Trial reportClinical pharmacokinetics2005
Pharmacokinetic study of tacrolimus in cystic fibrosis and non-cystic fibrosis lung transplant patients and design of Bayesian estimators using limited sampling strategies.
Trial report in Clinical pharmacokinetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
31 citing papers in PubMed, 4 syntheses or guidelines pooled it, 63 citations in OpenAlex.
- Model-Informed Precision Dosing of Tacrolimus: A Systematic Review of Population Pharmacokinetic Models and a Benchmark Study of Software Tools.Clinical pharmacokinetics · 2024Pooled it
- Pharmacokinetics in Patients with Cystic Fibrosis: A Systematic Review of Data Published Between 1999 and 2019.Clinical pharmacokinetics · 2020Pooled it
- Population Pharmacokinetic Models of Tacrolimus in Adult Transplant Recipients: A Systematic Review.Clinical pharmacokinetics · 2020Pooled it
- Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach.British journal of clinical pharmacology · 2019Pooled it
- Population pharmacokinetic model and Bayesian estimator for 2 tacrolimus formulations in adult liver transplant patients.British journal of clinical pharmacology · 2019Trial
- Population Pharmacokinetics and Bayesian Estimators for Refined Dose Adjustment of a New Tacrolimus Formulation in Kidney and Liver Transplant Patients.Clinical pharmacokinetics · 2017Trial
- Bayesian estimation of mycophenolate mofetil in lung transplantation, using a population pharmacokinetic model developed in kidney and lung transplant recipients.Clinical pharmacokinetics · 2012Trial
- Analytical Models to Optimize Tacrolimus Dosing in Solid Organ Transplantation: A Systematic Review.Pharmaceutics · 2026Review
- Population pharmacokinetic characteristics of tacrolimus in Chinese lung transplant recipients and optimisation of dosing regimen during the early post-transplantation phase.European journal of clinical pharmacology · 2025Article
- Tacrolimus overdosing in lung transplant recipients: clinical manifestations and management.Journal of thoracic disease · 2025Article
- Development and validation of a population pharmacokinetic model to guide perioperative tacrolimus dosing after lung transplantation.JHLT open · 2024Article
- Pharmacokinetic Evaluation of Tacrolimus in Chinese Adult Patients during the Early Stages Post-Lung Transplantation.Journal of personalized medicine · 2023Article
- Clinical Pharmacokinetics and Bayesian Estimators for the Individual Dose Adjustment of a Generic Formulation of Tacrolimus in Adult Kidney Transplant Recipients.Clinical pharmacokinetics · 2021Article
- Tacrolimus monitoring parameters are not associated with acute cellular rejection following lung transplantation.European journal of clinical pharmacology · 2021Article
- High Variability of Whole-Blood Tacrolimus Pharmacokinetics Early After Thoracic Organ Transplantation.European journal of drug metabolism and pharmacokinetics · 2020Article
- Tacrolimus exposure early after lung transplantation and exploratory associations with acute cellular rejection.European journal of clinical pharmacology · 2019Observational
- The impact of tacrolimus exposure on extrarenal adverse effects in adult renal transplant recipients.British journal of clinical pharmacology · 2019Observational
- A Limited Sampling Strategy to Estimate Exposure of Everolimus in Whole Blood and Peripheral Blood Mononuclear Cells in Renal Transplant Recipients Using Population Pharmacokinetic Modeling and Bayesian Estimators.Clinical pharmacokinetics · 2018Article
- Genotypes associated with tacrolimus pharmacokinetics impact clinical outcomes in lung transplant recipients.Clinical transplantation · 2018Article
- Tacrolimus Updated Guidelines through popPK Modeling: How to Benefit More from CYP3A Pre-emptive Genotyping Prior to Kidney Transplantation.Frontiers in pharmacology · 2017Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo: (i) test different pharmacokinetic models to fit full tacrolimus concentration-time profiles; (ii) estimate the tacrolimus pharmacokinetic characteristics in stable lung transplant patients with or without cystic fibrosis (CF); (iii) compare the pharmacokinetic parameters between these two patient groups; and (iv) design maximum a posteriori Bayesian estimators (MAP-BE) for pharmacokinetic forecasting in these patients using a limited sampling strategy.
methodsTacrolimus blood concentration-time profiles obtained on three occasions within a 5-day period in 22 adult lung transplant recipients (11 with CF and 11 without CF) were retrospectively studied. Three different one-compartment models with first-order elimination were tested to fit the data: one with first-order absorption, one convoluted with a gamma distribution to describe the absorption phase, and one convoluted with a double gamma distribution able to describe secondary concentration peaks. Finally, Bayesian estimation using the best model and a limited sampling strategy was tested in the two groups of patients for its ability to provide accurate estimates of the main tacrolimus pharmacokinetic parameters and exposure indices.
resultsThe one-compartment model with first-order elimination convoluted with a double gamma distribution gave the best results in both CF and non-CF lung transplant recipients. The patients with CF required higher doses of tacrolimus than those without CF to achieve similar drug exposure, and population modelling had to be performed in CF and non-CF patients separately. Accurate Bayesian estimates of area under the blood concentration-time curve from 0 to 12 hours (AUC12), AUC from 0 to 4 hours, peak blood concentration (Cmax) and time to reach Cmax were obtained using three blood samples collected at 0, 1 and 3 hours in non-CF patients (correlation coefficient between observed and estimated AUC12, R2 = 0.96), and at 0, 1.5 and 4 hours in CF patients (R2 = 0.91).
conclusionA particular pharmacokinetic model was designed to fit the complex and highly variable tacrolimus blood concentration-time profiles. Moreover, MAP-BE allowing tacrolimus therapeutic drug monitoring based on AUC12 were developed.
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