Skip to main content
An official website of the United States government
Grant Details

Grant Number: 5R01CA095946-03 Interpret this number
Primary Investigator: Parsonnet, Julie
Organization: Stanford University
Project Title: Gis for Extant Data: Modeling H.pylori and Gi Tumors
Fiscal Year: 2004


DESCRIPTION (provided by applicant): Many large demographic and health datasets exist in the public domain and significant federal resources have been committed to their collection and maintenance. We postulate that, using geographic information systems (GIS) technology, the enormous body of information within these unrelated datasets can be integrated to efficiently explore novel hypotheses. For such purposes, however, precise methods of using GIS have not been well standardized. In this proposal, we intend to develop a method for integrating diverse data sets using GIS and then use the spatial capacities of GIS to answer epidemiologic questions. We will validate these methods using the model of Helicobacter pylori and malignancy. H. pylori is a known cause of stomach cancer, and has been purported to cause colorectal and pancreatic adenocarcinomas and to protect against esophageal adenocarcinoma. The vast array of epidemiologic knowledge on this bacterium and its associated cancers makes it an excellent subject for validation of these methods. We will use GIS to combine data from the U.S. Census, NHANES III, and the SEER cancer registry. We will then assess the spatial correlations between H. pylori infection and specific cancer incidences and mortality rates. Development and validation of this methodology will highlight the utility of GIS in epidemiologic research. It will provide a cost-effective means to harness the power and efficiency of large-scale surveys to address specific hypotheses at low expense, even if they were not considered during the design of the surveys. Application of these methods could potentially allow investigators to use existing data sources to address novel hypotheses that may have otherwise been not feasible to pursue.


Estimating disease prevalence using census data.
Authors: Choy M. , Switzer P. , De Martel C. , Parsonnet J. .
Source: Epidemiology and infection, 2008 Sep; 136(9), p. 1253-60.
EPub date: 2007-11-30.
PMID: 18047747
Related Citations

Back to Top