Association Between Neighborhood Opportunity, Allostatic Load, and All-Cause Mortality in Patients With Breast Cancer

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Abstract

PURPOSE

Adverse neighborhood contextual factors may affect breast cancer outcomes through environmental, psychosocial, and biological pathways. The objective of this study is to examine the relationship between allostatic load (AL), neighborhood opportunity, and all-cause mortality among patients with breast cancer.

METHODS

Women age 18 years and older with newly diagnosed stage I-III breast cancer who received surgical treatment between January 1, 2012, and December 31, 2020, at a National Cancer Institute Comprehensive Cancer Center were identified. Neighborhood opportunity was operationalized using the 2014-2018 Ohio Opportunity Index (OOI), a composite measure derived from neighborhood level transportation, education, employment, health, housing, crime, and environment. Logistic and Cox regression models tested associations between the OOI, AL, and all-cause mortality.

RESULTS

The study cohort included 4,089 patients. Residence in neighborhoods with low OOI was associated with high AL (adjusted odds ratio, 1.21 [95% CI, 1.05 to 1.40]). On adjusted analysis, low OOI was associated with greater risk of all-cause mortality (adjusted hazard ratio [aHR], 1.45 [95% CI, 1.11 to 1.89]). Relative to the highest (99th percentile) level of opportunity, risk of all-cause mortality steeply increased up to the 70th percentile, at which point the rate of increase plateaued. There was no interaction between the composite OOI and AL on all-cause mortality ( P = .12). However, there was a higher mortality risk among patients with high AL residing in lower-opportunity environments (aHR, 1.96), but not in higher-opportunity environments (aHR, 1.02; P interaction = .02).

CONCLUSION

Lower neighborhood opportunity was associated with higher AL and greater risk of all-cause mortality among patients with breast cancer. Additionally, environmental factors and AL interacted to influence all-cause mortality. Future studies should focus on interventions at the neighborhood and individual level to address socioeconomically based disparities in breast cancer.

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Most cited references 45

Record: found
Abstract: found
Article: not found

A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

Mary E Charlson, Peter Pompei, Kathy L. Ales … (1987)

The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.

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Record: found
Abstract: found
Article: not found

Molecular portraits of human breast tumours.

Charles Perou, Therese Sørlie, Michael B. Eisen … (2001)

Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cell's identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.

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Record: found
Abstract: found
Article: not found

Breast cancer statistics, 2019

Carol DeSantis, Jiemin Ma, Mia Gaudet … (2019)

This article is the American Cancer Society's biennial update on female breast cancer statistics in the United States, including data on incidence, mortality, survival, and screening. Over the most recent 5-year period (2012-2016), the breast cancer incidence rate increased slightly by 0.3% per year, largely because of rising rates of local stage and hormone receptor-positive disease. In contrast, the breast cancer death rate continues to decline, dropping 40% from 1989 to 2017 and translating to 375,900 breast cancer deaths averted. Notably, the pace of the decline has slowed from an annual decrease of 1.9% during 1998 through 2011 to 1.3% during 2011 through 2017, largely driven by the trend in white women. Consequently, the black-white disparity in breast cancer mortality has remained stable since 2011 after widening over the past 3 decades. Nevertheless, the death rate remains 40% higher in blacks (28.4 vs 20.3 deaths per 100,000) despite a lower incidence rate (126.7 vs 130.8); this disparity is magnified among black women aged <50 years, who have a death rate double that of whites. In the most recent 5-year period (2013-2017), the death rate declined in Hispanics (2.1% per year), blacks (1.5%), whites (1.0%), and Asians/Pacific Islanders (0.8%) but was stable in American Indians/Alaska Natives. However, by state, breast cancer mortality rates are no longer declining in Nebraska overall; in Colorado and Wisconsin in black women; and in Nebraska, Texas, and Virginia in white women. Breast cancer was the leading cause of cancer death in women (surpassing lung cancer) in four Southern and two Midwestern states among blacks and in Utah among whites during 2016-2017. Declines in breast cancer mortality could be accelerated by expanding access to high-quality prevention, early detection, and treatment services to all women.

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Author and article information

Contributors

J.C. Chen: (View ORCID Profile)

Mohamed I. Elsaid: (View ORCID Profile)

Demond Handley: (View ORCID Profile)

Jesse J. Plascak: (View ORCID Profile)

Barbara L. Andersen: (View ORCID Profile)

Timothy M. Pawlik: (View ORCID Profile)

Samilia Obeng-Gyasi: (View ORCID Profile)

Journal

Title: Journal of Clinical Oncology

Abbreviated Title: JCO

Publisher: American Society of Clinical Oncology (ASCO)

ISSN (Print): 0732-183X

ISSN (Electronic): 1527-7755

Publication date Created: May 20 2024

Publication date (Print): May 20 2024

Volume: 42

Issue: 15

Pages: 1788-1798

Affiliations

[1 ]Division of Surgical Oncology, Department of Surgery, The Ohio State University, Columbus, OH

[2 ]Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH

[3 ]Secondary Data Core, Center for Biostatistics, College of Medicine, The Ohio State University, Columbus, OH

[4 ]Division of Cancer Prevention and Control, Department of Internal Medicine, The Ohio State University, Columbus, OH

[5 ]Department of Psychology, The Ohio State University, Columbus, OH

Article

DOI: 10.1200/JCO.23.00907

PubMed ID: 38364197

SO-VID: 2488cd5c-13c4-49e0-ae1e-afc4a3a56c46

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