Literature DB >> 17037263

Design and analysis of dose-finding studies combining multiple comparisons and modeling procedures.

José Pinheiro1, Björn Bornkamp, Frank Bretz.   

Abstract

The search for an adequate dose involves some of the most complex series of decisions to be made in developing a clinically viable product. Typically decisions based on such dose-finding studies reside in two domains: (i) "proof" of evidence that the treatment is effective and (ii) the need to choose dose(s) for further development. We consider a unified strategy for designing and analyzing dose-finding studies, including the testing of proof-of-concept and the selection of one or more doses to take into further development. The methodology combines the advantages of multiple comparisons and modeling approaches, consisting of a multi-stage procedure. Proof-of-concept is tested in the first stage, using multiple comparison methods to identify statistically significant contrasts corresponding to a set of candidate models. If proof-of-concept is established in the first stage, the best model is then used for dose selection in subsequent stages. This article describes and illustrates practical considerations related to the implementation of this methodology. We discuss how to determine sample sizes and perform power calculations based on the proof-of-concept step. A relevant topic in this context is how to obtain good prior values for the model parameters: different methods to translate prior clinical knowledge into parameter values are presented and discussed. In addition, different possibilities of performing sensitivity analyses to assess the consequences of misspecifying the true parameter values are introduced. All methods are illustrated by a real dose-response phase II study for an anti-anxiety compound.

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Year:  2006        PMID: 17037263     DOI: 10.1080/10543400600860428

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  12 in total

1.  Optimizing Sedative Dose in Preterm Infants Undergoing Treatment for Respiratory Distress Syndrome.

Authors:  Peter F Thall; Hoang Q Nguyen; Sarah Zohar; Pierre Maton
Journal:  J Am Stat Assoc       Date:  2014-09-01       Impact factor: 5.033

2.  An example of optimal phase II design for exposure response modelling.

Authors:  Alan Maloney; Marloes Schaddelee; Jan Freijer; Walter Krauwinkel; Marcel van Gelderen; Philippe Jacqmin; Ulrika S H Simonsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-09-25       Impact factor: 2.745

3.  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

4.  An adaptive two-stage dose-response design method for establishing proof of concept.

Authors:  Yoko Franchetti; Stewart J Anderson; Allan R Sampson
Journal:  J Biopharm Stat       Date:  2013       Impact factor: 1.051

5.  The feasibility of serving liquid yoghurt supplemented with probiotic bacteria, Lactobacillus rhamnosus LB 21, and Lactococcus lactis L1A--a pilot study among old people with dementia in a residential care facility.

Authors:  M Carlsson; Y Gustafson; L Haglin; S Eriksson
Journal:  J Nutr Health Aging       Date:  2009-11       Impact factor: 4.075

6.  Fulranumab for treatment of diabetic peripheral neuropathic pain: A randomized controlled trial.

Authors:  Hao Wang; Gary Romano; Mary Ellen Frustaci; Norm Bohidar; Huizhong Ma; Panna Sanga; Seth Ness; Lucille J Russell; Margaret Fedgchin; Kathleen M Kelly; John Thipphawong
Journal:  Neurology       Date:  2014-07-09       Impact factor: 9.910

7.  Locally Optimal Designs for Some Dose-Response Models With Continuous Endpoints.

Authors:  Yi Zhai; Zhide Fang
Journal:  Commun Stat Theory Methods       Date:  2017-10-23       Impact factor: 0.893

8.  Spline-based procedures for dose-finding studies with active control.

Authors:  Hans-Joachim Helms; Norbert Benda; Jörg Zinserling; Thomas Kneib; Tim Friede
Journal:  Stat Med       Date:  2014-10-16       Impact factor: 2.373

9.  Point and Interval Estimators of the Target Dose in Clinical Dose-Finding Studies with Active Control.

Authors:  H-J Helms; N Benda; T Friede
Journal:  J Biopharm Stat       Date:  2014-06-11       Impact factor: 1.051

10.  A randomized, double-blind, placebo-controlled, dose-ranging study of lisdexamfetamine dimesylate augmentation for major depressive disorder in adults with inadequate response to antidepressant therapy.

Authors:  Cynthia Richards; Dan V Iosifescu; Rajnish Mago; Elias Sarkis; James Reynolds; Brooke Geibel; Matthew Dauphin
Journal:  J Psychopharmacol       Date:  2017-08-31       Impact factor: 4.153

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