Literature DB >> 27226147

Model selection versus model averaging in dose finding studies.

Kirsten Schorning1, Björn Bornkamp2, Frank Bretz2, Holger Dette1.   

Abstract

A key objective of Phase II dose finding studies in clinical drug development is to adequately characterize the dose response relationship of a new drug. An important decision is then on the choice of a suitable dose response function to support dose selection for the subsequent Phase III studies. In this paper, we compare different approaches for model selection and model averaging using mathematical properties as well as simulations. We review and illustrate asymptotic properties of model selection criteria and investigate their behavior when changing the sample size but keeping the effect size constant. In a simulation study, we investigate how the various approaches perform in realistically chosen settings. Finally, the different methods are illustrated with a recently conducted Phase II dose finding study in patients with chronic obstructive pulmonary disease.
Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  clinical trials; model averaging; model selection; simulation study

Mesh:

Year:  2016        PMID: 27226147     DOI: 10.1002/sim.6991

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  8 in total

1.  Estimation of QT interval prolongation through model-averaging.

Authors:  Peter L Bonate
Journal:  J Pharmacokinet Pharmacodyn       Date:  2017-04-18       Impact factor: 2.745

2.  Comparison of Model Averaging and Model Selection in Dose Finding Trials Analyzed by Nonlinear Mixed Effect Models.

Authors:  Simon Buatois; Sebastian Ueckert; Nicolas Frey; Sylvie Retout; France Mentré
Journal:  AAPS J       Date:  2018-03-29       Impact factor: 4.009

3.  Model Averaging in Viral Dynamic Models.

Authors:  Antonio Gonçalves; France Mentré; Annabelle Lemenuel-Diot; Jérémie Guedj
Journal:  AAPS J       Date:  2020-02-13       Impact factor: 4.009

4.  Fevipiprant, an oral prostaglandin DP2 receptor (CRTh2) antagonist, in allergic asthma uncontrolled on low-dose inhaled corticosteroids.

Authors:  Eric D Bateman; Alfredo G Guerreros; Florian Brockhaus; Björn Holzhauer; Abhijit Pethe; Richard A Kay; Robert G Townley
Journal:  Eur Respir J       Date:  2017-08-24       Impact factor: 16.671

5.  Optimal designs for frequentist model averaging.

Authors:  K Alhorn; K Schorning; H Dette
Journal:  Biometrika       Date:  2019-07-13       Impact factor: 3.028

6.  New Insights in Computational Methods for Pharmacovigilance: E-Synthesis, a Bayesian Framework for Causal Assessment.

Authors:  Francesco De Pretis; Barbara Osimani
Journal:  Int J Environ Res Public Health       Date:  2019-06-24       Impact factor: 3.390

7.  Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4-5 December 2014).

Authors:  F T Musuamba; E Manolis; N Holford; Sya Cheung; L E Friberg; K Ogungbenro; M Posch; Jwt Yates; S Berry; N Thomas; S Corriol-Rohou; B Bornkamp; F Bretz; A C Hooker; P H Van der Graaf; J F Standing; J Hay; S Cole; V Gigante; K Karlsson; T Dumortier; N Benda; F Serone; S Das; A Brochot; F Ehmann; R Hemmings; I Skottheim Rusten
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2017-07-19

Review 8.  Lessons learned from IDeAl - 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials.

Authors:  Ralf-Dieter Hilgers; Malgorzata Bogdan; Carl-Fredrik Burman; Holger Dette; Mats Karlsson; Franz König; Christoph Male; France Mentré; Geert Molenberghs; Stephen Senn
Journal:  Orphanet J Rare Dis       Date:  2018-05-11       Impact factor: 4.123

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.