARGET ATTAINMENT ANALYSIS
- IMPAIRED RENAL-FUNCTION
- MIXED-EFFECT MODELS
- POPULATION PHARMACOKINETICS
- DOSING SIMULATIONS