Independent effects of comorbidities and race on breast cancer mortality.

e13791 Background: Racial disparities and breast cancer outcomes are well-documented. Socioeconomic inequalities, diagnostic delays, and comorbid conditions impact these outcomes. Specific comorbidities, for example, diabetes, hypertension, and congestive heart failure, have been independently linked to poorer survival outcomes in breast cancer patients. The association of medical comorbidities and race in breast cancer patients remains inadequately characterized. Methods: This retrospective cohort study included breast cancer patients between 2018 and 2023 using the Syapse database of cancer patients in the United States. White and Asian patients were combined into one group (W/A), and Black, Native American, and Pacific Islander were combined into another (B/O). Standard statistics were used to compare baseline variables of comorbidities and racial groups. Cox regression models and random forest models were used to analyze factors affecting all-cause mortality (ACM). The comorbidities included in the analysis were cardiovascular disease (CVD), diabetes (DM), chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), peripheral vascular disease (PVD), and renal disease (CKD). Results: Among 31,150 patients (W/A = 26,136; B/O = 5,014), median age was 61 and 62 years respectively. B/O patients demonstrated higher ACM when controlling for comorbidities (HR 1.3 (1.2-1.4)). All comorbidities increased ACM in both racial groups as follows: CVD (HR 2.5 (1.6, 3.9)), DM (HR 1.6 (1.2, 2.0)), COPD (HR 1.5 (1.0, 2.1)), CHF (HR 2.5 (1.8, 3.7)), PVD (HR 2.3 (1.6, 2.4)), CKD (HR 2.6 (2.0, 3.3)). CKD and CHF were identified on forest plots to be the most significant comorbidities to predict ACM. No significant interaction between independent comorbidities and race was identified, specifically: CVD ( p = 0.665), DM ( p = 0.665), COPD ( p = 0.06), CHF ( p = 0.06), PVD ( p = 0.373), CKD ( p = 0.844). In addition, breast cancer stage was the most important factor to determine ACM (HR 17.4 (14.4-21)). Conclusions: B/O patients demonstrated higher mortality even after controlling for comorbidities, indicating a possible implication for socioeconomic factors or a delay in diagnosis as a cause of ACM in these patients. Regardless of race, comorbidities increased ACM with CKD and CHF having the highest risk of ACM. Despite both race and comorbidities independently increasing mortality, no significant interaction was identified potentially because of the strong impact comorbidities had on mortality regardless of race. Further analyses will control for breast cancer stage, explore additional socioeconomic factors, and will assess the effects of multiple comorbidities at once.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.e13791
Primary Topic
Global Cancer Incidence and Screening
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Independent effects of comorbidities and race on breast cancer mortality.

Murtaza Qazi, Amrutha Mittapalli, Mark J. Koury, Arezoo Ghaneie et al.
1 links
Journal of Clinical Oncology
Global Cancer Incidence and Screening
article

Independent effects of comorbidities and race on breast cancer mortality.

Murtaza Qazi, Amrutha Mittapalli, Mark J. Koury, Arezoo Ghaneie, Stephanie Kjelstrom, Alisha Maity
article en

Abstract

e13791 Background: Racial disparities and breast cancer outcomes are well-documented. Socioeconomic inequalities, diagnostic delays, and comorbid conditions impact these outcomes. Specific comorbidities, for example, diabetes, hypertension, and congestive heart failure, have been independently linked to poorer survival outcomes in breast cancer patients. The association of medical comorbidities and race in breast cancer patients remains inadequately characterized. Methods: This retrospective cohort study included breast cancer patients between 2018 and 2023 using the Syapse database of cancer patients in the United States. White and Asian patients were combined into one group (W/A), and Black, Native American, and Pacific Islander were combined into another (B/O). Standard statistics were used to compare baseline variables of comorbidities and racial groups. Cox regression models and random forest models were used to analyze factors affecting all-cause mortality (ACM). The comorbidities included in the analysis were cardiovascular disease (CVD), diabetes (DM), chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), peripheral vascular disease (PVD), and renal disease (CKD). Results: Among 31,150 patients (W/A = 26,136; B/O = 5,014), median age was 61 and 62 years respectively. B/O patients demonstrated higher ACM when controlling for comorbidities (HR 1.3 (1.2-1.4)). All comorbidities increased ACM in both racial groups as follows: CVD (HR 2.5 (1.6, 3.9)), DM (HR 1.6 (1.2, 2.0)), COPD (HR 1.5 (1.0, 2.1)), CHF (HR 2.5 (1.8, 3.7)), PVD (HR 2.3 (1.6, 2.4)), CKD (HR 2.6 (2.0, 3.3)). CKD and CHF were identified on forest plots to be the most significant comorbidities to predict ACM. No significant interaction between independent comorbidities and race was identified, specifically: CVD ( p = 0.665), DM ( p = 0.665), COPD ( p = 0.06), CHF ( p = 0.06), PVD ( p = 0.373), CKD ( p = 0.844). In addition, breast cancer stage was the most important factor to determine ACM (HR 17.4 (14.4-21)). Conclusions: B/O patients demonstrated higher mortality even after controlling for comorbidities, indicating a possible implication for socioeconomic factors or a delay in diagnosis as a cause of ACM in these patients. Regardless of race, comorbidities increased ACM with CKD and CHF having the highest risk of ACM. Despite both race and comorbidities independently increasing mortality, no significant interaction was identified potentially because of the strong impact comorbidities had on mortality regardless of race. Further analyses will control for breast cancer stage, explore additional socioeconomic factors, and will assess the effects of multiple comorbidities at once.

Journal of Clinical OncologyVol. 43(16_suppl)
Lankenau Institute for Medical Research (US), Lankenau Medical Center (US)
Openalex Percentile: Top 82%
Global Cancer Incidence and Screening
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.