Impact of covariate model building methods on their clinical relevance evaluation in population pharmacokinetic analyses: comparison of the full model, stepwise covariate model (SCM) and SCM+ approaches

European Medicines Agency (2022) ICH guideline E11A on pediatric extrapolation - Scientific guideline. https://www.ema.europa.eu/en/ich-guideline-e11a-pediatric-extrapolation-scientific-guideline. Accessed 4 Oct 2023

Dartois C, Brendel K, Comets E et al (2007) Overview of model-building strategies in population PK/PD analyses: 2002–2004 literature survey. Br J Clin Pharmacol 64:603–612. https://doi.org/10.1111/j.1365-2125.2007.02975.x

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hutmacher MM, Kowalski KG (2015) Covariate selection in pharmacometric analyses: a review of methods. Br J Clin Pharmacol 79:132–147. https://doi.org/10.1111/bcp.12451

Article  PubMed  Google Scholar 

Ahamadi M, Largajolli A, Diderichsen PM et al (2019) Operating characteristics of stepwise covariate selection in pharmacometric modeling. J Pharmacokinet Pharmacodyn 46:273–285. https://doi.org/10.1007/s10928-019-09635-6

Article  PubMed  Google Scholar 

Jonsson EN, Karlsson MO (1998) Automated covariate model building within NONMEM. Pharm Res 15:1463–1468. https://doi.org/10.1023/a:1011970125687

Article  CAS  PubMed  Google Scholar 

Lindbom L, Pihlgren P, Jonsson N (2005) PsN-Toolkit—a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed 79:241–257. https://doi.org/10.1016/j.cmpb.2005.04.005

Article  PubMed  Google Scholar 

Svensson RJ, Jonsson EN (2022) Efficient and relevant stepwise covariate model building for pharmacometrics. CPT Pharmacomet Syst Pharmacol 11:1210–1222. https://doi.org/10.1002/psp4.12838

Article  CAS  Google Scholar 

Lindbom L, Ribbing J, Jonsson EN (2004) Perl-speaks-NONMEM (PsN)—a Perl module for NONMEM related programming. Comput Methods Programs Biomed 75:85–94. https://doi.org/10.1016/j.cmpb.2003.11.003

Article  PubMed  Google Scholar 

Ayral G, Si Abdallah J-F, Magnard C, Chauvin J (2021) A novel method based on unbiased correlations tests for covariate selection in nonlinear mixed effects models: the COSSAC approach. CPT Pharmacomet Syst Pharmacol 10:318–329. https://doi.org/10.1002/psp4.12612

Article  CAS  Google Scholar 

Mandema JW, Verotta D, Sheiner LB (1992) Building population pharmacokineticpharmacodynamic models. I. Models for covariate effects. J Pharmacokinet Biopharm 20:511–528. https://doi.org/10.1007/BF01061469

Article  CAS  PubMed  Google Scholar 

Ribbing J, Nyberg J, Caster O, Jonsson EN (2007) The lasso—a novel method for predictive covariate model building in nonlinear mixed effects models. J Pharmacokinet Pharmacodyn 34:485–517. https://doi.org/10.1007/s10928-007-9057-1

Article  PubMed  Google Scholar 

Prague M, Lavielle M (2022) SAMBA: A novel method for fast automatic model building in nonlinear mixed-effects models. CPT Pharmacomet Syst Pharmacol 11:161–172. https://doi.org/10.1002/psp4.12742

Article  CAS  Google Scholar 

Terranova N, Venkatakrishnan K, Benincosa LJ (2021) Application of machine learning in translational medicine: current status and future opportunities. AAPS J 23:74. https://doi.org/10.1208/s12248-021-00593-x

Article  PubMed  Google Scholar 

Sibieude E, Khandelwal A, Hesthaven JS et al (2021) Fast screening of covariates in population models empowered by machine learning. J Pharmacokinet Pharmacodyn 48:597–609. https://doi.org/10.1007/s10928-021-09757-w

Article  PubMed  PubMed Central  Google Scholar 

Ronchi D, Tosca EM, Bartolucci R, Magni P (2023) Go beyond the limits of genetic algorithm in daily covariate selection practice. J Pharmacokinet Pharmacodyn. https://doi.org/10.1007/s10928-023-09875-7

Article  PubMed  PubMed Central  Google Scholar 

Xu XS, Yuan M, Zhu H et al (2018) Full covariate modelling approach in population pharmacokinetics: understanding the underlying hypothesis tests and implications of multiplicity. Br J Clin Pharmacol 84:1525–1534. https://doi.org/10.1111/bcp.13577

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gastonguay MR (2011) Full covariate models as an alternative to methods relying on statistical significance for inferences about covariate effects: a review of methodology and 42 case studies. Twentieth Meeting, Population Approach Group in Europe, Athens, Grece. https://www.page-meeting.org/pdf_assets/1694-GastonguayPAGE2011.pdf. Accessed 4 Oct 2023

Yngman G, Nordgren R, Freiberga S, Karlsson MO Linearization of full random effects modeling (FREM) for time-efficient automatic covariate assessment

U.S. Food & Drug Administration (2022) Population pharmacokinetics, guidance for industry. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/population-pharmacokinetics. Accessed 4 Oct 2023

Yngman G, Bjugård Nyberg H, Nyberg J et al (2022) An introduction to the full random effects model. CPT Pharmacomet Syst Pharmacol 11:149–160. https://doi.org/10.1002/psp4.12741

Article  CAS  Google Scholar 

Amann LF, Wicha SG (2023) Operational characteristics of full random effects modelling (‘frem’) compared to stepwise covariate modelling (‘scm’). J Pharmacokinet Pharmacodyn. https://doi.org/10.1007/s10928-023-09856-w

Article  PubMed  PubMed Central  Google Scholar 

European Medicines Agency (2018) Investigation of subgroups in confirmatory clinical trials - Scientific guideline. https://www.ema.europa.eu/en/investigation-subgroups-confirmatory-clinical-trials-scientific-guideline. Accessed 26 Oct 2023

Menon-Andersen D, Yu B, Madabushi R et al (2011) Essential pharmacokinetic information for drug dosage decisions: a concise visual presentation in the drug label. Clin Pharmacol Ther 90:471–474. https://doi.org/10.1038/clpt.2011.149

Article  CAS  PubMed  Google Scholar 

Marier J-F, Teuscher N, Mouksassi M-S (2022) Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package. CPT Pharmacomet Syst Pharmacol 11:1283–1293. https://doi.org/10.1002/psp4.12829

Article  CAS  Google Scholar 

European Medicines Agency (2018) Investigation of bioequivalence - Scientific guideline. https://www.ema.europa.eu/en/investigation-bioequivalence-scientific-guideline. Accessed 4 Oct 2023

Thai H-T, Mentré F, Holford NHG et al (2014) Evaluation of bootstrap methods for estimating uncertainty of parameters in nonlinear mixed-effects models: a simulation study in population pharmacokinetics. J Pharmacokinet Pharmacodyn 41:15–33. https://doi.org/10.1007/s10928-013-9343-z

Article  PubMed  Google Scholar 

Dosne A-G, Bergstrand M, Harling K, Karlsson MO (2016) Improving the estimation of parameter uncertainty distributions in nonlinear mixed effects models using sampling importance resampling. J Pharmacokinet Pharmacodyn 43:583–596. https://doi.org/10.1007/s10928-016-9487-8

Article  PubMed  PubMed Central  Google Scholar 

Cuzick J (2005) Forest plots and the interpretation of subgroups. Lancet 365:1308. https://doi.org/10.1016/S0140-6736(05)61026-4

Article  PubMed  Google Scholar 

Hahn AW, Dizman N, Msaouel P (2022) Missing the trees for the forest: most subgroup analyses using forest plots at the ASCO annual meeting are inconclusive. Ther Adv Med Oncol 14:17588359221103200. https://doi.org/10.1177/17588359221103199

Article  Google Scholar 

Retout S, Schmitt C, Petry C et al (2020) Population pharmacokinetic analysis and exploratory exposure-bleeding rate relationship of emicizumab in adult and pediatric persons with hemophilia A. Clin Pharmacokinet 59:1611–1625. https://doi.org/10.1007/s40262-020-00904-z

Article  CAS  PubMed  PubMed Central  Google Scholar 

Oldenburg J, Mahlangu JN, Kim B et al (2017) Emicizumab prophylaxis in hemophilia A with inhibitors. N Engl J Med 377:809–818. https://doi.org/10.1056/NEJMoa1703068

Article  CAS  PubMed  Google Scholar 

Mahlangu J, Oldenburg J, Paz-Priel I et al (2018) Emicizumab prophylaxis in patients who have hemophilia A without inhibitors. N Engl J Med 379:811–822. https://doi.org/10.1056/NEJMoa1803550

Article  CAS  PubMed  Google Scholar 

Yoneyama K, Schmitt C, Portron A et al (2023) Clinical pharmacology of emicizumab for the treatment of hemophilia A. Expert Rev Clin Pharmacol 16:775–790. https://doi.org/10.1080/17512433.2023.2243213

Article  CAS  PubMed  Google Scholar 

Gallant AR (1975) Seemingly unrelated nonlinear regressions. J Econ 3:35–50. https://doi.org/10.1016/0304-4076(75)90064-0

Article  Google Scholar 

National Center for Advancing Translational Sciences Toolkit. Clinical relevance - Glossary. https://toolkit.ncats.nih.gov/glossary/clinical-relevance. Accessed 17 Nov 2023

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