Evidence map›Paper›PMID 40730936›Full record

ArticleEuropean journal of drug metabolism and pharmacokinetics2025

Population Pharmacokinetic Model Evaluation with a Small Real-World Dataset Versus a Large Virtual Dataset: Does Sample Size Affect Decision-Making?

Mehdi El Hassani, Daniel J G Thirion, Amélie Marsot

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Article in European journal of drug metabolism and pharmacokinetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
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1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Mehdi El HassaniFaculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada. mehdi.el.hassani@umontreal.ca.ORCID http://orcid.org/0000-0003-4314-5368
Daniel J G ThirionFaculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada.
Amélie MarsotFaculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveIn a recent simulation-based study, we found that sample size had minimal influence on the external evaluation of population pharmacokinetic (PK) models. However, the applicability of these findings to clinical data remains unexplored. This study aims to validate our previous simulation-based results using real-world clinical data.

methodsData from a prospective clinical study in the > 75-year-old population admitted to the McGill University Health Center (MUHC) receiving piperacillin/tazobactam were collected. A virtual population of 1000 patients representative of the characteristics of MUHC patients was also simulated. A population PK model was externally evaluated both using the small clinical dataset and a larger simulated dataset. The predictive performance of the model was assessed using bias, imprecision, goodness-of-fit plots (GOF), and prediction-corrected visual predictive checks (pcVPC). The distribution of prediction errors between the clinical and simulated datasets was compared using the Wilcoxon rank-sum test.

resultsData from 13 patients undergoing piperacillin/tazobactam therapy were collected. The Ishihara et al. model showed low bias (2.4% population, 0.5% individual) and imprecision (23.8% and 3.2%) and was therefore chosen for Monte Carlo simulation of the virtual population. The Hemmersbach-Miller et al. model showed bias values of - 37.8% (population) and - 21.4% (individual), with imprecision values of 43.2% (population) and 31.3% (individual) for the clinical dataset. For the simulated population, bias values were - 28.4% (population) and - 13.9% (individual), with imprecision values of 40.2% (population) and 18.1% (individual). No significant difference was observed between the prediction error distributions of the clinical and simulated datasets. Both GOF plots and pcVPCs showed similar model misspecification across the clinical and simulated datasets.

conclusionsThis study confirms that small clinical datasets may be used to externally evaluate population PK models.

Indexed as

Anti-Bacterial AgentsDecision MakingModels, BiologicalAgedAged, 80 and overComputer SimulationFemaleHumansMalePiperacillinPiperacillin, Tazobactam Drug CombinationProspective StudiesSample SizeAnti-Bacterial AgentsPiperacillinPiperacillin, Tazobactam Drug CombinationModelingPiperacillinSimulation

Identifiers

PMID40730936

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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.