Case Report: Low Hematocrit Leading to Tacrolimus Toxicity

Examining Whole Blood, Total and Free Plasma Tacrolimus in Elderly Kidney Transplant Recipients

BACKGROUND

Therapeutic monitoring is routinely performed to ensure tacrolimus whole-blood concentrations fall within a predefined target. Despite this, patients still experience inefficacy and toxicity that could be related to variability in free (unbound) tacrolimus exposure. Therefore, the aim of this study was to compare tacrolimus-free plasma (C u ), total plasma (C p ), and whole-blood (C wb ) concentrations in adult kidney transplant recipients and to characterize tacrolimus disposition across different matrices.

METHODS

Twelve-hour concentration-time profiling was performed in 15 recipients, allowing simultaneous measurement of C u , C p , and C wb . Pharmacokinetic parameters were estimated using noncompartmental analysis. The relationship between C wb and C p were examined using a capacity-limited binding model, incorporating the hematocrit fraction ( fHCT ) to estimate maximum binding concentration ( Bmax ) and dissociation constant ( Kd ). The relationship between C p and C u was evaluated using a linear binding model to estimate the nonspecific binding parameter ( Nplasma ). Nonlinear regression analysis was used to obtain estimates of Bmax , Kd , and Nplasma .

RESULTS

A total of 195 paired C wb , C p , and C u values were collected. The median ratios of C wb :C p , C p :C u , and C wb :C u were 9:1, 20:1, and 138:1, respectively. Variability in free plasma exposure was large; free trough values ranged from 8 to 51 ng/L and free area-under-the-concentration-time-curve values ranged from 424 to 7160 ng·h/L. Median (range) estimates of Bmax , Kd , and Nplasma were 90.4 µg/L (22.4-752.5 µg/L), 2.36 µg/L (0-69.2 µg/L), and 0.05 (0.035-0.085), respectively. The interindividual variability (CV%) in binding parameters was considerable ( Bmax 117.2%; Nplasma 32.5%).

CONCLUSIONS

Large variability was observed in tacrolimus-free plasma exposure and binding parameters. Future research to characterize the relationship between tacrolimus C u and patient outcomes may be of benefit.

Description and Modeling of Relevant Demographic and Laboratory Variables in a Large Oncology Cohort to Generate Virtual Populations

Background/Objectives: Pathophysiological variability in patients with cancer is associated with differences in responses to pharmacotherapy. In this work, we aimed to describe the demographic characteristics and hematological, biochemical, and coagulation variables in a large oncology cohort and to develop, optimize, and provide open access to modeling equations for the estimation of variables potentially relevant in pharmacokinetic modeling. Methods: Using data from 1793 patients with cancer, divided into training (n = 1259) and validation (n = 534) datasets, a modeling network was developed and used to simulate virtual oncology populations. All analyses were conducted in RStudio 4.3.2 Build 494. Results: The simulation network based on sex, age, biogeographic origin/ethnicity, and tumor type (fixed or primary factors) was successfully validated, able to predict age, height, weight, alpha-1-acid glycoprotein, albumin, hemoglobin, C-reactive protein and lactate dehydrogenase serum levels, platelet-lymphocyte and neutrophil-lymphocyte ratios, and hematocrit. This network was then successfully extrapolated to simulate the laboratory variables of eight oncology populations (n = 1200); only East Asians, Sub-Saharan Africans, Europeans, only males, females, patients with an ECOG performance status equal to 2, and only patients with pancreas cancer or ovarian cancer. Conclusions: this network constitutes a valuable tool to predict relevant characteristics/variables of patients with cancer, which may be useful in the evaluation and prediction of pharmacokinetics in virtual oncology populations, as well as for model-based optimization of oncology treatments.

Factors influencing intrapatient variability of tacrolimus and its association with 1-year post-transplant outcomes in pediatric liver transplant recipients

Objective

This study aims to explore the factors influencing tacrolimus intrapatient variability (TAC-IPV) and its association with 1-year post-transplant outcomes in pediatric liver transplant recipients.

Methods

Clinical and biological data of pediatric patients after liver transplantation were collected. The patients were divided into high- and low-IPV groups according to the median TAC-IPV for statistical comparisons. Factors with p < 0.05 in univariate analysis were introduced into binomial logistic regression analysis. Correlation analysis was used to test the connections between the Tac-IPV and outcomes within 1 year after liver transplantation (LT), and Kaplan-Meier was used to draw the survival curves.

Results

A total of 116 children underwent 746 measurements of TAC trough concentrations. The median TAC-IPV was 32.31% (20.81%, 46.77%). Hematocrit (p = 0.017) and concomitant medications (p = 0.001) were identified as independent influencing factors for TAC-IPV. The incidence of transplant rejection (p = 0.008), CMV infection (p < 0.001), and hospital admission due to infection (p = 0.003) were significantly higher in the high-IPV group than in the low-IPV group. Kaplan-Meier survival analysis suggests that after considering the time factor, high IPV (IPV > 32.31%) was still significantly associated with transplant rejection (HR = 3.17 and p = 0.005) and CMV infection (HR = 2.3 and p < 0.001) within 1 year after LT.

Conclusion

The study highlights the significant variation in TAC-IPV among children post-liver transplantation, emphasizing the impact of hematocrit levels and concomitant medications on TAC-IPV. Elevated TAC-IPV is associated with increased risks of transplant rejection, CMV infection, and readmission due to infection in the first year after liver transplantation. Close monitoring of patients with high TAC-IPV is recommended to promptly detect adverse reactions and provide timely intervention and treatment.

A joint population pharmacokinetic model to assess the high variability of whole-blood and intracellular tacrolimus in early adult renal transplant recipients

Tacrolimus (TAC) has high pharmacokinetic (PK) variability during the early transplantation period. The relationships between whole-blood and intracellular TAC concentrations and clinical outcomes remain controversial. This study identifies the factors affecting the PK variability of TAC and characterizes the relationships between whole-blood and intracellular TAC concentrations. Data regarding whole-blood TAC concentrations of 1,787 samples from 215 renal transplant recipients (<90 days postoperative) across two centers and intracellular TAC concentrations (648 samples) digitized from previous studies were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were screened, and the distribution of whole-blood to intracellular TAC concentration ratios (RWB:IC) was estimated. The final model was evaluated using bootstrap, goodness of fit, and prediction-corrected visual predictive checks. The optimal dosing regimens and target ranges for each type of immune cell subsets were determined using Monte Carlo simulations. A two-compartment model adequately described the data, and the estimated mean TAC CL/F was 23.6 L·h-1 (relative standard error: 11.5 %). The hematocrit level, CYP3A5*3 carrier status, co-administration with Wuzhi capsules, and tapering prednisolone dose may contribute to the high variability of TAC PK variability during the early post-transplant period. The estimated RWB:IC of all TAC concentrations in peripheral blood mononuclear cells (PBMCs) was 4940, and inter-center variability of PBMCs was observed. The simulated TAC target range in PBMCs was 20.2-85.9 pg·million cells-1. Inter-center variability in intracellular concentrations should be taken into account in further analyses. TAC dosage adjustments can be guided based on PK/PD variability and simulated intracellular concentrations.

Optimizing the initial tacrolimus dosage in Chinese children with lung transplantation within normal hematocrit levels

Background

The appropriate initial dosage of tacrolimus is undefined in Chinese pediatric lung transplant patients with normal hematocrit values. The purpose of this study is to optimize the initial dose of tacrolimus in Chinese children who are undergoing lung transplantation and have normal hematocrit levels.

Methods

The present study is based on a published population pharmacokinetic model of tacrolimus in lung transplant patients and uses the Monte Carlo simulation to optimize the initial tacrolimus dosage in Chinese children with lung transplantation within normal hematocrit levels.

Results

Within normal hematocrit levels, for children with lung transplantation who do not carry the CYP3A5*1 gene and have no coadministration with voriconazole, it is recommended to administer tacrolimus at a dosage of 0.02 mg/kg/day, divided into two doses, for children weighing 10-32 kg, and a dosage of 0.03 mg/kg/day, also divided into two doses, for children weighing 32-40 kg. For children with lung transplantation who carry the CYP3A5*1 gene and have no coadministration with voriconazole, tacrolimus dosages of 0.02, 0.03, and 0.04 mg/kg/day split into two doses are recommended for children weighing 10-15, 15-32, and 32-40 kg, respectively. For children with lung transplantation who do not carry the CYP3A5*1 gene and have coadministration with voriconazole, tacrolimus dosages of 0.01 and 0.02 mg/kg/day split into two doses are recommended for children weighing 10-17 and 17-40 kg, respectively. For children with lung transplantation who carry the CYP3A5*1 gene and have coadministration with voriconazole, a tacrolimus dosage of 0.02 mg/kg/day split into two doses is recommended for children weighing 10-40 kg.

Conclusions

It is the first time to optimize the initial dosage of tacrolimus in Chinese children undergoing lung transplantation within normal hematocrit.

Modelling changes in the pharmacokinetics of tacrolimus during pregnancy after kidney transplantation: A retrospective cohort study

AIMS

Pregnancy after kidney transplantation is realistic but immunosuppressants should be continued to prevent rejection. Tacrolimus is safe during pregnancy and is routinely dosed based on whole-blood predose concentrations. However, maintaining these concentrations is complicated as physiological changes during pregnancy affect tacrolimus pharmacokinetics. The aim of this study was to describe tacrolimus pharmacokinetics throughout pregnancy and explain the changes by investigating covariates in a population pharmacokinetic model.

METHODS

Data of pregnant women using a twice-daily tacrolimus formulation following kidney transplantation were retrospectively collected from 6 months before conception, throughout gestation and up to 6 months postpartum. Pharmacokinetic analysis was performed using nonlinear mixed effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. The final model was evaluated using goodness-of-fit plots, visual predictive checks and a bootstrap analysis.

RESULTS

A total of 260 whole-blood tacrolimus predose concentrations from 14 pregnant kidney transplant recipients were included. Clearance increased during pregnancy from 34.5 to 41.7 L/h, by 15, 19 and 21% in the first, second and third trimester, respectively, compared to prior to pregnancy. This indicates a required increase in the tacrolimus dose by the same percentage to maintain the prepregnancy concentration. Haematocrit and gestational age were negatively correlated with tacrolimus clearance (P ≤ 0.01), explaining 18% of interindividual and 85% of interoccasion variability in oral clearance.

CONCLUSIONS

Tacrolimus clearance increases during pregnancy, resulting in decreased exposure to tacrolimus, which is explained by gestational age and haematocrit. To maintain prepregnancy target whole-blood tacrolimus predose concentrations during pregnancy, increasing the dose is required.