Literature DB >> 10407255

Combining different phases in the development of medical treatments within a single trial.

P Bauer1, M Kieser.   

Abstract

In the development of medical treatments, identification of promising therapies and inference on selected treatments are usually performed in subsequent separate trials. An adaptive two-stage design is proposed for the situation of multiple treatments to be compared with a control, allowing integration of both steps within a single confirmatory trial controlling the multiple level alpha. After the interim analysis, the trial may be terminated early or is continued with a second stage, where the set of treatments may be reduced due to lack of efficacy or to safety problems. The procedure is highly flexible with respect to the distributional assumptions, stopping rules and selection criteria and allows a completely free recalculation of the sample size for the second stage. Simulations show that the method may be substantially more powerful than classical one-stage multiple treatment designs with the same total sample size. As in conventional strategies with a series of separate experiments, a reasonable selection strategy has to be applied in order to prevent proceeding with non-optimal treatments. Copyright 1999 John Wiley & Sons, Ltd.

Mesh:

Year:  1999        PMID: 10407255     DOI: 10.1002/(sici)1097-0258(19990730)18:14<1833::aid-sim221>3.0.co;2-3

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


  40 in total

1.  The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design.

Authors:  Munyaradzi Dimairo; Philip Pallmann; James Wason; Susan Todd; Thomas Jaki; Steven A Julious; Adrian P Mander; Christopher J Weir; Franz Koenig; Marc K Walton; Jon P Nicholl; Elizabeth Coates; Katie Biggs; Toshimitsu Hamasaki; Michael A Proschan; John A Scott; Yuki Ando; Daniel Hind; Douglas G Altman
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Review 2.  Relative efficacy of drugs: an emerging issue between regulatory agencies and third-party payers.

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3.  [Modern study designs and analysis methods in clinical research].

Authors:  J Gerß; M Eveslage; A Faldum; R Schmidt
Journal:  Z Rheumatol       Date:  2015-03       Impact factor: 1.372

Review 4.  Bayesian Approaches to Subgroup Analysis and Related Adaptive Clinical Trial Designs.

Authors:  Ciara Nugent; Wentian Guo; Peter Müller; Yuan Ji
Journal:  JCO Precis Oncol       Date:  2019-10-24

5.  Safety and efficacy of Cerebrolysin in acute brain injury and neurorecovery: CAPTAIN I-a randomized, placebo-controlled, double-blind, Asian-Pacific trial.

Authors:  W Poon; C Matula; P E Vos; D F Muresanu; N von Steinbüchel; K von Wild; V Hömberg; E Wang; T M C Lee; S Strilciuc; J C Vester
Journal:  Neurol Sci       Date:  2019-09-07       Impact factor: 3.307

6.  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

7.  Adaptive designs for comparative effectiveness research trials.

Authors:  John A Kairalla; Christopher S Coffey; Mitchell A Thomann; Ronald I Shorr; Keith E Muller
Journal:  Clin Res Regul Aff       Date:  2014-11-13

8.  Response adaptive randomization procedures in seamless phase II/III clinical trials.

Authors:  Hongjian Zhu; Jin Piao; J Jack Lee; Feifang Hu; Lixin Zhang
Journal:  J Biopharm Stat       Date:  2019-08-27       Impact factor: 1.051

9.  Anagrelide compared with hydroxyurea in WHO-classified essential thrombocythemia: the ANAHYDRET Study, a randomized controlled trial.

Authors:  Heinz Gisslinger; Mirjana Gotic; Jerzy Holowiecki; Miroslav Penka; Juergen Thiele; Hans-Michael Kvasnicka; Robert Kralovics; Petro E Petrides
Journal:  Blood       Date:  2013-01-11       Impact factor: 22.113

10.  Closed Testing in Pharmaceutical Research: Historical and Recent Developments.

Authors:  Kevin S S Henning; Peter H Westfall
Journal:  Stat Biopharm Res       Date:  2015       Impact factor: 1.452

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