Literature DB >> 17151088

The influence of competing-risks setting on the choice of hypothesis test for treatment effect.

P R Williamson1, R Kolamunnage-Dona, C Tudur Smith.   

Abstract

There is considerable debate regarding the choice of test for treatment difference in a randomized clinical trial in the presence of competing risks. This question arose in the study of standard and new antiepileptic drugs (SANAD) trial comparing new and standard antiepileptic drugs. This paper provides simulation results for the log-rank test comparing cause-specific hazard rates and Gray's test comparing cause-specific cumulative incidence curves. To inform the analysis of the SANAD trial, competing-risks settings were considered where both events are of interest, events may be negatively correlated, and the degree of correlation may differ in the 2 treatment groups. In settings where there are effects in opposite directions for the 2 event types, a likely situation for the SANAD trial, Gray's test has greater power to detect treatment differences than log-rank analysis. For the epilepsy application, conclusions were qualitatively similar for both log-rank and Gray's tests.

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Year:  2006        PMID: 17151088     DOI: 10.1093/biostatistics/kxl040

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  12 in total

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2.  Retention rates of rufinamide in pediatric epilepsy patients with and without Lennox-Gastaut Syndrome.

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Authors:  James J Dignam; Maria N Kocherginsky
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5.  Analysis and design of randomised clinical trials involving competing risks endpoints.

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Authors:  Sameer Parpia; Lehana Thabane; Jim A Julian; Timothy J Whelan; Mark N Levine
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7.  Testing the treatment effect on competing causes of death in oncology clinical trials.

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8.  Modelling variable dropout in randomised controlled trials with longitudinal outcomes: application to the MAGNETIC study.

Authors:  Ruwanthi Kolamunnage-Dona; Colin Powell; Paula Ruth Williamson
Journal:  Trials       Date:  2016-04-28       Impact factor: 2.279

9.  Donor-Recipient Matching for KIR Genotypes Reduces Chronic GVHD and Missing Inhibitory KIR Ligands Protect against Relapse after Myeloablative, HLA Matched Hematopoietic Cell Transplantation.

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Journal:  PLoS One       Date:  2016-06-24       Impact factor: 3.240

10.  Importance of competing risks in the analysis of anti-epileptic drug failure.

Authors:  Paula R Williamson; Catrin Tudur Smith; Josemir W Sander; Anthony G Marson
Journal:  Trials       Date:  2007-03-29       Impact factor: 2.279

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