Serum Cystatin C as a Risk Factor for Supratherapeutic Digoxin Concentration in Elderly Patients with Heart Failure and Chronic Kidney Disease.

BACKGROUND: Digoxin is primarily metabolized by the kidney, and its toxicity is strongly associated with high concentrations, particularly in elderly patients. The purpose of this study was to evaluate the predictive performance of renal function biomarkers for supratherapeutic digoxin concentrations in elderly patients with heart failure (HF) and chronic kidney disease (CKD). METHODS: Data were retrospectively obtained from elderly patient with HF and CKD who received digoxin treatment from January 2022 and December 2022. Logistic regression was used to assess independent risk factors for supratherapeutic concentrations. The predictive performance of serum creatinine, serum cystatin C, and blood urea nitrogen on supratherapeutic concentrations was compared by receiver operating characteristic analysis. RESULTS: A total of 115 elderly patients with HF and CKD were enrolled in our study. Supratherapeutic concentrations were detected in 49 patients. Logistic regression analysis showed that estimated glomerular filtration rate calculated by serum cystatin C [eGFRCysC, odds ratio (OR): 0.962, P = 0.006], heart rate (OR: 1.024, P = 0.040), and NYHA class (OR: 3.099, P = 0.010) were independent risk factors for supratherapeutic concentration. Cutoff value for eGFRCysC between the two groups was 41 ml/min/1.73m2. Predictive performance of serum cystatin C was further improved in patients with obesity, CKD stage 4-5, and older than 75 years compared with normal weight, CKD stage 3, and aged 60-75-year-old patients. CONCLUSIONS: Serum cystatin C is a sensitive renal function biomarker to predict supratherapeutic digoxin concentration in elderly patients with HF and CKD.

Population pharmacokinetics of cyclosporine A in pediatric patients with thalassemia undergoing allogeneic hematopoietic stem cell transplantation.

PURPOSE: To establish the population pharmacokinetics (PPK) model of cyclosporine A(CsA) in pediatric patients with thalassemia undergoing allogeneic hematopoietic stem cell transplantation (HSCT), aiming at providing a reference for clinical dose individualization of CsA. METHODS: Children with thalassemia who underwent allogeneic HSCT were enrolled retrospectively. The PPK structural model and the random variable model of CsA were established on NONMEN. And goodness of fit plots (GOFs), visual predictive check (VPC), and bootstrap and normalized prediction distribution errors (NPDE) were used to evaluate the final model. RESULTS: A one-compartment model with first-order absorption was employed to fit the base model. A total of 74 pediatric patients and 600 observations of whole blood concentration were included. The final model included weight (WT) in clearance (CL), alongside post-operative day (POD), fluconazole (FLUC), voriconazole (VORI), posaconazole (POSA), and red blood cell count (RBC) significantly. All the model evaluations were passed. CONCLUSION: In the PPK model based on the pediatric cohort on CsA with thalassemia undergoing allogeneic HSCT, WT, POD, FLUC, VORI, POSA, and RBC were found to be the significant factors influencing CL of CsA. The reliability and robustness of the final model were excellent. It is expected that the PPK model can assist in individualizing dosing strategy clinically.

Dosage Optimization of Digoxin in Older Patients with Heart Failure and Chronic Kidney Disease: A Population Pharmacokinetic Analysis.

BACKGROUND: Renal function is an important index for digoxin dose adjustment, especially in patients with chronic kidney disease (CKD). Decreased glomerular filtration rate is common in older patients with cardiovascular disease. OBJECTIVE: The aim of this study was to establish a digoxin population pharmacokinetic model in older patients with heart failure and CKD and to optimize the digoxin dose strategy. METHODS: Older patients with heart failure and CKD aged > 60 years from January 2020 to January 2021 and who had an estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73 m2 or urine protein production were enrolled in this retrospective study. Population pharmacokinetic analysis and Monte Carlo simulations (n = 1000) were performed using NONMEN software. The precision and stability of the final model were analyzed by graphical and statistical methods. RESULTS: Overall, 269 older patients with heart failure were enrolled. A total of 306 digoxin concentrations were collected, with a median value of 0.98 ng/mL (interquartile range [IQR] 0.62-1.61, range 0.04-4.24). The median age was 68 years (IQR 64-71, range 60-94) and eGFR was 53.6 mL/min/1.73 m2 (IQR 38.1-65.2, range 11.4-89.8). A one-compartment model with first-order elimination was developed to describe the digoxin pharmacokinetics. Typical values for clearance and volume of distribution were 2.67 L/h and 36.9 L, respectively. Dosage simulations were stratified by eGFR and metoprolol. Doses of 62.5 and 125 µg were recommended for older patients with eGFR < 60 mL/min/1.73 m2. CONCLUSIONS: A population pharmacokinetic model of digoxin in older patients with heart failure and CKD was established in this study. A novel digoxin dosage strategy was recommended in this vulnerable population.

Comparison of Vancomycin Clearance Between Augmented Renal Clearance and Normal Renal Function in Critically Ill Infants: A Population Pharmacokinetics Study.

Augmented renal clearance presents as super-renal function with enhanced renal perfusion and glomerular hyperfiltration in many critically ill infants. This study was to compare vancomycin clearance (CL) between critically ill infants with augmented renal clearance and with normal renal function and to optimize the vancomycin dosage. Data were retrospectively obtained from infants treated in intensive care units. Population pharmacokinetics analysis was conducted using nonlinear mixed-effects model software. A total of 66 critically ill infants were included: 47 infants with augmented renal clearance and 19 infants with normal renal function. The median doses of vancomycin for infants with augmented renal clearance and with normal renal function were 48 and 47 mg/kg/day (P > .05), respectively. The median CL in infants with augmented renal clearance was increased 1.96-fold compared with infants who had normal renal function (0.98 versus 0.5 L/h, P < .001). Simulations indicated that the recommended dosage of 60, 70, 80, 90, and 100 mg/kg/day would be appropriate in critically ill infants with an estimated glomerular filtration rate (eGFR) of 130-149, 150-169, 170-189, 190-209, and >210 mL/min/1.73 m2 , respectively. Doses of 70 and 75 mg/kg/day were recommended for infants with augmented renal clearance and gestational ages of 27-32.9 and 33-39 weeks, respectively. Doses of 70, 75, 80, and 90 mg/kg/day were recommended for infants with augmented renal clearance and weights of 2.0-2.9, 3.0-3.9, 4.0-4.9, and 5.0-6.0 kg, respectively. In conclusion, the typical vancomycin dosage is insufficient for critically ill infants with augmented renal clearance. Premature infants and infants of low weight with augmented renal clearance need individualized dosing regimens to obtain an adequate area under the serum concentration time curve over 24 h/minimum inhibitory concentration ratio.

Influential Factors and Efficacy Analysis of Tacrolimus Concentration After Allogeneic Hematopoietic Stem Cell Transplantation in Children with ß-Thalassemia Major.

PURPOSE: To analyze factors influencing tacrolimus (TAC) trough concentration (C0) in ß-thalassemia major (ß-TM) pediatric patients after allogeneic hematopoietic stem cell transplantation (Allo-HSCT) and to investigate the effects of genotype polymorphism and drug-drug interactions on TAC trough concentration in children with ß-TM. Furthermore, to analyze the correlation between TAC C0 and efficacy and adverse reactions. PATIENTS AND METHODS: Prospectively collection of demographic information and details of combined treatment of patients with ß-TM receiving HSCT, and genotypes of CYP3A4, CYP3A5, and ABCB1 (rs1045642, rs1128503, rs2032582) were obtained for each patient. Univariate analysis and multiple linear regression analysis were used to investigate influencing factors on TAC C0. The impact of different genotypes and the co-administration of azole antifungal drugs on ß-TM patients receiving TAC were evaluated, together with the correlation between acute graft-versus-host disease (aGVHD), infection, and liver injury of TAC C0. RESULTS: A total of 46 patients with 587 concentration data were included. The multiple linear regression results showed that the patient's sex, weight, postoperative time, hemoglobin, platelet count, serum cystatin C, and combined voriconazole were independent influencing factors of the infusion trough concentration/daily dose, C0/Div. Age, body surface area, postoperative time, co-administration of voriconazole, and CYP3A4*18B are independent influencing factors of C0/Dpo. Group comparisons showed that voriconazole can affect TAC C0 administered intravenously (IV) and orally in ß-TM pediatric patients, while patient genotype can affect TAC C0 during oral administration. TAC C0 does not correlate with aGVHD or liver injury, but infection may be associated with TAC C0. CONCLUSION: The concentration of TAC should be closely monitored when co-administered with voriconazole. It is worth considering that the influence of genotype on the trough concentration of oral TAC and individualized drug administration warrant investigation. Finally, this study indicated that C0 is not suitable as an indicator of the efficacy of TAC.

Systematic external evaluation of reported population pharmacokinetic models of vancomycin in Chinese children and adolescents.

WHAT IS KNOWN AND OBJECTIVES: Various population pharmacokinetic (PopPK) models for vancomycin in children and adolescents have been constructed to optimize the therapeutic regimen of vancomycin. However, little is known about their predictive performance when extrapolated to different clinical centres. Therefore, the aim of this study was to externally validate the predictability of vancomycin PopPK model when extrapolated to different clinical centres and verify its applicability in an independent data set. METHODS: The published models were screened from the literature and evaluated using an external data set of a total of 451 blood concentrations of vancomycin measured in 220 Chinese paediatric patients. Prediction- and simulation-based diagnostics and Bayesian forecasting were performed to evaluate the predictive performance of the models. RESULTS: Ten published PopPK models were assessed. Prediction-based diagnostics showed that none of the investigated models met all the standards (median prediction error (MDPE) ≤ ±20%, median absolute prediction error (MAPE) ≤30%, PE% within ±20% (F20 ) ≥35% and PE% within ±30% (F30 ) ≥50%), indicating unsatisfactory predictability. In simulation-based diagnostics, both the visual predictive checks (VPC) and the normalized prediction distribution error (NPDE) indicated misspecification in all models. Bayesian forecasting results showed that the accuracy and precision of individual predictions could be significantly improved with one or two prior observations, but frequent monitoring might not be necessary in the clinic, since Bayesian forecasting identified that greater number of samples did not significantly improve the predictability. Model 3 established by Moffett et al showed better predictability than other models. WHAT IS NEW AND CONCLUSION: The 10 published models performed unsatisfactorily in prediction- and simulation-based diagnostics; none of the published models was suitable for designing the initial dosing regimens of vancomycin. Pharmacokinetic characteristics and covariates, such as weight, renal function, age and underlying disease should be taken into account when extrapolating the vancomycin model. Bayesian forecasting combined with therapeutic drug monitoring based on model 3 can be used to adjust vancomycin dosing regimens.

Initial Dosage Optimization of Tacrolimus in Pediatric Patients With Thalassemia Major Undergoing Hematopoietic Stem Cell Transplantation Based on Population Pharmacokinetics.

BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is an effective treatment for hematological disorders. Tacrolimus is widely used after HSCT, but it has highly interindividual variable pharmacokinetics. Population pharmacokinetics (PPK) researches of tacrolimus in children with ß-thalassemia major (ß-TM) undergoing HSCT are insufficient. OBJECTIVE: To establish a PPK model of tacrolimus in children with ß-TM and optimize initial dosing regimen for achieving target concentration of 5 to 15 ng/mL. METHODS: Data on patients aged <18 years were retrospectively collected from January 2017 to December 2018. PPK analysis and Monte Carlo simulations were performed using nonlinear mixed-effects modeling. RESULTS: A data set of 55 patients with 332 concentrations was included. A 2-compartment model could best describe the pharmacokinetics of tacrolimus. The body surface area and gender were significant covariates in the final model. The typical value of clearance, the distribution volume of the central room, the distribution volume of the peripheral room, and the intercompartmental clearance were 5.05L/h, 4.33L, 155L, and 6.22L/h, respectively. The optimal initial dosing regimen of 0.03, 0.04, 0.05, 0.06, and 0.10 mg/kg were appropriate for female children with a weight (WT) of 50 to 10 kg. The regimen of 0.04, 0.05, 0.06, 0.07, and 0.12 mg/kg is suitable for male children with a WT of 50 to 10 kg. The probability of target attainment (PTA) of each regimen reached 91%. CONCLUSION AND RELEVANCE: A stable PPK model of tacrolimus was established. The proposed dosage regimen reached a good PTA, which could provide a reference for tacrolimus therapy.

Vancomycin population pharmacokinetics and dosing recommendations in haematologic malignancy with augmented renal clearance children.

WHAT IS KNOWN AND OBJECTIVES: Augmented renal clearance (ARC) is characterized by enhanced renal clearance, which leads to insufficient vancomycin exposure and treatment failure. In haematologic malignancy patients, determination of optimal vancomycin dosage is essential because of high stake of life-threatening bacterial infection and increased clearance. The aim of this study was to describe vancomycin pharmacokinetic parameters in haematologic malignancy with augmented renal clearance children and define the appropriate dosing regimen to achieve an AUC0-24h /MIC ≥400. METHODS: Hematologic malignancy with ARC children was enrolled in this retrospective study. The vancomycin PPK model was established by non-linear mixed-effects modelling programme. Goodness-of-fit (GOF) plots, non-parametric bootstrap, normalized prediction distribution error (NPDE) and visual predictive checks (VPCs) were carried out for internal evaluation of the final model. Monte Carlo simulation method was used to stimulate the optimal dosage regimens. RESULTS: Fifty-three patients with 106 samples were included. A one-compartment model with first-order elimination was developed, and the final model was as follows: CL (L/h) = 6.32×（WT/70）0.75  × e0.0467 ; V(L) = 39.6×(WT/70), where WT denotes weight (kg). The internal validation of the model showed a good prediction performance. Monte Carlo simulation results showed that when MIC was 0.5 mg/L or 1 mg/L, the recommended doses to achieve a target of AUC0-24h /MIC ≥400 were 25 to 40 and 50 to 75 mg/kg/d, respectively. With decreasing weight, the recommended dosage to achieve an AUC0-24h /MIC ≥400 increased. WHAT IS NEW AND CONCLUSION: A one-compartment vancomycin PPK model was established in haematologic malignancy with augmented renal clearance children with weight with allometric scaling as a significant covariate. When MIC was 1 mg/L, current recommended paediatric dosages were insufficient in haematologic malignancy with augmented renal clearance children and should be increased.

A Population Pharmacokinetics Model for Vancomycin Dosage Optimization Based on Serum Cystatin C.

BACKGROUND AND OBJECTIVES: Renal function has an important influence on the pharmacokinetics of vancomycin, and serum cystatin C (CysC) exhibits accurate predictive performance as a marker for renal function. This study aimed to develop a population pharmacokinetics (PopPK) model of vancomycin based on serum CysC in pediatric patients. In addition, vancomycin dosage was optimized with the area under the serum concentration-time curve over 24 h (AUC0-24)/minimum inhibitory concentration (MIC) ratio in the target range of 400-700 and the steady-state trough concentration (Css,trough). METHODS: Data were retrospectively obtained from pediatric patients aged 2-18 years who received vancomycin treatment for infection from January 2014 to June 2019. PopPK analysis and Monte Carlo simulations were conducted using nonlinear mixed effects model (NONMEM) software. RESULTS: A total of 220 children were included. Serum CysC and age were significant covariates affecting the pharmacokinetics of vancomycin. The final typical value of clearance was 2.25 L/h; the volume of distribution was 8.17 L. The average probability of target attainment values of AUC0-24/MIC ratios within 400-700 in the 2-7, 7-12, and 12-18 years age groups were 66.1%, 68.1% and 66.5%, respectively. The median Css,trough values of vancomycin for the 2-7, 7-12, and 12-18 years age groups were 7.49-11.84, 5.98-11.32, and 5.15-11.39 mg/L, respectively, and were highly correlated with AUC0-24/MIC ratios in the range of 400-700 when the MIC was 1 mg/L. CONCLUSIONS: The pharmacokinetic parameters for vancomycin in pediatric patients were estimated using a serum CysC model. The simulated dosages provide a reference for vancomycin therapy.

Comparison of the Predictive Performance Between Cystatin C and Serum Creatinine by Vancomycin via a Population Pharmacokinetic Models: A Prospective Study in a Chinese Population.

BACKGROUND: Most of the current published population pharmacokinetic (PopPK) models are based on serum creatinine, but we often encounter an underestimation of its concentration in our clinical work. Therefore, we established a cystatin C-based model of vancomycin. OBJECTIVES: The purpose of this study was to externally verify the PopPK model of vancomycin based on the glomerular filtration rate (GFR) estimated by serum cystatin C in our previous study and to compare the prediction performance of cystatin C (Cys C) and serum creatinine (SCR)-based models. METHODS: The external data set consists of adults receiving vancomycin treatment at The First Affiliated Hospital of Guangxi Medical University. We summarized and restored published models based on serum creatinine values from the literature and used our external data set for initial screening. Visual and external verifications were used to further select candidate models for comparison. The mean prediction error (ME), mean absolute error (MAE) and root mean squared error (RMSE) were the primary outcomes for the overall comparison. Group comparisons of patients with different glomerular filtration rates (GFRs), ages and body mass index (BMI) levels were obtained by the Bayesian method. RESULTS: A total of 156 patients with 233 samples were collected as an external data set. Sixteen published models were summarized and restored. After screening, four candidate models suitable for the external data set were finally obtained for comparison. The cystatin C-based model has a smaller ME value in the overall comparison. In the group comparison, serum creatinine-based models were underestimated in the prediction for patient groups with age ≥ 60 years, abnormal BMI values and GFR < 90 ml/min/1.73 m2, for which the cystatin C-based model could solve this problem. CONCLUSION: After comparison, we suggest that cystatin C is a superior renal function marker to serum creatinine for vancomycin PopPK models.

Development and comparison of population pharmacokinetic models of vancomycin in neurosurgical patients based on two different renal function markers.

WHAT IS KNOWN AND OBJECTIVES: Some previous studies have indicated that serum cystatin C (Cys C) is a better marker than serum creatinine (SCR) for assessing the glomerular filtering rate (GFR). However, in almost all population pharmacokinetic models of vancomycin, the GFR is usually estimated from SCR. Therefore, the aim of this study was to compare the GFR estimated from SCR (sGFR) with the GFR estimated from Cys C (cGFR) and investigate which one can describe the characteristics of vancomycin population pharmacokinetics better in Chinese neurosurgical adult patients. METHODS: Patients from the Neurosurgery Department aged ≥18 years were enrolled retrospectively. Among these patients, the data from 222 patients were used to establish two population pharmacokinetic models based on sGFR and cGFR, separately. The data from another 95 patients were used for the external validation of these two models. Non-linear mixed-effect modelling (NONMEM) 7.4.3 was used for the population pharmacokinetic analysis. RESULTS: We developed two one-compartment models with first-order absorption based on Cys C and SCR, separately. In the Cys C model, age, body weight and cGFR were significant covariates on the clearance rate (CL) of vancomycin (typical value, 6.4 L/hour). In the SCR model, age and sGFR were significant covariates on the CL (typical value, 6.46 L/hour). The external validation results showed that the predictive performance of the two models was similar. WHAT IS NEW AND CONCLUSION: In this study, the predictive performance of two models was similar in neurosurgical patients. We did not find a significant improvement in the predictive performance of the model when GFR was estimated from Cys C.