The determination of the appropriate initial dose for tacrolimus is crucial in achieving the target concentration promptly and avoiding adverse effects and poor prognosis. However, the trial-and-error approach is still common practice. This study aimed to establish a prediction model for an initial dosing algorithm of tacrolimus in patients receiving a lung transplant. A total of 210 lung transplant recipients were enrolled, and 26 single nucleotide polymorphisms (SNP) from 18 genes that could potentially affect tacrolimus pharmacokinetics were genotyped. Associations between SNPs and tacrolimus concentration/dose ratio were analyzed. SNPs that remained significant in pharmacogenomic analysis were further combined with clinical factors to construct a prediction model for tacrolimus initial dose. The dose needed to reach steady state tacrolimus concentrations and achieve the target range was used to validate model prediction efficiency. Our final model consisted of 7 predictors-CYP3A5 rs776746, SLCO1B3 rs4149117, SLC2A2 rs1499821, NFATc4 rs1955915, alanine aminotransferase, direct bilirubin, and hematocrit-and explained 41.4% variance in the tacrolimus concentration/dose ratio. It achieved an area under the receiver operating characteristic curve of 0.804 (95% confidence interval, 0.746-0.861). The Hosmer-Lemeshow test yielded a nonsignificant P value of .790, suggesting good fit of the model. The predicted dose exhibited good correlation with the observed dose in the early postoperative period (r = 0.748, P less than .001). Our study provided a genotype-guided prediction model for tacrolimus initial dose, which may help to guide individualized dosing of tacrolimus in the lung transplant population in clinical practice.
[1]China Japan Friendship Hosp, Dept Pharm, Beijing, Peoples R China.
[2]China Japan Friendship Hosp, Dept Dermatol, Dept Pharm, Beijing, Peoples R China.
(8.0+极速模式)