Literature DB >> 22945865

The use of group sequential designs with common competing risks tests.

Brent R Logan1, Mei-Jie Zhang.   

Abstract

Clinical trials are often performed using a group sequential design in order to allow investigators to review the accumulating data sequentially and possibly terminate the trial early for efficacy or futility. Standard methods for comparing survival distributions have been shown under varying levels of generality to follow an independent increments structure. In the presence of competing risks, where the occurrence of one type of event precludes the occurrence of another type of event, researchers may be interested in inference on the cumulative incidence function, which describes the probability of experiencing a particular event by a given time. This manuscript shows that two commonly used tests for comparing cumulative incidence functions, a pointwise comparison at a single point, and Gray's test, also follow the independent increments structure when used in a group sequential setting. A simulation study confirms the theoretical derivations even for modest trial sample sizes. We used two examples of clinical trials in hematopoietic cell transplantation to illustrate the techniques.
Copyright © 2012 John Wiley & Sons, Ltd.

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Year:  2012        PMID: 22945865      PMCID: PMC3574186          DOI: 10.1002/sim.5597

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


  8 in total

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Authors:  Aurélien Latouche; Raphaël Porcher; Sylvie Chevret
Journal:  Stat Med       Date:  2004-11-15       Impact factor: 2.373

2.  Sample size calculations in the presence of competing risks.

Authors:  A Latouche; R Porcher
Journal:  Stat Med       Date:  2007-12-30       Impact factor: 2.373

3.  Group sequential designs for monitoring survival probabilities.

Authors:  D Y Lin; L Shen; Z Ying; N E Breslow
Journal:  Biometrics       Date:  1996-09       Impact factor: 2.571

4.  Non-parametric inference for cumulative incidence functions in competing risks studies.

Authors:  D Y Lin
Journal:  Stat Med       Date:  1997-04-30       Impact factor: 2.373

5.  Sample-size formula for the proportional-hazards regression model.

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Journal:  Biometrics       Date:  1983-06       Impact factor: 2.571

6.  Randomized, double-blind trial of fluconazole versus voriconazole for prevention of invasive fungal infection after allogeneic hematopoietic cell transplantation.

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Journal:  Blood       Date:  2010-09-08       Impact factor: 22.113

7.  Sample sizes for clinical trials with time-to-event endpoints and competing risks.

Authors:  Gabi Schulgen; Manfred Olschewski; Vera Krane; Christoph Wanner; Günther Ruf; Martin Schumacher
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Authors:  Matthieu Resche-Rigon; Elie Azoulay; Sylvie Chevret
Journal:  Crit Care       Date:  2006-02       Impact factor: 9.097

  8 in total
  9 in total

1.  Confidence intervals for the cumulative incidence function via constrained NPMLE.

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Review 2.  The Blood and Marrow Transplant Clinical Trials Network: An Effective Infrastructure for Addressing Important Issues in Hematopoietic Cell Transplantation.

Authors: 
Journal:  Biol Blood Marrow Transplant       Date:  2016-07-11       Impact factor: 5.742

3.  A group sequential test for treatment effect based on the Fine-Gray model.

Authors:  Michael J Martens; Brent R Logan
Journal:  Biometrics       Date:  2018-03-13       Impact factor: 2.571

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Authors:  Michael J Martens; Brent R Logan
Journal:  Lifetime Data Anal       Date:  2019-11-15       Impact factor: 1.588

5.  Nonparametric competing risks analysis using Bayesian Additive Regression Trees.

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Journal:  Stat Methods Med Res       Date:  2019-01-07       Impact factor: 3.021

6.  Radical prostatectomy or radiotherapy reduce prostate cancer mortality in elderly patients: a population-based propensity score adjusted analysis.

Authors:  Marco Bandini; Raisa S Pompe; Michele Marchioni; Zhe Tian; Giorgio Gandaglia; Nicola Fossati; Derya Tilki; Markus Graefen; Francesco Montorsi; Shahrokh F Shariat; Alberto Briganti; Fred Saad; Pierre I Karakiewicz
Journal:  World J Urol       Date:  2017-10-23       Impact factor: 4.226

7.  The effect of age on cancer-specific mortality in patients with small renal masses: A population-based analysis.

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Journal:  Can Urol Assoc J       Date:  2018-03-19       Impact factor: 1.862

8.  Survival after radical prostatectomy or radiotherapy for locally advanced (cT3) prostate cancer.

Authors:  Marco Bandini; Michele Marchioni; Felix Preisser; Emanuele Zaffuto; Zhe Tian; Derya Tilki; Francesco Montorsi; Shahrokh F Shariat; Fred Saad; Alberto Briganti; Pierre I Karakiewicz
Journal:  World J Urol       Date:  2018-05-02       Impact factor: 4.226

9.  Design aspects of COVID-19 treatment trials: Improving probability and time of favorable events.

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Journal:  Biom J       Date:  2021-10-22       Impact factor: 1.715

  9 in total

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