ABSTRACT
Purpose: CYP3A5 polymorphisms have been associated with variations in the pharmacokinetics of tacrolimus (Tac) in kidney transplant patients. Our study aims to quantify how the CYP3A5 genotype influences tacrolimus trough concentrations (C0) in a Vietnamese outpatient population by selecting an appropriate population pharmacokinetic model of Tac for our patients. Patients and Methods: The external dataset was obtained prospectively from 54 data of adult kidney transplant recipients treated at the 103 Military Hospital. All published Tac population pharmacokinetic models were systematically screened from PubMed and Scopus databases and were selected based on our patient's available characteristics. Mean absolute prediction error (MAPE), mean prediction error, and goodness-of-fit plots were used to identify the appropriate model for finding the formula that identifies the influence of CYP3A5 genotype on the pharmacokinetic data of Vietnamese patients. Results: The model of Zhu et al had a good predictive ability with MAPE of 19.29%. The influence of CYP3A5 genotype on tacrolimus clearance was expressed by the following formulas: CL/F=27,2×[(WT/70)0,75]×[(HCT/0,35)-0,501]×[(POD/180)0,0306]×CYP3A5(L/h). The simulation result showed that Tac C0 was significantly higher in patients not expressing CYP3A5 (p< 0.001). Conclusion: The incorporation of the CYP3A5 phenotype into Zhu's structural model has significantly enhanced our ability to predict Tacrolimus trough levels in the Vietnamese population. This study's results underscore the valuable role of CYP3A5 phenotype in optimizing the forecast of Tac concentrations, offering a promising avenue to assist health-care practitioners in their clinical decision-making and ultimately advance patient care outcomes.
ABSTRACT
BACKGROUND: To assess the incidence of new-onset diabetes after transplantation (NODAT) for the first year post-transplantation and the predictive value of high-sensitivity C-reactive Protein (hs-CRP) before transplantation for NODAT prediction in kidney transplantation patients. MATERIAL AND METHODS: A study of 251 consecutive adult end-stage kidney disease patients transplanted kidneys from living donors, follow-up during the first year to find NODAT. We diagnosed NODAT based on blood glucose or HbA1c following to the criteria of the American Diabetes Association. RESULTS: The ratio of NODAT was 12.4%. The mean age, mean BMI, the proportion of arteriosclerosis, and the median hs-CRP level in NODAT group were significantly higher than those of non-NODAT group with p < 0.05. Age, BMI and serum hs-CRP had a predictive value for NODAT (Age: AUC = 0.62, p < 0.05, BMI: AUC = 0.626, hs-CRP: AUC = 0.748, p < 0.001). CONCLUSION: Serum hs-CRP level measured prior transplantation is a good predictor for NODAT in renal transplant recipients.
