Literature DB >> 18711194

Choice and interpretation of statistical tests used when competing risks are present.

James J Dignam1, Maria N Kocherginsky.   

Abstract

In clinical cancer research, competing risks are frequently encountered. For example, individuals undergoing treatment for surgically resectable disease may experience recurrence near the removed tumor, metastatic recurrence at other sites, occurrence of second primary cancer, or death resulting from noncancer causes before any of these events. Two quantities, the cause-specific hazard function and the cumulative incidence function, are commonly used to summarize outcomes by event type. Tests for event-specific differences between treatment groups may thus be based on comparison of (a) cause-specific hazards via a log-rank or related test, or (b) the cumulative incidence functions via one of several available tests. Inferential results for tests based on these different metrics can differ considerably for the same cause-specific end point. Depending on the questions of principal interest, one or both metrics may be appropriate to consider. We present simulation study results and discuss examples from cancer clinical trials to illustrate these points and provide guidance for analysis when competing risks are present.

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Year:  2008        PMID: 18711194      PMCID: PMC2654314          DOI: 10.1200/JCO.2007.12.9866

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  31 in total

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Authors:  T A Gooley; W Leisenring; J Crowley; B E Storer
Journal:  Stat Med       Date:  1999-03-30       Impact factor: 2.373

2.  Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function.

Authors:  John P Klein; Per Kragh Andersen
Journal:  Biometrics       Date:  2005-03       Impact factor: 2.571

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5.  How dependent causes of death can make risk factors appear protective.

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7.  The analysis of failure times in the presence of competing risks.

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Journal:  Biometrics       Date:  1978-12       Impact factor: 2.571

Review 8.  Why actuarial estimates should be used in reporting late normal-tissue effects of cancer treatment ... now!

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

Authors:  P R Williamson; R Kolamunnage-Dona; C Tudur Smith
Journal:  Biostatistics       Date:  2006-12-06       Impact factor: 5.899

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10.  Competing event risk stratification may improve the design and efficiency of clinical trials: secondary analysis of SWOG 8794.

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