Literature DB >> 18680164

Two-stage design for dose-finding that accounts for both efficacy and safety.

Vladimir Dragalin1, Valerii V Fedorov, Yuehui Wu.   

Abstract

We introduce a two-stage design for dose-finding in the context of Phase I/II studies, where two binary correlated endpoints are available, for instance, one for efficacy and one for toxicity. The bivariate probit model is used as a working model for the dose-response relationship. Given a 'desirable point' for the marginal probabilities of efficacy and toxicity, the goal is to find the target dose that is 'closest' to the desirable point. The criterion of optimality (objective function) is the variance of the estimator for that dose. Optimal experimental design methodology is used to construct efficient dose allocation procedures that treat patients in the study at doses that are both safe and efficacious. Copyright 2008 John Wiley & Sons, Ltd.

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Year:  2008        PMID: 18680164     DOI: 10.1002/sim.3356

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


  13 in total

1.  Implementing Optimal Designs for Dose-Response Studies Through Adaptive Randomization for a Small Population Group.

Authors:  Yevgen Ryeznik; Oleksandr Sverdlov; Andrew C Hooker
Journal:  AAPS J       Date:  2018-07-19       Impact factor: 4.009

2.  Practical considerations for optimal designs in clinical dose finding studies.

Authors:  Frank Bretz; Holger Dette; Jose C Pinheiro
Journal:  Stat Med       Date:  2010-03-30       Impact factor: 2.373

3.  Adaptive Optimal Designs for Dose-Finding Studies with Time-to-Event Outcomes.

Authors:  Yevgen Ryeznik; Oleksandr Sverdlov; Andrew C Hooker
Journal:  AAPS J       Date:  2017-12-28       Impact factor: 4.009

4.  Optimal designs for active controlled dose-finding trials with efficacy-toxicity outcomes.

Authors:  K Schorning; H Dette; K Kettelhake; W K Wong; F Bretz
Journal:  Biometrika       Date:  2017-10-09       Impact factor: 2.445

5.  Statistical justification of expansion cohorts in phase 1 cancer trials.

Authors:  Ali A Mokdad; Xian-Jin Xie; Hong Zhu; David E Gerber; Daniel F Heitjan
Journal:  Cancer       Date:  2018-07-05       Impact factor: 6.860

6.  A latent variable model for improving inference in trials assessing the effect of dose on toxicity and composite efficacy endpoints.

Authors:  James Ms Wason; Shaun R Seaman
Journal:  Stat Methods Med Res       Date:  2019-02-25       Impact factor: 3.021

7.  Adaptive Clinical Trials: Overview of Early-Phase Designs and Challenges.

Authors:  Olga Marchenko; Valerii Fedorov; J Jack Lee; Christy Nolan; José Pinheiro
Journal:  Ther Innov Regul Sci       Date:  2013-11-26       Impact factor: 1.778

8.  The effect of using a robust optimality criterion in model based adaptive optimization.

Authors:  Eric A Strömberg; Andrew C Hooker
Journal:  J Pharmacokinet Pharmacodyn       Date:  2017-04-06       Impact factor: 2.745

9.  Dose-finding based on bivariate efficacy-toxicity outcome using Archimedean Copula.

Authors:  Yuxi Tao; Junlin Liu; Zhihui Li; Jinguan Lin; Tao Lu; Fangrong Yan
Journal:  PLoS One       Date:  2013-11-12       Impact factor: 3.240

10.  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
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