Biomaterial Database

Statistical analytical methods for comparing the incidence of tumors to the historical control data. 1994

K Kobayashi, and H Inoue

Biosafety Research Center, Shizuoka, Japan.

Statistical analysis for comparing the incidence of tumors in treated groups to historical control data is not generally performed. In the present study, a number of data exhibiting the lowest, low, moderate and highest incidence of tumors from long-term rodent bioassay studies has been compared with the historical control data. In studies exhibiting the lowest incidence (less than a few percent) of tumors, the Kastenbaum and Bowman test was found to be relevant since it takes into account the sample size of both the historical control data base and each treated group in the study. In studies where a wider range of tumor incidence was exhibited, a statistical method which employs a rejection limits based on the range of incidence in the historical data is recommended. When malignant tumors are evident in treated groups, no matter how low the incidence, they should be analyzed statistically and compared with the incidence in historical control data as well as those in the concurrent control group. Statistical analytical comparisons of study results to historical control data may contribute to more meaningful evaluations in carcinogenicity studies by eliminating possible false positive or false negative results.

UI	MeSH Term	Description	Entries
D008297	Male		Males
D009369	Neoplasms	New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms.	Benign Neoplasm,Cancer,Malignant Neoplasm,Tumor,Tumors,Benign Neoplasms,Malignancy,Malignant Neoplasms,Neoplasia,Neoplasm,Neoplasms, Benign,Cancers,Malignancies,Neoplasias,Neoplasm, Benign,Neoplasm, Malignant,Neoplasms, Malignant
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
D011237	Predictive Value of Tests	In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.	Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D011916	Rats, Inbred F344	An inbred strain of rat that is used for general BIOMEDICAL RESEARCH purposes.	Fischer Rats,Rats, Inbred CDF,Rats, Inbred Fischer 344,Rats, F344,Rats, Inbred Fisher 344,CDF Rat, Inbred,CDF Rats, Inbred,F344 Rat,F344 Rat, Inbred,F344 Rats,F344 Rats, Inbred,Inbred CDF Rat,Inbred CDF Rats,Inbred F344 Rat,Inbred F344 Rats,Rat, F344,Rat, Inbred CDF,Rat, Inbred F344,Rats, Fischer
D003627	Data Interpretation, Statistical	Application of statistical procedures to analyze specific observed or assumed facts from a particular study.	Data Analysis, Statistical,Data Interpretations, Statistical,Interpretation, Statistical Data,Statistical Data Analysis,Statistical Data Interpretation,Analyses, Statistical Data,Analysis, Statistical Data,Data Analyses, Statistical,Interpretations, Statistical Data,Statistical Data Analyses,Statistical Data Interpretations
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
D012376	Rodent Diseases	Diseases of rodents of the order RODENTIA. This term includes diseases of Sciuridae (squirrels), Geomyidae (gophers), Heteromyidae (pouched mice), Castoridae (beavers), Cricetidae (rats and mice), Muridae (Old World rats and mice), Erethizontidae (porcupines), and Caviidae (guinea pigs).	Disease, Rodent,Diseases, Rodent,Rodent Disease
D015197	Carcinogenicity Tests	Tests to experimentally measure the tumor-producing/cancer cell-producing potency of an agent by administering the agent (e.g., benzanthracenes) and observing the quantity of tumors or the cell transformation developed over a given period of time. The carcinogenicity value is usually measured as milligrams of agent administered per tumor developed. Though this test differs from the DNA-repair and bacterial microsome MUTAGENICITY TESTS, researchers often attempt to correlate the finding of carcinogenicity values and mutagenicity values.	Tumorigenicity Tests,Carcinogen Tests,Carcinogenesis Tests,Carcinogenic Activity Tests,Carcinogenic Potency Tests,Carcinogen Test,Carcinogenesis Test,Carcinogenic Activity Test,Carcinogenic Potency Test,Carcinogenicity Test,Potency Test, Carcinogenic,Potency Tests, Carcinogenic,Test, Carcinogen,Test, Carcinogenesis,Test, Carcinogenic Activity,Test, Carcinogenic Potency,Test, Carcinogenicity,Test, Tumorigenicity,Tests, Carcinogen,Tests, Carcinogenesis,Tests, Carcinogenic Activity,Tests, Carcinogenic Potency,Tests, Carcinogenicity,Tests, Tumorigenicity,Tumorigenicity Test
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model