Biomaterial Database

The statistical analysis of cancer inhibition/promotion experiments. 1993

S M Kokoska, and J M Hardin, and C J Grubbs, and C Hsu

Department of Mathematics and Computer Science, Bloomsburg University, PA 17815.

The purpose of this paper is to address the very important problem of accurate statistical analysis of certain types of cancer inhibition/promotion (IP) experiments. These experiments are routinely used by the National Cancer Institute to test the effects of potential chemopreventative agents. The statistical analysis is difficult since there is Type I censoring. In the IP experiments under investigation, laboratory animals (rats) are injected with a single dose of either a direct or indirect acting carcinogen. In the mammary tumor system, animals in the control group generally develop 5-7 tumors and typical experiments are usually terminated after 4-6 months. Animals are sacrificed at the end of the experiment and all observed tumors are confirmed. The two most common response variables are the number of observed tumors per animal and the rate of tumor development. The difficulty in analyzing these experiments occurs because experiments are terminated before all induced tumors have been observed. Fewer observed tumors in one group compared to another could be the result of a decreased number of induced tumors, a decrease in growth rate, or a combination of both. It is essential for the experimenter to distinguish between these two different biological actions. Present statistical techniques do not account for this confounding and since they rely primarily on nonparametric procedures, do not present an accurate description of potential IP agents. In this paper we introduce a parametric procedure that explicitly acknowledges the confounding present in experiments of this nature. The analysis is based on the comparison of the mean number of tumors per group (lambda) and the mean time to tumor appearance (mu). A longer mean time to development is believed to indicate a slower tumor growth rate. Hypothesis tests are developed to determine if there is an overall experiment effect, to isolate which groups are contributing to an observed experiment effect, and to isolate factors (tumor number and/or growth rate) contributing to an observed group difference. Confidence regions for (lambda, mu) are also generated. This analysis leads to a better understanding of how potential IP agents function.

UI	MeSH Term	Description	Entries
D008954	Models, Biological	Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.	Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D008962	Models, Theoretical	Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.	Experimental Model,Experimental Models,Mathematical Model,Model, Experimental,Models (Theoretical),Models, Experimental,Models, Theoretic,Theoretical Study,Mathematical Models,Model (Theoretical),Model, Mathematical,Model, Theoretical,Models, Mathematical,Studies, Theoretical,Study, Theoretical,Theoretical Model,Theoretical Models,Theoretical Studies
D009374	Neoplasms, Experimental	Experimentally induced new abnormal growth of TISSUES in animals to provide models for studying human neoplasms.	Experimental Neoplasms,Experimental Neoplasm,Neoplasm, Experimental
D002273	Carcinogens	Substances that increase the risk of NEOPLASMS in humans or animals. Both genotoxic chemicals, which affect DNA directly, and nongenotoxic chemicals, which induce neoplasms by other mechanism, are included.	Carcinogen,Oncogen,Oncogens,Tumor Initiator,Tumor Initiators,Tumor Promoter,Tumor Promoters,Initiator, Tumor,Initiators, Tumor,Promoter, Tumor,Promoters, Tumor
D004224	Diterpenes	Twenty-carbon compounds derived from MEVALONIC ACID or deoxyxylulose phosphate.	Diterpene,Diterpenes, Cembrane,Diterpenes, Labdane,Diterpenoid,Labdane Diterpene,Norditerpene,Norditerpenes,Norditerpenoid,Cembranes,Diterpenoids,Labdanes,Norditerpenoids,Cembrane Diterpenes,Diterpene, Labdane,Labdane Diterpenes
D000084562	Retinyl Esters	A carboxylic ester of retinol formed by condensation of the hydroxy group of retinol with a carboxy group.	All-Trans-Retinyl Ester,All-Trans-Retinyl Esters,Retinyl Ester,All Trans Retinyl Ester,All Trans Retinyl Esters,Ester, All-Trans-Retinyl,Ester, Retinyl
D000818	Animals	Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA.	Animal,Metazoa,Animalia
D013997	Time Factors	Elements of limited time intervals, contributing to particular results or situations.	Time Series,Factor, Time,Time Factor
D014801	Vitamin A	Retinol and derivatives of retinol that play an essential role in metabolic functioning of the retina, the growth of and differentiation of epithelial tissue, the growth of bone, reproduction, and the immune response. Dietary vitamin A is derived from a variety of CAROTENOIDS found in plants. It is enriched in the liver, egg yolks, and the fat component of dairy products.	Retinol,11-cis-Retinol,3,7-dimethyl-9-(2,6,6-trimethyl-1-cyclohexen-1-yl)-2,4,6,8-nonatetraen-1-ol, (all-E)-Isomer,All-Trans-Retinol,Aquasol A,Vitamin A1,All Trans Retinol
D015127	9,10-Dimethyl-1,2-benzanthracene	Polycyclic aromatic hydrocarbon found in tobacco smoke that is a potent carcinogen.	7,12-Dimethylbenzanthracene,7,12-Dimethylbenz(a)anthracene,7,12 Dimethylbenzanthracene