ArticleThe AAPS journal2018
Comparison of Model Averaging and Model Selection in Dose Finding Trials Analyzed by Nonlinear Mixed Effect Models.
Article in The AAPS journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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
15 citing papers in PubMed.
- Improved Confidence in a Confirmatory Stage by Application of Item-Based Pharmacometrics Model: Illustration with a Phase III Active Comparator-Controlled Trial in COPD Patients.Pharmaceutical research · 2022Trial
- Improved Decision-Making Confidence Using Item-Based Pharmacometric Model: Illustration with a Phase II Placebo-Controlled Trial.The AAPS journal · 2021Trial
- Methodologies for Population Pharmacokinetic Modeling of Target-Site Drug Exposure: A Narrative Review of Current Strategies.Clinical pharmacokinetics · 2026Review
- Comparing randomized trial designs to estimate treatment effect in rare diseases with longitudinal models: a simulation study showcased by Autosomal Recessive Cerebellar Ataxias using the SARA score.BMC medical research methodology · 2025Article
- Overcoming Model Uncertainty - How Equivalence Tests Can Benefit From Model Averaging.Statistics in medicine · 2025Article
- Evaluation of model-integrated evidence approaches for pharmacokinetic bioequivalence studies using model averaging methods.CPT: pharmacometrics & systems pharmacology · 2024Article
- Development and comparison of model-integrated evidence approaches for bioequivalence studies with pharmacokinetic end points.CPT: pharmacometrics & systems pharmacology · 2024Article
- Comparison of Seven Non-Linear Mixed Effect Model-Based Approaches to Test for Treatment Effect.Pharmaceutics · 2023Article
- Optimization of trial duration to predict long-term HbA1c change with therapy: A pharmacometrics simulation-based evaluation.CPT: pharmacometrics & systems pharmacology · 2022Article
- Impact of model misspecification on model-based tests in PK studies with parallel design: real case and simulation studies.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- SAMBA: A novel method for fast automatic model building in nonlinear mixed-effects models.CPT: pharmacometrics & systems pharmacology · 2022Article
- Conditional Non-parametric Bootstrap for Non-linear Mixed Effect Models.Pharmaceutical research · 2021Article
- New Model-Based Bioequivalence Statistical Approaches for Pharmacokinetic Studies with Sparse Sampling.The AAPS journal · 2020Article
- Model Averaging in Viral Dynamic Models.The AAPS journal · 2020Article
- Optimal designs for frequentist model averaging.Biometrika · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In drug development, pharmacometric approaches consist in identifying via a model selection (MS) process the model structure that best describes the data. However, making predictions using a selected model ignores model structure uncertainty, which could impair predictive performance. To overcome this drawback, model averaging (MA) takes into account the uncertainty across a set of candidate models by weighting them as a function of an information criterion. Our primary objective was to use clinical trial simulations (CTSs) to compare model selection (MS) with model averaging (MA) in dose finding clinical trials, based on the AIC information criterion. A secondary aim of this analysis was to challenge the use of AIC by comparing MA and MS using five different information criteria. CTSs were based on a nonlinear mixed effect model characterizing the time course of visual acuity in wet age-related macular degeneration patients. Predictive performances of the modeling approaches were evaluated using three performance criteria focused on the main objectives of a phase II clinical trial. In this framework, MA adequately described the data and showed better predictive performance than MS, increasing the likelihood of accurately characterizing the dose-response relationship and defining the minimum effective dose. Moreover, regardless of the modeling approach, AIC was associated with the best predictive performances.
Indexed as
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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.