||5R03CA108370-02 Interpret this number
||University Of California, San Francisco
||Pancreas Cancer Analysis-Sf Bay Area Case-Control Study
DESCRIPTION (provided by applicant):
Pancreas cancer analysis-SF Bay Area case-control study: Pancreatic cancer (PC) is the fourth most common cause of cancer death with the lowest 5-year survival rate (<5%) of all cancers. It has been designated as a high priority for NCI by the NCI-sponsored Progress Review Group and by Congress for FY 2004. The overall study goal is to continue data analyses for our large population-based case-control study of PC that was conducted between 1994 and 2002 (no proxy interviews, n=532 patients, 1701 controls). Using unconditional logistic regression, the specific aims are to: 1) perform data analyses of diet (energy-adjusted for nutrients), pancreatitis, diabetes, smoking, alcohol consumption, and hormone use in women in relation to PC; and 2) to evaluate the relationships between factors in Aim 1 and previously determined polymorphisms (GSTT1, GSTM1, CYPIA1, XRCC1). Detailed data were collected for this study about each factor of interest. Because the genes of interest play an important role in detoxification of carcinogenic polycyclic aromatic hydrocarbons and heterocyclic amines, estrogen metabolism and repair of DNA damaged by oxidative stress, it is plausible that the presence of polymorphisms in these genes will alter the association between pancreatic cancer and factors in Aim 1. Study strengths include: 1) already identified genetic polymorphisms; 2) extensive information on risk factors; 3) diet questionnaire developed by Dr. Walter Willett's group at Harvard University who have computed macro and micronutrients for this study; 4) large sample size allows combination of risk-factor and molecular data to determine possible interactions between genetic and environmental factors; 5) data were collected on food preparation methods and vitamins that may be relevant in PC etiology; 6) SEER registry provided complete case ascertainment; and 7) can evaluate potential confounding and effect modification. Data on modifiable risk factors may provide new and provocative results of 3ublic health importance for this devastating disease.