Grant Number:	1R01CA100760-01A1 Interpret this number
Primary Investigator:	Schootman, Mario
Organization:	Washington University
Project Title:	Geographic Variation of Breast Cancer Survival
Fiscal Year:	2004

DESCRIPTION (provided by applicant): Breast cancer is the second leading cause of cancer death among women in the United States. About 80% of such deaths occur in women age 65 years or older. These women also have a lower survival rate and are less likely to receive recommended treatment. Identifying geographic areas where survival from breast cancer among women 65 years of age or older is lower and the underlying factors responsible is important to ensure that differences in treatment are addressed and that interventions can be designed at a level where they can be implemented. The aims of this revised application are to: 1) examine small-area geographic clustering of breast cancer survival among women 66 years of age and older; 2) Determine the extent to which geographic variation of survival can be explained by the geographic variation in area social and economic deprivation among women age 66 and older; and 3) identify potential pathways by which area social and economic deprivation explains any geographic variation of breast cancer survival among women age 66 and older. Based on the reviewers' comments, we have refocused the conceptual model and associated hypotheses on delineating the geographic variation of area social and economic deprivation on the geographical variation of breast cancer survival and the pathways by which area deprivation influences this outcome. The analytic models have also been refocused and are described in more statistical detail. To address the specific aims, the following data sources will be linked: 1) 1992-1999 data from the Surveillance, Epidemiology, and End Results (SEER) program (survival, demographics, stage at diagnosis, treatment, tumor biology); 2) 1991- 1999 Medicare data and its linkage to the SEER data (comorbidity, treatment); 3) 1992-1999 data from the Centers for Medicare and Medicaid (availability of and proximity to medical care) and 4) the 1992-1999 intercensal estimates (area deprivation measures). Advanced Bayesian analyses of breast cancer survival will be performed. The findings of the proposed study will identify geographic disparities in survival and factors responsible, which can be used to develop and implement future interventions to reduce these disparities.




The role of poverty rate and racial distribution in the geographic clustering of breast cancer survival among older women: a geographic and multilevel analysis.
Authors: Schootman M. , Jeffe D.B. , Lian M. , Gillanders W.E. , Aft R. .
Source: American Journal Of Epidemiology, 2009-03-01 00:00:00.0; 169(5), p. 554-61.
EPub date: 2009-03-01 00:00:00.0.
PMID: 19103608
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Racial disparities in the development of breast cancer metastases among older women: a multilevel study.
Authors: Schootman M. , Jeffe D.B. , Gillanders W.E. , Aft R. .
Source: Cancer, 2009-02-15 00:00:00.0; 115(4), p. 731-40.
PMID: 19130463
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Area-level poverty is associated with greater risk of ambulatory-care-sensitive hospitalizations in older breast cancer survivors.
Authors: Schootman M. , Jeffe D.B. , Lian M. , Deshpande A.D. , Gillanders W.E. , Aft R. , Sumner W. .
Source: Journal Of The American Geriatrics Society, 2008 Dec; 56(12), p. 2180-7.
PMID: 19093916
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Surveillance mammography and the risk of death among elderly breast cancer patients.
Authors: Schootman M. , Jeffe D.B. , Lian M. , Aft R. , Gillanders W.E. .
Source: Breast Cancer Research And Treatment, 2008 Oct; 111(3), p. 489-96.
PMID: 17957465
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The effects of radiotherapy for the treatment of contralateral breast cancer.
Authors: Schootman M. , Jeffe D.B. , Gillanders W.E. , Yan Y. , Aft R. .
Source: Breast Cancer Research And Treatment, 2007 May; 103(1), p. 77-83.
PMID: 17033921
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Prognosis of metachronous contralateral breast cancer according to stage at diagnosis: the importance of early detection.
Authors: Schootman M. , Fuortes L. , Aft R. .
Source: Breast Cancer Research And Treatment, 2006 Sep; 99(1), p. 91-5.
PMID: 16555124
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A Bayesian semi-parametric model for colorectal cancer incidences.
Authors: Zhang S. , Sun D. , He C.Z. , Schootman M. .
Source: Statistics In Medicine, 2006-01-30 00:00:00.0; 25(2), p. 285-309.
PMID: 16381075
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