Academic Journal
Using Stochastic Simulation-Estimation and Automated Model Development to Assess Power and Accuracy for Covariate Identification.
| Τίτλος: | Using Stochastic Simulation-Estimation and Automated Model Development to Assess Power and Accuracy for Covariate Identification. |
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| Συγγραφείς: | Hsu YH; Department of Pharmacy, Uppsala University, Uppsala, Sweden., Costa B; Department of Pharmacy, Uppsala University, Uppsala, Sweden.; PerMed Research Group, RISE-Health, Faculty of Medicine, University of Porto, Porto, Portugal.; RISE-Health, Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal.; Laboratory of Personalized Medicine, Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal., Vale N; PerMed Research Group, RISE-Health, Faculty of Medicine, University of Porto, Porto, Portugal.; RISE-Health, Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal.; Laboratory of Personalized Medicine, Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal., Dorlo TPC; Department of Pharmacy, Uppsala University, Uppsala, Sweden., Karlsson MO; Department of Pharmacy, Uppsala University, Uppsala, Sweden.; Centre for Parasite Biology and Immunology, Department of Infectious Diseases, National Health Institute Dr. Ricardo Jorge, Lisbon, Portugal. |
| Πηγή: | CPT: pharmacometrics & systems pharmacology [CPT Pharmacometrics Syst Pharmacol] 2026 Aug; Vol. 15 (8), pp. e70299. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Wiley Country of Publication: United States NLM ID: 101580011 Publication Model: Print Cited Medium: Internet ISSN: 2163-8306 (Electronic) Linking ISSN: 21638306 NLM ISO Abbreviation: CPT Pharmacometrics Syst Pharmacol Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2015- : Hoboken, NJ : Wiley Original Publication: New York, NY : Nature Pub. Group |
| Ιατρικοί όροι (MeSH): | Computer Simulation* , Models, Biological* , Pharmacokinetics*, Stochastic Processes ; Humans ; Research Design |
| Περίληψη: | When study designs are evaluated using clinical trial simulations for their ability to identify covariate effects in population pharmacokinetic (PopPK) modeling, it is typically assumed that the true model will be known at the data analysis stage. In this study, this was compared with the more realistic assumption that the PopPK model needs to be built on the data generated by the planned study. Three approaches were compared: (i) stochastic simulation and re-estimation (SSE) with the simulation model, (ii) automated model development (AMD) with exploratory covariate search (AMD-exploratory), and (iii) AMD forcing the covariate effect into the model from the start and reevaluating it in the end (AMD-structural). With a simulated covariate effect (a hypothetical pregnancy effect on clearance), we assessed (i) the type 1 error (T1E) and the power of covariate identification and (ii) covariate parameter accuracy. The T1E rate was controlled in SSE and AMD-exploratory but 20% inflated for AMD-structural. The power of covariate identification in rich, medium, and sparse designs was (i) 99%, 100%, and 79% in SSE, (ii) 74%, 72%, and 41% in AMD-exploratory, and (iii) 92%, 93%, and 80% in AMD-structural. Sparse designs amplified power differences between strategies, with AMD-exploratory often selecting alternative or no covariates. The rRMSE of covariate parameter estimates was lowest in SSE (27%, 22%, and 42%), followed by AMD-exploratory (34%, 26%, and 49%) and then AMD-structural (42%, 47%, and 60%). SSE provides optimistic power estimates as model building is data-driven, while AMD-based approaches incorporate model uncertainty and reflect real-world analysis conditions. (© 2026 The Author(s). CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.) |
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| Contributed Indexing: | Keywords: automated model development (AMD); covariate identification; model building; power analysis; stochastic simulation and estimation (SSE); study design evaluation |
| Entry Date(s): | Date Created: 20260721 Date Completed: 20260721 Latest Revision: 20260721 |
| Update Code: | 20260722 |
| DOI: | 10.1002/psp4.70299 |
| PMID: | 42481919 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 2163-8306 |
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| DOI: | 10.1002/psp4.70299 |