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Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study

BACKGROUND: Exploring spatial-temporal patterns of disease incidence through cluster analysis identifies areas of significantly elevated or decreased risk, providing potential clues about disease risk factors. Little is known about the etiology of non-Hodgkin lymphoma (NHL), or the latency period th...

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Autores principales: Wheeler, David C, De Roos, Anneclaire J, Cerhan, James R, Morton, Lindsay M, Severson, Richard, Cozen, Wendy, Ward, Mary H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3148953/
https://www.ncbi.nlm.nih.gov/pubmed/21718483
http://dx.doi.org/10.1186/1476-069X-10-63
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author Wheeler, David C
De Roos, Anneclaire J
Cerhan, James R
Morton, Lindsay M
Severson, Richard
Cozen, Wendy
Ward, Mary H
author_facet Wheeler, David C
De Roos, Anneclaire J
Cerhan, James R
Morton, Lindsay M
Severson, Richard
Cozen, Wendy
Ward, Mary H
author_sort Wheeler, David C
collection PubMed
description BACKGROUND: Exploring spatial-temporal patterns of disease incidence through cluster analysis identifies areas of significantly elevated or decreased risk, providing potential clues about disease risk factors. Little is known about the etiology of non-Hodgkin lymphoma (NHL), or the latency period that might be relevant for environmental exposures, and there are no published spatial-temporal cluster studies of NHL. METHODS: We conducted a population-based case-control study of NHL in four National Cancer Institute (NCI)-Surveillance, Epidemiology, and End Results (SEER) centers: Detroit, Iowa, Los Angeles, and Seattle during 1998-2000. Using 20-year residential histories, we used generalized additive models adjusted for known risk factors to model spatially the probability that an individual had NHL and to identify clusters of elevated or decreased NHL risk. We evaluated models at five different time periods to explore the presence of clusters in a time frame of etiologic relevance. RESULTS: The best model fit was for residential locations 20 years prior to diagnosis in Detroit, Iowa, and Los Angeles. We found statistically significant areas of elevated risk of NHL in three of the four study areas (Detroit, Iowa, and Los Angeles) at a lag time of 20 years. The two areas of significantly elevated risk in the Los Angeles study area were detected only at a time lag of 20 years. Clusters in Detroit and Iowa were detected at several time points. CONCLUSIONS: We found significant spatial clusters of NHL after allowing for disease latency and residential mobility. Our results show the importance of evaluating residential histories when studying spatial patterns of cancer.
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spelling pubmed-31489532011-08-03 Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study Wheeler, David C De Roos, Anneclaire J Cerhan, James R Morton, Lindsay M Severson, Richard Cozen, Wendy Ward, Mary H Environ Health Research BACKGROUND: Exploring spatial-temporal patterns of disease incidence through cluster analysis identifies areas of significantly elevated or decreased risk, providing potential clues about disease risk factors. Little is known about the etiology of non-Hodgkin lymphoma (NHL), or the latency period that might be relevant for environmental exposures, and there are no published spatial-temporal cluster studies of NHL. METHODS: We conducted a population-based case-control study of NHL in four National Cancer Institute (NCI)-Surveillance, Epidemiology, and End Results (SEER) centers: Detroit, Iowa, Los Angeles, and Seattle during 1998-2000. Using 20-year residential histories, we used generalized additive models adjusted for known risk factors to model spatially the probability that an individual had NHL and to identify clusters of elevated or decreased NHL risk. We evaluated models at five different time periods to explore the presence of clusters in a time frame of etiologic relevance. RESULTS: The best model fit was for residential locations 20 years prior to diagnosis in Detroit, Iowa, and Los Angeles. We found statistically significant areas of elevated risk of NHL in three of the four study areas (Detroit, Iowa, and Los Angeles) at a lag time of 20 years. The two areas of significantly elevated risk in the Los Angeles study area were detected only at a time lag of 20 years. Clusters in Detroit and Iowa were detected at several time points. CONCLUSIONS: We found significant spatial clusters of NHL after allowing for disease latency and residential mobility. Our results show the importance of evaluating residential histories when studying spatial patterns of cancer. BioMed Central 2011-06-30 /pmc/articles/PMC3148953/ /pubmed/21718483 http://dx.doi.org/10.1186/1476-069X-10-63 Text en Copyright ©2011 Wheeler et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Wheeler, David C
De Roos, Anneclaire J
Cerhan, James R
Morton, Lindsay M
Severson, Richard
Cozen, Wendy
Ward, Mary H
Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study
title Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study
title_full Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study
title_fullStr Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study
title_full_unstemmed Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study
title_short Spatial-temporal analysis of non-Hodgkin lymphoma in the NCI-SEER NHL case-control study
title_sort spatial-temporal analysis of non-hodgkin lymphoma in the nci-seer nhl case-control study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3148953/
https://www.ncbi.nlm.nih.gov/pubmed/21718483
http://dx.doi.org/10.1186/1476-069X-10-63
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