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Objective: Many hematopoietic stem cell transplantation (HSCT) patients receive vancomycin empirically during febrile neutropenia. There are several models for estimation of vancomycin pharmacokinetic parameters and calculation of initial dosing regimen accordingly. However, the performance of these methods in HSCT patients remained to be evaluated. The aim of the study was to determine which of the vancomycin population pharmacokinetic methods best fit Iranian HSCT patients.

Methods: In order to evaluate predicted performance of seven vancomycin population pharmacokinetic models, the pharmacokinetic parameters of patients were estimated using each model's equations. Then the predicted steady-state trough vancomycin concentration was calculated based on each model's parameters and using a formula based on Sawchuk-Zaske method. The predicted steady-state trough vancomycin concentration and the real measured concentrations were compared to see which method was the most precise and least biased using mean squared error (MSE) and mean prediction error (ME) respectively.

Findings: Forty-six patients (65% men) were included in the study. Calculated metrics showed a range of 38% under-prediction bias with Rodvold to 34% over-prediction bias with Matzke and Burton models. Birt and revised Burton methods showed no significant bias (ME [95% confidence interval (CI)]: -0.067 [-0.235-0.101] and 0.066 [-0.105-0.238]). Birt and revised Burton were not different significantly considering MSE (95% CI) of 0.385 (0.227-0.544) and 0.401 (0.255-0.546), respectively. Comparisons of precision with naive predictors revealed a delta MSE (95% CI) of -0.128 (-1.379-1.890) for Birt and 0.026 (-0.596-0.940) for revised Burton models.

Conclusion: Although the Birt and Burton revised methods performed well, none of the studied models showed acceptable performance to be implemented as a routine method for initial dose calculation in HSCT patients. A vancomycin pharmacokinetic model specific for this high-risk subpopulation of Iranian patients should be designed and validated.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548431PMC
http://dx.doi.org/10.4103/2279-042X.162357DOI Listing

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