Space-Time Clustering of Non-Hodgkin's Lymphoma Using Residential Histories

Project Number:

5R03CA125827-02

Principal Investigator(s):

MELIKER, JAYMIE R.

Title:

SPACE-TIME CLUSTERING OF NON-HODGKIN'S LYMPHOMA USING RESIDENTIAL HISTORIES

Awardee Organization:

STATE UNIVERSITY NEW YORK STONY BROOK

 

Abstract Text:

DESCRIPTION (provided by applicant): The primary objective of the proposed research project is to generate valuable insights concerning the etiology of Non-Hodgkin's lymphoma (NHL) by investigating space-time clustering of current and past residences of cases and controls in a large, multi-center, population-based study in the United States. Despite more than 300,000 cases of NHL diagnosed each year worldwide, accounting for approximately 2.8% of all cancers, relatively little is known about the etiology of NHL. The established and presumptive risk factors, taken as a whole, account for only a small proportion of the total NHL cases that occur annually, and novel techniques are needed to solve this enigma. Our research team has recently developed Q-statistics and Space-Time Information System (STISTM) technology that enable space-time cluster analyses. Other methods for analyzing cancer clusters typically ignore residential mobility, and almost exclusively work with static spatial point distributions of place-of-residence at time of diagnosis or time of death. In addition, few spatial techniques adequately account for known risk factors and covariates. Our approach addresses each of these needs by utilizing the residential history of the participants represented as a life-line, and thus evaluates space-time clustering at any moment in the life-course of the residential histories of the cases relative to the residential histories of the controls. In addition, in place of the widely used (but often inappropriate) null hypothesis of spatial randomness, Q-statistics can incorporate each individual's probability of being a case based on his/her known risk factors and covariates. This project will apply the innovative Q-statistics and STISTM technology to identify spatial clustering of NHL at any moment in the life-course of the residential histories of the cases relative to the residential histories of the controls. This will, for the first time ever, allow epidemiologists to assess possible geographic and temporal clusters of NHL incidence using current and past residences. The proposed research is a secondary analysis of a large, carefully collected pre-exiting multi-center dataset (1321 cases, 1057 controls), with the intended purpose of generating new hypotheses about potential etiologic factors associated with NHL to be investigated in future studies.

Last updated by jamie.romeiser on June 16, 2011

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