ArticleSocial science & medicine (1982)2017
Assessment of spatial variation in breast cancer-specific mortality using Louisiana SEER data.
Article in Social science & medicine (1982), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Industrial Pollution and Health in Louisiana: A Systematic Review of Quantitative and Qualitative Studies.Current environmental health reports · 2026Pooled it
- Review
- Spatial-temporal Bayesian accelerated failure time models for survival endpoints with applications to prostate cancer registry data.BMC medical research methodology · 2024Article
- Relative burden of cancer and noncancer mortality among long-term survivors of differentiated thyroid cancer in the US.Frontiers in endocrinology · 2024Article
- Understanding the role of environmental and socioeconomic factors in the geographic variation of breast cancer risk in the US-wide Sister Study.Environmental research · 2023Article
- Relative Burden of Cancer and Noncancer Mortality Among Long-Term Survivors of Breast, Prostate, and Colorectal Cancer in the US.JAMA network open · 2023Article
- Intra-urban spatial variability of breast and cervical cancer mortality in the city of São Paulo: analysis of associated factors.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2023Article
- Implications for health system resilience: Quantifying the impact of the COVID-19-related stay at home orders on cancer screenings and diagnoses in southeastern North Carolina, USA.Preventive medicine · 2022Article
- Spatial Variation of Survival for Colorectal Cancer in Malaysia.International journal of environmental research and public health · 2021Article
- Evaluating overall survival and competing risks of survival in patients with early-stage breast cancer using a comprehensive nomogram.Cancer medicine · 2020Article
- Spatial patterns in prostate Cancer-specific mortality in Pennsylvania using Pennsylvania Cancer registry data, 2004-2014.BMC cancer · 2020Article
- Temporally dependent accelerated failure time model for capturing the impact of events that alter survival in disease mapping.Biostatistics (Oxford, England) · 2019Article
- Trends in Colorectal Cancer Incidence and Survival in Iowa SEER Data: The Timing of It All.Clinical colorectal cancer · 2019Article
- A data-driven approach for estimating the change-points and impact of major events on disease risk.Spatial and spatio-temporal epidemiology · 2019Article
- Gaining relevance from the random: Interpreting observed spatial heterogeneity.Spatial and spatio-temporal epidemiology · 2018Article
- The fluctuating incidence, improved survival of patients with breast cancer, and disparities by age, race, and socioeconomic status by decade, 1981-2010.Cancer management and research · 2018Article
- Integration of Cancer Registry Data into the Text Information Extraction System: Leveraging the Structured Data Import Tool.Journal of pathology informatics · 2018Article
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4 authors.
Funding
Abstract
backgroundPrevious studies suggest spatial differences in mortality for many types of cancer, including breast cancer. Identifying explanations for these spatial differences results in a better understanding of what leads to longer survival time.
methodsWe used a Bayesian accelerated failure time model with spatial frailty terms to investigate potential spatial differences in breast cancer mortality following breast cancer diagnosis using 2000-2013 Louisiana SEER data.
resultsThere are meaningful spatial differences in breast cancer mortality across the parishes of Louisiana, even after adjusting for known demographic and clinical risk factors. For example, the average survival time of a woman diagnosed in Orleans parish was 1.51 times longer than that of a woman diagnosed in Terrebonne parish. Additionally, there is evidence to suggest shorter survival times in lower income parishes along the Red and Mississippi Rivers, as well as parishes with lower socioeconomic status, less access to care and fresh food, worse quality of care, and more workers in certain industries.
conclusionThe addition of spatial frailties to account for an individual's geographic location is useful when analyzing breast cancer mortality data. Our findings suggest that survival following breast cancer diagnosis could potentially be improved if socioeconomic status differences were addressed, healthcare improved in quality and became more accessible, and certain industrial situations were improved for individuals diagnosed in parishes identified as having shorter average survival times.
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