Literature DB >> 12205692

Estimating a treatment effect in survival studies in which patients switch treatment.

Michael Branson1, John Whitehead.   

Abstract

For disease indications such as Acquired Immune Deficiency Syndrome (AIDS) and various cancers, randomization to a pure control treatment may be scientifically desirable but not ethically acceptable. Clinicians may insist that the experimental treatment be made available, at least as a rescue medication, for all patients in the control arm. A method for estimating a treatment effect in survival data from randomized clinical trials of this type is developed under an accelerated failure time model. This approach retains all patients in the groups to which they were randomized and is not based on an ad hoc subgroup analysis. By conditioning on having observed patient switch times, this method avoids the need to model patient switching patterns in the analysis. This new approach is evaluated using simulation studies, and is illustrated through analysing data from a Medical Research Council lung cancer trial. Copyright 2002 John Wiley & Sons, Ltd.

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Year:  2002        PMID: 12205692     DOI: 10.1002/sim.1219

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


  26 in total

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3.  Adjusting for the Confounding Effects of Treatment Switching-The BREAK-3 Trial: Dabrafenib Versus Dacarbazine.

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4.  Causal inference in randomized clinical trials.

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5.  Estimating treatment effects with treatment switching via semicompeting risks models: an application to a colorectal cancer study.

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Journal:  Biometrika       Date:  2011-12-29       Impact factor: 2.445

6.  Methods for adjusting for bias due to crossover in oncology trials.

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7.  A Multi-state Model for Designing Clinical Trials for Testing Overall Survival Allowing for Crossover after Progression.

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8.  Effect of Blinatumomab vs Chemotherapy on Event-Free Survival Among Children With High-risk First-Relapse B-Cell Acute Lymphoblastic Leukemia: A Randomized Clinical Trial.

Authors:  Franco Locatelli; Gerhard Zugmaier; Carmelo Rizzari; Joan D Morris; Bernd Gruhn; Thomas Klingebiel; Rosanna Parasole; Christin Linderkamp; Christian Flotho; Arnaud Petit; Concetta Micalizzi; Noemi Mergen; Abeera Mohammad; William N Kormany; Cornelia Eckert; Anja Möricke; Mary Sartor; Ondrej Hrusak; Christina Peters; Vaskar Saha; Luciana Vinti; Arend von Stackelberg
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Review 9.  Azacitidine for Treating Acute Myeloid Leukaemia with More Than 30 % Bone Marrow Blasts: An Evidence Review Group Perspective of a National Institute for Health and Care Excellence Single Technology Appraisal.

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Journal:  Pharmacoeconomics       Date:  2017-03       Impact factor: 4.981

10.  Estimating time-varying effects for overdispersed recurrent events data with treatment switching.

Authors:  Qingxia Chen; Donglin Zeng; Joseph G Ibrahim; Mouna Akacha; Heinz Schmidli
Journal:  Biometrika       Date:  2013       Impact factor: 2.445

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