ArticleBritish journal of clinical pharmacology2016
External evaluation of published population pharmacokinetic models of tacrolimus in adult renal transplant recipients.
Article in British journal of clinical pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 7 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
63 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Relevance-Based Score for MIPD Model Selection: Systematic Review and External Evaluation of popPK Tacrolimus Models in Adult Transplant Recipients.CPT: pharmacometrics & systems pharmacology · 2026Pooled it
- Accelerating tacrolimus model-informed precision dosing in kidney transplant recipients: Model evaluation and refinement strategies.British journal of clinical pharmacology · 2026Pooled it
- Published Population Pharmacokinetic Models of Imatinib Perform Poorly on TDM Data from Pediatric Patients.Targeted oncology · 2025Pooled it
- Population pharmacokinetic analyses of tacrolimus in non-transplant patients: a systematic review.European journal of clinical pharmacology · 2023Pooled 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
- Systematic external evaluation of published population pharmacokinetic models of mycophenolate mofetil in adult kidney transplant recipients co-administered with tacrolimus.British journal of clinical pharmacology · 2019Pooled it
- Evaluation of the performance of a prior tacrolimus population pharmacokinetic kidney transplant model among adult allogeneic hematopoietic stem cell transplant patients.Clinical and translational science · 2021Trial
- Comparing the Predictive Performance of Machine Learning Models with a Newly Developed Population Pharmacokinetic Model for Busulfan in Paediatric Patients.Clinical pharmacokinetics · 2026Article
- Vancomycin optimised dosing regimens for critically ill patients receiving renal replacement therapy.Critical care (London, England) · 2026Article
- External evaluation of population pharmacokinetic models for tacrolimus in kidney transplant recipients: implications for model-informed precision dosing.BMC nephrology · 2026Article
- Defining Optimal Sampling Strategies for Cefepime Model-Informed Precision Dosing.Therapeutic drug monitoring · 2026Article
- Mechanism-informed machine learning for individualized tacrolimus dose adjustment in the early post-kidney transplant period.British journal of clinical pharmacology · 2026Article
- Bayesian Dosing Simulator (BDS): A Pharmacokinetic Modeling Tool for Optimized Antibiotic Therapy.Pharmacotherapy · 2026Article
- Leveraging Model-Informed Drug Development to Predict Asciminib Efficacy in Second-Line Treatment of Chronic Myeloid Leukemia in Chronic Phase.Clinical pharmacokinetics · 2026Article
- Analytical Models to Optimize Tacrolimus Dosing in Solid Organ Transplantation: A Systematic Review.Pharmaceutics · 2026Review
- External Pharmacokinetic Model Evaluation of Caffeine in Critically Ill Neonates With Heart Disease Using Data Collected From a Pragmatic Platform Trial.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2026Article
- Article
- A multifactorial approach to tacrolimus therapeutic drug monitoring in complex liver transplantation: a case report.Frontiers in medicine · 2026Article
- Exploring the comprehensive factors influencing tacrolimus pharmacokinetics in early renal transplant recipients: A population pharmacokinetic analysis.European journal of clinical pharmacology · 2025Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimSeveral tacrolimus population pharmacokinetic models in adult renal transplant recipients have been established to facilitate dose individualization. However, their applicability when extrapolated to other clinical centres is not clear. This study aimed to (1) evaluate model external predictability and (2) analyze potential influencing factors.
methodsPublished models were screened from the literature and were evaluated using an external dataset with 52 patients (609 trough samples) collected by postoperative day 90 via methods that included (1) prediction-based prediction error (PE%), (2) simulation-based prediction- and variability-corrected visual predictive check (pvcVPC) and normalized prediction distribution error (NPDE) tests and (3) Bayesian forecasting to assess the influence of prior observations on model predictability. The factors influencing model predictability, particularly the impact of structural models, were evaluated.
resultsSixteen published models were evaluated. In prediction-based diagnostics, the PE% within ±30% was less than 50% in all models, indicating unsatisfactory predictability. In simulation-based diagnostics, both the pvcVPC and the NPDE indicated model misspecification. Bayesian forecasting improved model predictability significantly with prior 2-3 observations. The various factors influencing model extrapolation included bioassays, the covariates involved (CYP3A5*3 polymorphism, postoperative time and haematocrit) and whether non-linear kinetics were used.
conclusionsThe published models were unsatisfactory in prediction- and simulation-based diagnostics, thus inappropriate for direct extrapolation correspondingly. However Bayesian forecasting could improve the predictability considerably with priors. The incorporation of non-linear pharmacokinetics in modelling might be a promising approach to improving model predictability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.