The purpose of this case-control study is to assess the contributions of neurocarcinogen exposure and of glutathione S-transferase, cytochrome P-450, and DNA repair genes to the development and genetic susceptibility of brain tumors and to study the effect of these polymorphisms on treatment outcome and toxicity. Studies to date suggest a moderate to large effect for GSTT1 in selected tumor subtypes. We are targeting obtaining data on approximately 1000 cases and controls, with an adequate number of glioblastomas (n=430), astrocytomas (n=300), oligodendrogliomas (n=100) and meningiomas (n=150) to evaluate this hypothesis with reasonable power for relative risks previously reported for GSTT1. All study subjects will be asked to complete a web-based self-administered or telephone-based questionnaire and to provide blood and/or buceal samples for DNA analysis. Research nurses at Duke University Cancer Center (DUCC)/Evanston Hospital will recruit approximately 770/220 recently diagnosed cases (within 3 months) over a 4-year period. An equal number of friend controls will be identified by asking cases to distribute packets of information to 5 friends of the same age (+/- 5 yrs), gender and race. Controls will return interest cards or phone the research nurse to express interest, then complete the protocol at a clinic appointment or using a distance based protocol. Medical records for cases will be reviewed to obtain clinical and treatment information for the survival and toxicity analyses. Linkage with the National Death Index in Year 4 will obtain vital statistics for up to 3 years of follow-up time to assess outcomes. Study coordination and survey data management will be completed at UIC; molecular analysis will be conducted at DUCC. DUCC will facilitate the neuropathology review, provide management support and some local data collection, and store the remaining specimens in their central respository. Data analysis files will be compiled at Duke University and distributed to the PI's at Duke and UIC. Statistical analyses will use conditional logistic regression models appropriate to each specific aim.
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