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. 2009 Sep 1;15(5):858-875.
doi: 10.1080/10807030903153360.

Applications of the Poly-K Statistical Test to Life-Time Cancer Bioassay Studies

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Applications of the Poly-K Statistical Test to Life-Time Cancer Bioassay Studies

Mulugeta Gebregziabher et al. Hum Ecol Risk Assess. .

Abstract

The statistical analysis of cancer bioassay data has historically depended on the pathological determination of the experimental animal's cause of death. The poly-k statistical test has provided a method of statistical analysis of animal bioassay data without the need for cause of death information. The test has been shown to have good statistical properties in the typical 2-year cancer bioassay. However, while the poly-k test has been applied to chronic lifetime animal studies, it has not been formally evaluated with respect to the operating characteristics of this statistical test when applied to such studies. Thus, our objective is to assess the performance of the poly-k test for lifetime studies and to make comparisons with other tests. We observed in one recent lifetime study of the gasoline additive MTBE that the application of the poly-k test was not statistically robust. Simulation studies were subsequently conducted for a limited number of scenarios of lifetime cancer bioassays. These simulations showed that the poly-k test is not statistically robust for testing effect of increasing dose in some lifetime cancer studies.

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Figures

Figure 1
Figure 1
Kaplan-Meier Survival Curves for the three dose groups in the Leydig tumors MTBE data example (solid line = control dose, broken line = 250mg/kg/day, dotted line = 1000mg/kg/day). There were 3/60, 5/60 and 11/60 LCT events for control, 250mg/kg and 1000mg/kg doses, respectively, and are indicated by + signs in the plots.
Figure 2
Figure 2
Test size and power of trend tests for equally spaced three dose groups and n = 100 per group (shape and scale parameters for other causes of death were fixed at 4.2 and 0.01205, respectively). Panel 2A and 2B are when treatment does not affect death due to causes other than the tumor of interest, i.e., non-cancer hazard ratio HR = 1 and Panel 2C and 2D are when treatment does not affect the tumor of interest, i.e., tumor onset hazard rate = 1 but affects non-cancer mortality.
Figure 3
Figure 3
Test size and power of trend tests for equally spaced three dose groups and n = 100 per group (shape and scale for other causes of death were fixed at 4.2 and 0.01205, respectively). Panel 3A and 3B are when the treatment effect on death due to other causes is fixed at hazard ratio HR = 1.4 and Panel 3C and 3D are when the treatment effect on tumor incidence is fixed at HR = 2.2 and when the treatment affects non-cancer mortality.

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