RESUMO
Carcinogenic test is an important part of non-clinical safety evaluation of new drugs, which aims to evaluate and predict the human carcinogenic risk in long-term drug use by examining the potential carcinogenic effects of drugs on animals. Historical control data may be vital in the interpretation of rare tumors and unexpected increases or decreases of tumors in treated animals compared to controls. Foreign institutions have accumulated a considerable amount of historical control data that can be attributed to the pathological working group and peer review. Such data is valuable and referable, and can be used as a reliable comparator for concurrent study-specific control data. Different experimental animal strains have evolved in history from the F344 rat and B6C3F1 mice, which were traditionally employed by the National Toxicology Program (NTP), to the SD rats, CD-1 mice, and Wistar rats that were routinely used by industrial firms, and finally to the strains of the p53+/- and Tg.rasH2 transgenic mice. It is true that each strain of rodent animal used in carcinogenicity test has different characters in tumorigenesis. Carcinogenicity tests are increasing in China, but the background data that can be referred to is limited so that how to accumulate and use our own historical control data has become challenging. This article summarizes and compares the tumor lesion data of the collected rodent animals, and concludes that different strains have specific types of tumors with gender-related difference.
RESUMO
Recently, the use of databases for clinical trials is being promoted. We used the Japan Adult Cardiovascular Surgery Database (JACVSD) data was used as a historical control in a clinical trial, and we analyzed following : the processes of using data and the efficiency of data collection, available variables for statistical analysis, and query functions for missing and invalid data. We chose available variables of JACVSD data and created rules for merging JACVSD data with interventional group data, in addition to analyzing the data collection processes for clinical trials. Subjects were selected from cases registered in the JACVSD. On statistical analysis, 63% of 76 variables were used ; variables related to the patients' symptoms had to be collected separately. Missing and invalid data were effectively excluded. We could conduct data collection efficiently by using the JACVSD as a historical control for clinical trials. Selecting subjects from the JACVSD could reduce the burden of selecting subjects from hospitals and prevent selection bias.