Literature DB >> 10440879

Investigating centre effects in a multi-centre clinical trial of superficial bladder cancer.

T Yamaguchi1, Y Ohashi.   

Abstract

This paper examines the amount of variation among centres and estimates the overall effect of therapy in a multi-centre cancer clinical trial with censored failure time data. To investigate the centre effects, the variation in the treatment effect must be taken into consideration in addition to the variation in the baseline risk. We treat centre effects as random ones and extend the penalized partial likelihood approach proposed by McGilchrist to estimate the treatment-by-centre interaction as well as the baseline risk. This method is applied to data from a superficial bladder cancer clinical trial investigating the efficacy of intravesical chemotherapy after transurethral resection. In this trial, although there exists some degree of centre variation, especially in the baseline risk, the treatment is effective in preventing recurrence among the participating centres. This result indicates that the treatment effect is generalizable to the target population. Copyright 1999 John Wiley & Sons, Ltd.

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Year:  1999        PMID: 10440879     DOI: 10.1002/(sici)1097-0258(19990815)18:15<1961::aid-sim170>3.0.co;2-3

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


  8 in total

1.  Validation of prognostic indices using the frailty model.

Authors:  C Legrand; L Duchateau; P Janssen; V Ducrocq; R Sylvester
Journal:  Lifetime Data Anal       Date:  2008-07-11       Impact factor: 1.588

2.  Frailty modelling for survival data from multi-centre clinical trials.

Authors:  Il Do Ha; Richard Sylvester; Catherine Legrand; Gilbert Mackenzie
Journal:  Stat Med       Date:  2011-05-12       Impact factor: 2.373

3.  Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties.

Authors:  Il Do Ha; Nicholas J Christian; Jong-Hyeon Jeong; Junwoo Park; Youngjo Lee
Journal:  Stat Methods Med Res       Date:  2014-03-11       Impact factor: 3.021

4.  MULTI-CENTER CLINICAL TRIALS: RANDOMIZATION AND ANCILLARY STATISTICS.

Authors:  L U Zheng; Marvin Zelen
Journal:  Ann Appl Stat       Date:  2008-07-03       Impact factor: 2.083

5.  Differences in clinical trial patient attributes and outcomes according to enrollment setting.

Authors:  Elizabeth B Lamont; Mary Beth Landrum; Nancy L Keating; Laura Archer; Lan Lan; Gary M Strauss; Rogerio Lilenbaum; Harvey B Niell; L Herbert Maurer; Michael P Kosty; Antonius A Miller; Gerald H Clamon; Anthony D Elias; Edward F McClay; Everett E Vokes; Barbara J McNeil
Journal:  J Clin Oncol       Date:  2009-11-23       Impact factor: 44.544

6.  Individual patient data meta-analysis of survival data using Poisson regression models.

Authors:  Michael J Crowther; Richard D Riley; Jan A Staessen; Jiguang Wang; Francois Gueyffier; Paul C Lambert
Journal:  BMC Med Res Methodol       Date:  2012-03-23       Impact factor: 4.615

Review 7.  Making trials matter: pragmatic and explanatory trials and the problem of applicability.

Authors:  Shaun Treweek; Merrick Zwarenstein
Journal:  Trials       Date:  2009-06-03       Impact factor: 2.279

Review 8.  Get real in individual participant data (IPD) meta-analysis: a review of the methodology.

Authors:  Thomas P A Debray; Karel G M Moons; Gert van Valkenhoef; Orestis Efthimiou; Noemi Hummel; Rolf H H Groenwold; Johannes B Reitsma
Journal:  Res Synth Methods       Date:  2015-08-19       Impact factor: 5.273

  8 in total

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