What is the clinical evidence from this study?

Study design: Observational. Population: Breast cancer (n=60388). Intervention: Neighborhood change (declining, stable, or upgrading vulnerability) vs. Stably low Social Vulnerability Index (CA-SVI) areas. Primary outcome: Breast cancer-specific mortality (RR 1.24, 95% CI 1.04-1.48).

What question did this study set out to answer?

To investigate how changing neighborhood dynamics impact breast cancer-specific mortality rates among women in Maryland from 2000 to 2019.

April 5, 2026

Abstract 2341: Using geospatial methods to analyze associations of neighborhood change on breast cancer mortality in Maryland, 2000-2019.

Q: What does this research mean for the field?

Neighborhoods becoming more disadvantaged are associated with an 11 to 24% higher risk of breast cancer mortality compared to stably low vulnerability areas. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Key Result

Neighborhoods becoming more disadvantaged were associated with an 11 to 24% higher risk of breast cancer mortality compared to stably low vulnerability areas (RR 1.24; 95% CrI 1.04-1.48).

Key Points

To investigate how changing neighborhood dynamics impact breast cancer-specific mortality rates among women in Maryland from 2000 to 2019.
Analyzed primary breast cancer cases from the Maryland Cancer Registry (2005-2019) with neighborhood data.
Calculated observed and expected breast cancer deaths by census tract, linked to the continuity-adjusted Social Vulnerability Index.
Classified neighborhoods as stable, upgrading, or declining based on changes in social vulnerability over time.
Used Bayesian negative binomial models to assess the relationship between neighborhood change and breast cancer mortality.
Among 60,388 breast cancer cases, 8,946 resulted in mortality.
Women in modestly improving neighborhoods had a 11% increased risk of mortality compared to stable low vulnerability areas.
Neighborhoods that became more disadvantaged showed an increased mortality risk of 11-24% for breast cancer.

Study Design

Type

Observational (n=60,388)

Structured PICO

Does neighborhood change status affect breast cancer-specific mortality in women with primary breast cancer?

Population

60,388 primary breast cancer cases diagnosed among women age ≥18 in the Maryland Cancer Registry between 2005-2019

Intervention

Neighborhood change status (declining, stable, or upgrading based on CA-SVI percentiles)

Comparator

Stably low CA-SVI neighborhoods

Outcome

Breast cancer-specific mortalityhard clinical

Both sustained neighborhood vulnerability and shifts toward greater disadvantage are associated with increased breast cancer-specific mortality.

Main Result

Effect estimate: RR 1.24 (95% CI 1.04-1.48)

Abstract

Abstract Purpose: To examine whether neighborhood change status (declining, stable, or upgrading) is associated with the risk of breast cancer (BC)-specific mortality. Background: Neighborhood-level social determinants of health are associated with BC mortality, but few studies have investigated how dynamic neighborhood conditions over time and geography (i.e., neighborhood trajectories) can modulate the risk of BC-specific mortality. Methods: We identified primary BC cases diagnosed among women age ≥18 in the Maryland Cancer Registry (NPCR) between 2005-2019 with valid census tract information at diagnosis (proxy for neighborhood). Observed and expected BC deaths were calculated by tract using 2000 standard female population and referent BC mortality rates for Maryland from 2018-2022 (age 50: 4.4 deaths/100k; age ≥50: 60.8 deaths/100k). Tracts were linked to a continuity-adjusted version of the Social Vulnerability Index (CA-SVI), which harmonized SVI component variables across years. Neighborhood change was defined as the difference in CA-SVI percentiles between consecutive 5-year periods (2000-2004, 2005-2009, 2010-2014, 2015-2019). Tracts were classified as stable (Low, Low-Medium, Medium-High, High CA-SVI)), upgrading (−25 to −49 or ≤−50 %ile; becoming moderately/substantially less disadvantaged), or declining (+25 to +49 or ≥+50 %ile; becoming moderately/substantially more disadvantaged). We evaluated the relationship between neighborhood change and BC mortality using Bayesian negative binomial space-time models that captured effects for geographic clustering and temporal trends. Models were adjusted for individual-level covariates (age, stage, grade, receipt of treatment surgery, chemotherapy, radiation, hormone, and tumor characteristics ER, PR, HER2 status), starting/ending CA-SVI categories, and county-level rurality (2013 USDA Beale Rural-Urban Continuum Codes). Results: Among 60,388 BC cases, 8,946 died as a result of their diagnosis. Women residing in neighborhoods that modestly improved (+1 cat.) had a slightly elevated risk of BC mortality compared to those living in areas of stably low CA-SVI (Relative risk RRInc =1.11, 95% Credible Interval CrI 1.01-1.22). Women living in neighborhoods that became more disadvantaged had between 11 to 24% higher risk of BC mortality (RRDecl1 cat.=1.11 1.01-1.02, RRDecl2 cat.=1.24 1.04-1.48). Conclusion: Both sustained vulnerability and shifts in neighborhood conditions were associated with BC-specific mortality. Marked declines showed the highest risk for BC mortality, but sustained vulnerability and modest upgrades also indicated elevated risk. These results highlight the importance of neighborhood contexts on cancer outcomes, emphasizing the need for longitudinal research evaluating how neighborhood trajectories might affect place-based inequities. Citation Format: Katherine L. Ho, Kassandra I. Alcaraz, Avonne E. Connor, Michael R. Desjardins. Using geospatial methods to analyze associations of neighborhood change on breast cancer mortality in Maryland, 2000-2019 abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2341.

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