|Authors:||Hojin Moon, Hongshik Ahn, Ralph L. Kodell|
|Title:||A Computational Tool for Testing Dose-related Trend Using an Age-adjusted Bootstrap-based Poly-k Test|
|Abstract:||A computational tool for testing for a dose-related trend and/or a pairwise difference in the incidence of an occult tumor via an age-adjusted bootstrap-based poly-k test and the original poly-k test is presented in this paper. The poly-k test (Bailer and Portier 1988) is a survival-adjusted Cochran-Armitage test, which achieves robustness to effects of differential mortality across dose groups. The original poly-k test is asymptotically standard normal under the null hypothesis. However, the asymptotic normality is not valid if there is a deviation from the tumor onset distribution that is assumed in this test. Our age-adjusted bootstrap-based poly-k test assesses the significance of assumed asymptotic normal tests and investigates an empirical distribution of the original poly-k test statistic using an age-adjusted bootstrap method. A tumor of interest is an occult tumor for which the time to onset is not directly observable. Since most of the animal carcinogenicity studies are designed with a single terminal sacrifice, the present tool is applicable to rodent tumorigenicity assays that have a single terminal sacrifice. The present tool takes input information simply from a user screen and reports testing results back to the screen through a user-interface. The computational tool is implemented in C/C++ and is applied to analyze a real data set as an example. Our tool enables the FDA and the pharmaceutical industry to implement a statistical analysis of tumorigenicity data from animal bioassays via our age-adjusted bootstrap-based poly-k test and the original poly-k test which has been adopted by the National Toxicology Program as its standard statistical test.|
Page views:: 4577. Submitted: 2004-11-16. Published: 2006-08-04.
A Computational Tool for Testing Dose-related Trend Using an Age-adjusted Bootstrap-based Poly-k Test
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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.