ABSTRACT
OBJECTIVE:To study the relationship of GSTP 1(rs1695)(simply as GSTP 1)gene polymorphism with the hematological toxicity in autologous hematopoietic stem cell transplantation(AHSCT)patients who used CBV regimen (cyclophosphamide,carmustine,etoposide). METHODS:A total of 83 AHSCT patients receiving CBV regimen were retrospective analyzed in our hospital during Apr. 2015-Jun. 2017. The gene polymorphism of GSTP 1 A313G was detected by fluorescence staining in situ hybridization. The hematological toxicity and the incidence of agranulocytosis fever,the implantation time of leukocyte,neutrophils and platelet were analyzed statistically. The relationship of GSTP 1 with above indexes were analyzed. RESULTS:Among 83 patients,gene variation was observed in one gene loci at least of 28 patients(33.73%).The gene frequency of A allele was 81.3%,while that of G allele was 18.7%. The reduce time of Ⅳ grade leukopenia,Ⅳ grade neutropenia and Ⅳgrade thrombocytopenia in GSTP 1 AA genotype patients were(8.91 ± 1.25),(9.02 ± 1.19),(11.56 ± 1.58)d after chemotherapy;those of patients with GSTP 1 313 allele G(AG/GG genotype) were(8.61 ± 1.17),(8.68 ± 1.19),(11.44 ± 1.34)d after chemotherapy. The implantation time of leukocyte,neutrophils and platelet in patients with GSTP 1 AA genotype were(11.98±1.99),(10.44±1.35),(15.55±2.18)d after autologus peripheral blood stem cell reinfusion;those of patients with GSTP1 313 allele G(AG/GG genotype)were(12.41±2.44),(10.36±1.62),(16.29±3.15)d after autologus peripheral blood stem cell reinfusion. The case number of grade Ⅲ-Ⅳ anemia were 24 and 11,accounting for 43.64% and 39.29% of corresponding genotype patients. The case number of agranulocytosis fever in patients with GSTP 1 AA genotype or GSTP 1 313 allele G(AG/GG genotype)were 21 and 11 during transplantation,accounting for 38.18% and 39.29% of corresponding genotype patients, respectively,without statistical significantly(P>0.05). CONCLUSIONS:There is no relationship between GSTP 1 gene polymorphism and hematological toxicity of AHSCT patients receiving CBV regimen.
ABSTRACT
This study is to develop a therapeutic drug monitoring (TDM) network server of tacrolimus for Chinese renal transplant patients, which can facilitate doctor to manage patients' information and provide three levels of predictions. Database management system MySQL was employed to build and manage the database of patients and doctors' information, and hypertext mark-up language (HTML) and Java server pages (JSP) technology were employed to construct network server for database management. Based on the population pharmacokinetic model of tacrolimus for Chinese renal transplant patients, above program languages were used to construct the population prediction and subpopulation prediction modules. Based on Bayesian principle and maximization of the posterior probability function, an objective function was established, and minimized by an optimization algorithm to estimate patient's individual pharmacokinetic parameters. It is proved that the network server has the basic functions for database management and three levels of prediction to aid doctor to optimize the regimen of tacrolimus for Chinese renal transplant patients.
ABSTRACT
In this study, we evaluated the influence of different variance from each of the parameters on the output of tacrolimus population pharmacokinetic (PopPK) model in Chinese healthy volunteers, using Fourier amplitude sensitivity test (FAST). Besides, we estimated the index of sensitivity within whole course of blood sampling, designed different sampling times, and evaluated the quality of parameters' and the efficiency of prediction. It was observed that besides CL1/F, the index of sensitivity for all of the other four parameters (V1/F, V2/F, CL2/F and k(a)) in tacrolimus PopPK model showed relatively high level and changed fast with the time passing. With the increase of the variance of k(a), its indices of sensitivity increased obviously, associated with significant decrease in sensitivity index for the other parameters, and obvious change in peak time as well. According to the simulation of NONMEM and the comparison among different fitting results, we found that the sampling time points designed according to FAST surpassed the other time points. It suggests that FAST can access the sensitivities of model parameters effectively, and assist the design of clinical sampling times and the construction of PopPK model.
ABSTRACT
To evaluate the effect of components in Guanxin Ⅱ prescription on the pharmacokinetic profiles of paeoniflorin and ferulic acid. METHODS: Drug concentrations of rat plasmas after intravenous injection of paronia pall (PPE) or ferulic acid (FA) extract solution, as well as oral administration of PPE and FA solution, and different kinds of decoctions based on Guanxin Ⅱ prescription were determined by an HPLC system. NONMEM (nonlinear mixed-effect modeling) method was used to analyze the population pharmacokinetics of PF and FA. RESULTS: A two-compartment model with first order degradation in absorption phase, and an ordinary two-compartment model were adequately describe PF and FA pharmacokinetic profiles, respectively. The mean of PF population parameters, CL1, V1, CL2, V2, Ka0, and Ka1, were 0.509 L/h, 0.104 L, 0.113 L/h, 0.123 L, 0.135 /h, and 0.0135 /h, respectively, while the typical values of CL1, V1, CL2, V2, Ka1, and F in FA model were 0.295 L/h, 0.025 L, 0.0331 L/h, 0.0518 L, 0.110 /h, and 0.40, respectively. Inter-individual variabilities were estimated and dose formulation (DF) was identified as a significant covariate in the model. CONCLUSION: The results indicate that the pharmacokinetic behaviors of index components in Guanxin Ⅱ prescription can be influenced by different dose formulations administrated in rats.
ABSTRACT
In the medical activity, the relationship between doctors and patients is an eternal theme. Moral level of medical personnel plays a very important role in realizing harmonious relationship between doctors and patients. Medical moral, can realize its lofty value only through the practice of medical personnel.