Age-Adjusted Exact Trend Tests in the Event of Rare Occurrences

Ahn, Hongshik; Chen, James J.; Mancuso, James P.

doi:10.1111/j.0006-341x.2002.00403.x

Cited by 10 publications

(11 citation statements)

References 22 publications

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“…However, simulation studies demonstrate that the Poly-3 test is sensitive to certain departures from the underlying Weibull model (Mancuso et al, 2002;Peddada et al, 2005). Peddada et al (2005) suggested an alternative trend test which uses the Poly-3 weights, but does not assume the tumor rates are linear in dose, does not depend on the numerical scores assigned to the dose groups, and does not incorporate a continuity correction.…”

Section: Introductionmentioning

confidence: 99%

Incorporating Historical Control Data When Comparing Tumor Incidence Rates

Peddada

Dinse

Kissling

2007

Journal of the American Statistical Association

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Animal carcinogenicity studies, such as those conducted by the U.S. National Toxicology Program (NTP), focus on detecting trends in tumor rates across dose groups. Over time, the NTP has compiled vast amounts of data on tumors in control animals. Currently, this information is used informally, without the benefit of statistical tests for carcinogenicity that directly incorporate historical data on control animals. This article proposes a survival-adjusted test for detecting doserelated trends in tumor incidence rates, which incorporates data on historical control rates and formally accounts for variation in these rates among studies. An extensive simulation, based on a wide range of realistic situations, demonstrates that the proposed test performs well in comparison to the current NTP test, which does not incorporate historical control data. In particular, our test can aid in interpreting the occurrence of a few tumors in treated animals that are rarely seen in controls. One such example, which motivates our work, concerns the analysis of histiocytic sarcoma in the NTP's 2-year cancer bioassay of benzophenone. Whereas the occurrence of three histiocytic sarcomas in female rats was not significant according to the current NTP testing procedure (P = 0.074), it was highly significant (P = 0.004) when control data from six recent historical studies were included and our test was applied to the combined data.

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Section: Introductionmentioning

confidence: 99%

Incorporating Historical Control Data When Comparing Tumor Incidence Rates

Peddada

Dinse

Kissling

2007

Journal of the American Statistical Association

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“…The CA test is known to be sensitive to increases in treatment lethality. In such a case, the CA test often fails to control the probability of a Type I error (Bailer and Portier 1988;Mancuso, Ahn, Chen, and Mancuso 2002;Moon et al 2002Moon et al , 2003Moon et al , 2005. Bailer and Portier (1988) proposed the poly-k test, which made an adjustment of the CA test by using a fractional weighting scheme for animals according to information on tumor presence/absence at the age of death.…”

Section: The Poly-k Survival-adjusted Trend Testmentioning

confidence: 99%

A Computational Tool for Testing Dose-Related Trend Using an Age-Adjusted Bootstrap-Based Poly-kTest

Moon¹,

Kodell²,

Pearce³

et al. 2006

J. Stat. Soft.

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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.

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“…This simulation design is for frequent tumours. For spontaneous tumours with low rates, exact tests can be applied [27].…”

Section: Simulation Studymentioning

confidence: 99%

A dose–response test via closed‐form solutions for constrained MLEs in survival/sacrifice experiments

Kim

Ahn

Moon

2006

Statistics in Medicine

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In most survival-sacrifice experiments in animal carcinogenicity studies, the onset of the tumour of interest is not clinically observable. Due to the complexity of constraints for a biological justification, recently developed methods for estimating the tumour onset function and tumour-specific survival function employ computer-intensive numerical solutions. In this paper, closed-form solutions for nonparametric maximum likelihood estimators are derived under explicit and implicit inequality constraints obtained from the monotonicity of the survival functions. Our methods do not require cause-of-death information. The proposed methods can be used to estimate the tumour onset function and the survival function of the tumour of interest. We use the proposed estimators for the development of our new dose-response trend test. A modification of the Poly-k test is made by replacing the time-at-risk weight to a function of the tumour onset survival function. The weighted least square regression method is applied to the estimated survival functions in order to construct a dose-response trend test. A simulation study is conducted to evaluate the performance of the proposed test and compare it with existing trend tests. A real example is used to illustrate the methods.

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Age-Adjusted Exact Trend Tests in the Event of Rare Occurrences

Cited by 10 publications

References 22 publications

Incorporating Historical Control Data When Comparing Tumor Incidence Rates

Incorporating Historical Control Data When Comparing Tumor Incidence Rates

A Computational Tool for Testing Dose-Related Trend Using an Age-Adjusted Bootstrap-Based Poly-kTest

A dose–response test via closed‐form solutions for constrained MLEs in survival/sacrifice experiments

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