ArticleJournal of pharmacokinetics and pharmacodynamics2020
Assessing parameter uncertainty in small-n pharmacometric analyses: value of the log-likelihood profiling-based sampling importance resampling (LLP-SIR) technique.
Article in Journal of pharmacokinetics and pharmacodynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
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- Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice.British journal of clinical pharmacology · 2025Review
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- Bayesian estimation in NONMEM.CPT: pharmacometrics & systems pharmacology · 2024Article
- Effect of albumin substitution on pharmacokinetics of piperacillin/tazobactam in patients with severe burn injury admitted to the ICU.The Journal of antimicrobial chemotherapy · 2024Article
- Impact of Key Components of Intensified Ceftaroline Dosing on Pharmacokinetic/Pharmacodynamic Target Attainment.Clinical pharmacokinetics · 2024Article
- Operational characteristics of full random effects modelling ('frem') compared to stepwise covariate modelling ('scm').Journal of pharmacokinetics and pharmacodynamics · 2023Article
- Pharmacokinetics of Ribavirin in the Treatment of Lassa Fever: An Observational Clinical Study at the Irrua Specialist Teaching Hospital, Edo State, Nigeria.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Observational
- Pilot Pharmacokinetic Study in Healthy Adults Using Intravascular Microdialysis Catheters Modified for Use in Paediatric Patients to Assess Vancomycin Blood Levels.Clinical pharmacokinetics · 2023Article
- Ciprofloxacin in Patients Undergoing Extracorporeal Membrane Oxygenation (ECMO): A Population Pharmacokinetic Study.Pharmaceutics · 2022Article
- Tigecycline Dosing Strategies in Critically Ill Liver-Impaired Patients.Antibiotics (Basel, Switzerland) · 2022Article
- Voriconazole Pharmacokinetics Are Not Altered in Critically Ill Patients with Acute-on-Chronic Liver Failure and Continuous Renal Replacement Therapy: An Observational Study.Microorganisms · 2021Article
- Conditional Non-parametric Bootstrap for Non-linear Mixed Effect Models.Pharmaceutical research · 2021Article
- An Integrated Dialysis Pharmacometric (IDP) Model to Evaluate the Pharmacokinetics in Patients Undergoing Renal Replacement Therapy.Pharmaceutical research · 2020Article
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Abstract
Assessing parameter uncertainty is a crucial step in pharmacometric workflows. Small datasets with ten or fewer subjects appear regularly in drug development and therapeutic use, but it is unclear which method to assess parameter uncertainty is preferable in such situations. The aim of this study was to (i) systematically evaluate the performance of standard error (SE), bootstrap (BS), log-likelihood profiling (LLP), Bayesian approaches (BAY) and sampling importance resampling (SIR) to assess parameter uncertainty in small datasets and (ii) to evaluate methods to provide proposal distributions for the SIR. A simulation study was conducted and the 0-95% confidence interval (CI) and coverage for each parameter was evaluated and compared to reference CIs derived by stochastic simulation and estimation (SSE). A newly proposed LLP-SIR, combining the proposal distribution provided by LLP with SIR, was included in addition to conventional SE-SIR and BS-SIR. Additionally, the methods were applied to a clinical dataset. The determined CIs differed substantially across the methods. The CIs of SE, BS, LLP and BAY were not in line with the reference in datasets with ≤ 10 subjects. The best alignment was found for the LLP-SIR, which also provided the best coverage results among the SIR methods. The best overall results regarding the coverage were provided by LLP and BAY across all parameters and dataset sizes. To conclude, the popular SE and BS methods are not suitable to derive parameter uncertainty in small datasets containing ≤ 10 subjects, while best performances were observed with LLP, BAY and LLP-SIR.
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