Literature DB >> 7973211

The CHART trials: Bayesian design and monitoring in practice. CHART Steering Committee.

M K Parmar1, D J Spiegelhalter, L S Freedman.   

Abstract

In this paper we describe the design and monitoring of two large randomized trials being conducted through the British Medical Research Council (MRC) Cancer Trials Office. In particular we discuss the issues involved in the design of the trials, specifying the null and alternative hypotheses and how the design has influenced the monitoring procedure used. From these two examples, and some other MRC experiences, we suggest some basic considerations which could be applied to many MRC and other trials.

Mesh:

Year:  1994        PMID: 7973211     DOI: 10.1002/sim.4780131304

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


  25 in total

Review 1.  Methods in health service research. An introduction to bayesian methods in health technology assessment.

Authors:  D J Spiegelhalter; J P Myles; D R Jones; K R Abrams
Journal:  BMJ       Date:  1999-08-21

Review 2.  Trials and fast changing technologies: the case for tracker studies.

Authors:  R J Lilford; D A Braunholtz; R Greenhalgh; S J Edwards
Journal:  BMJ       Date:  2000-01-01

Review 3.  Strategy for randomised clinical trials in rare cancers.

Authors:  Say-Beng Tan; Keith B G Dear; Paolo Bruzzi; David Machin
Journal:  BMJ       Date:  2003-07-05

4.  Interpreting trial results in light of conflicting evidence: a Bayesian analysis of adjuvant chemotherapy for non-small-cell lung cancer.

Authors:  Rebecca A Miksad; Mithat Gönen; Thomas J Lynch; Thomas G Roberts
Journal:  J Clin Oncol       Date:  2009-03-23       Impact factor: 44.544

5.  Bayesian statistical methods.

Authors:  L Freedman
Journal:  BMJ       Date:  1996-09-07

6.  Sample sizes for randomized trials measuring quality of life in cancer patients.

Authors:  S A Julious; S George; D Machin; R J Stephens
Journal:  Qual Life Res       Date:  1997-03       Impact factor: 4.147

7.  Quantifying veterinarians' beliefs on disease control and exploring the effect of new evidence: a Bayesian approach.

Authors:  H M Higgins; J N Huxley; W Wapenaar; M J Green
Journal:  J Dairy Sci       Date:  2014-03-27       Impact factor: 4.034

8.  Bayesian clinical trials at The University of Texas MD Anderson Cancer Center: An update.

Authors:  Rebecca S Slack Tidwell; S Andrew Peng; Minxing Chen; Diane D Liu; Ying Yuan; J Jack Lee
Journal:  Clin Trials       Date:  2019-08-26       Impact factor: 2.486

9.  A Bayesian approach to Weibull survival models--application to a cancer clinical trial.

Authors:  K Abrams; D Ashby; D Errington
Journal:  Lifetime Data Anal       Date:  1996       Impact factor: 1.588

10.  Bayesian analysis of a mastitis control plan to investigate the influence of veterinary prior beliefs on clinical interpretation.

Authors:  M J Green; W J Browne; L E Green; A J Bradley; K A Leach; J E Breen; G F Medley
Journal:  Prev Vet Med       Date:  2009-07-02       Impact factor: 2.670

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