ArticleThe AAPS journal2012
Shrinkage in nonlinear mixed-effects population models: quantification, influencing factors, and impact.
Article in The AAPS journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Population pharmacokinetic analysis of abiraterone in chemotherapy-naïve and docetaxel-treated patients with metastatic castration-resistant prostate cancer.Clinical pharmacokinetics · 2014Trial
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- Integrated Population Pharmacokinetic Analysis of Intravitreal Aflibercept Drug Products.CPT: pharmacometrics & systems pharmacology · 2026Article
- Assessing the Validity of the Fellow Eye as an Internal Control in Early-Phase Clinical Trials for Myopic Chorioretinal Atrophy.Journal of clinical medicine · 2026Article
- Nonlinear Mixed-Effects Modeling to Characterize the Pharmacokinetics of a Novel Mithramycin Analogue for Ewing Sarcoma in Mice.Research square · 2026Article
- Population Pharmacokinetics of Propofol in Critically Ill Patients with and Without Extracorporeal Membrane Oxygenation.Clinical pharmacokinetics · 2026Observational
- Population Pharmacokinetics and Exposure-Response Analysis of Voriconazole in ICU and Non-ICU Hospitalized Adults.Infection and drug resistance · 2026Article
- Individual Differences in Developmental Trajectories of Global and Subcortical Brain Volumes Between Late Childhood and Late Adolescence: Findings From a 12-Wave Neuroimaging Study.Human brain mapping · 2025Article
- Pharmacokinetics of betamethasone in pre-eclampsia: An in vivo and ex vivo study.British journal of clinical pharmacology · 2025Article
- Target-Mediated Modeling of Alirocumab in Adolescents and Children ≥8 to <12 Years of Age Using Phase II and III Data.Clinical pharmacology in drug development · 2025Article
- Amikacin dosing in neonates: evaluation of target attainment using a simplified and complex pharmacokinetic model-derived dosing regimen in clinical practice.Antimicrobial agents and chemotherapy · 2025Article
- Drug-drug interaction of phenytoin sodium and methylprednisolone on voriconazole: a population pharmacokinetic model in children with thalassemia undergoing allogeneic hematopoietic stem cell transplantation.European journal of clinical pharmacology · 2025Article
- Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab.Frontiers in pharmacology · 2025Article
- Trilaciclib dosage in Chinese patients with extensive-stage small cell lung cancer: a pooled pharmacometrics analysis.Acta pharmacologica Sinica · 2024Article
- Translational pharmacokinetic/pharmacodynamic model for mRNA-0184, an investigational therapeutic for the treatment of heart failure.Clinical and translational science · 2024Article
- Toward Model-Based Informed Precision Dosing of Vancomycin in Hematologic Cancer Patients: A First Step.Clinical pharmacokinetics · 2024Article
- Individualized dosing parameters for tacrolimus in the presence of voriconazole: a real-world PopPK study.Frontiers in pharmacology · 2024Article
- "De-Shrinking" EBEs: The Solution for Bayesian Therapeutic Drug Monitoring.Clinical pharmacokinetics · 2022Article
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6 authors.
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Abstract
Shrinkage of empirical Bayes estimates (EBEs) of posterior individual parameters in mixed-effects models has been shown to obscure the apparent correlations among random effects and relationships between random effects and covariates. Empirical quantification equations have been widely used for population pharmacokinetic/pharmacodynamic models. The objectives of this manuscript were (1) to compare the empirical equations with theoretically derived equations, (2) to investigate and confirm the influencing factor on shrinkage, and (3) to evaluate the impact of shrinkage on estimation errors of EBEs using Monte Carlo simulations. A mathematical derivation was first provided for the shrinkage in nonlinear mixed effects model. Using a linear mixed model, the simulation results demonstrated that the shrinkage estimated from the empirical equations matched those based on the theoretically derived equations. Simulations with a two-compartment pharmacokinetic model verified that shrinkage has a reversed relationship with the relative ratio of interindividual variability to residual variability. Fewer numbers of observations per subject were associated with higher amount of shrinkage, consistent with findings from previous research. The influence of sampling times appeared to be larger when fewer PK samples were collected for each individual. As expected, sample size has very limited impact on shrinkage of the PK parameters of the two-compartment model. Assessment of estimation error suggested an average 1:1 relationship between shrinkage and median estimation error of EBEs.
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