Causes of death after breast cancer diagnosis: A US population‐based analysis

Afifi, Ahmed; Saad, Anas M.; Al‐Husseini, Muneer J.; Elmehrath, Ahmed O.; Northfelt, Donald W.; Sonbol, Mohamad Bassam

doi:10.1002/cncr.32648

Cited by 133 publications

(111 citation statements)

References 37 publications

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“…As advances in treatment options continue to improve outcomes for women with early breast cancer, women with highly treatable early‐stage HR+ tumors are more likely to die of causes other than their early breast cancer 28 . A recent study showed that among women with breast cancer who died 10 or more years after their diagnosis, 60.9% died of noncancer causes, whereas 23.6% and 15.5% died of breast cancer and other cancers, respectively 29 . Even within the 5 to 10 years after the diagnosis, 48.4% died of noncancer causes, and regardless of the time since diagnosis, Black women had higher standardized mortality ratios for individual noncancer causes of death 29 .…”

Section: Introductionmentioning

confidence: 99%

“…A recent study showed that among women with breast cancer who died 10 or more years after their diagnosis, 60.9% died of noncancer causes, whereas 23.6% and 15.5% died of breast cancer and other cancers, respectively 29 . Even within the 5 to 10 years after the diagnosis, 48.4% died of noncancer causes, and regardless of the time since diagnosis, Black women had higher standardized mortality ratios for individual noncancer causes of death 29 . Noncancer causes include chronic diseases that, like cancer, are associated with advancing age, and many are obesity‐related: heart disease, stroke, diabetes mellitus, kidney disease, and hypertension 30…”

Section: Introductionmentioning

confidence: 99%

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Obesity, comorbidities, and treatment selection in Black and White women with early breast cancer

Nyrop

Damone

Deal

et al. 2020

Cancer

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Background This study investigates obesity and comorbidity in Black and White women with early breast cancer (stages I‐III) and their potential impact on treatment decisions for patients with hormone receptor–positive (HR+)/human epidermal growth factor receptor 2–negative (HER2–) tumors. Methods In this retrospective chart review, comparisons of frequencies for Black and White patients were calculated with the Fisher exact test. Log binomial regression was used to estimate prevalence ratios (PRs) with 95% confidence intervals for total and individual comorbidities, and multivariable modeling was used to estimate PRs adjusted for age and body mass index (BMI). Results In a sample of 548 patients, 26% were Black, and 74% were White. Sixty‐two percent of Black patients and 32% of White patients were obese (BMI ≥ 30 kg/m2; P < .0001). Seventy‐five percent of Black patients and 87% of White patients had HR+ tumors (P = .001). Significant intergroup differences were seen for 2 or more total comorbidities (62% of Blacks vs 47% of Whites; P = .001), 2 or more obesity‐related comorbidities (33% vs 10%; P < .0001), hypertension (60% vs 32%; P < .0001), diabetes mellitus (23% vs 6%; P < .0001), hypercholesterolemia or hyperlipidemia (28% vs 18%; P = .02), and hypothyroidism (4% vs 11%; P = .012). In women with HR+/HER2– tumors, there were no intergroup differences in treatment decisions regarding the type of surgery, chemotherapy regimen, radiation, or endocrine treatment despite significant differences in the prevalence of obesity and comorbidities. Conclusions This study documents significant disparities between Black and White women with early breast cancer with regard to high rates of obesity, overall comorbidities, and obesity‐related comorbidities, and it highlights the prevalence of competing risks that may complicate outcomes in breast cancer.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Obesity, comorbidities, and treatment selection in Black and White women with early breast cancer

Nyrop

Damone

Deal

et al. 2020

Cancer

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“…Prior studies have reported on the non-cancer causes of death among patients with various cancer (e.g. prostate [9], breast [10], and oropharynx [11]). Moreover, non-cancer causes of death in long-term bladder cancer survivors were also investigated in a previously published study [12].…”

Section: Introductionmentioning

confidence: 99%

Short-term mortality risks among patients with non-metastatic bladder cancer

Zhai¹,

Tang²,

Li³

et al. 2020

BMC Cancer

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Background Population-based analysis for the short-term non-bladder cancer related mortality among patients with non-metastatic bladder cancer is currently lacking. The objective of the current study was to assess and quantify cause of death after bladder cancer diagnosis. Methods The custom Surveillance, Epidemiology, and End Results (SEER) dataset for standardized mortality ratios (SMRs) was utilized to identify 24,074 patients who were diagnosed with nonmetastatic (M0) bladder cancer from 2014 to 2015. SMRs for causes of death were calculated. Risk factors for bladder cancer-specific mortality, competing mortality, second-cancer mortality, and noncancer mortality were determined using either multivariable Cox or competing risk regression models. Results Among all the 4179 (17.4%) deaths occurred during the follow-up period, almost half of them (44.2%) were attributed to non-bladder cancer cause, including second non-bladder cancer (10%) and other non-cancer causes (34.2%). The most common noncancer causes of death were heart diseases followed by chronic obstructive pulmonary disease. Patients had a higher risk of death from second malignancies (SMR, 1.59; 95% CI, 1.47–1.74) compared with death from first malignancies in the US general population, and also had higher risks of death from heart diseases (SMR, 1.29; 95% CI, 1.18–1.40) and chronic obstructive pulmonary disease (SMR, 1.52; 95% CI, 1.29–1.79) compared with the US general population. Additionally, some risk factors for competing second malignancies or noncancer mortality were determined, such as age, gender, marital status and treatment modalities. Conclusions Death from non-bladder cancer cause contributed to almost half of all deaths in bladder cancer survivors during the short-term follow-up period. These findings can inform medical management and assist clinicians in counseling those survivors regarding their short-term health risks.

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“…During 10 years of follow-up, the non-BCSD rate of pN0(i+) and pN0(i − ) was as high as 71.33 and 79.00%, respectively. A study on the causes of death for FBC patients has confirmed that the main cause of death was not breast cancer but heart disease 5 years after the diagnosis, and the proportion of BCSD will gradually decrease ( 27 ). Therefore, for patients with early-stage breast cancer, it is very important to pay close attention to other non-cancer diseases, especially cardiovascular health.…”

Section: Discussionmentioning

confidence: 99%

A Competing Risk Analysis Model to Determine the Prognostic Value of Isolated Tumor Cells in Axillary Lymph Nodes for T1N0M0 Breast Cancer Patients Based on the Surveillance, Epidemiology, and End Results Database

Zhang

et al. 2020

Front. Oncol.

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Introduction: Knowledge of the association between isolated tumor cells (ITCs) in breast cancer patients and the outcome is very limited. We aimed to determine the prognostic value of axillary lymph node ITCs for T1N0M0 female breast cancer (FBC) patients. Methods: Data for T1N0M0 FBC patients staged ITCs negative [pN0(i−)] and positive [pN0(i+)] were extracted from the Surveillance, Epidemiology, and End Results database from 2004 to 2015. Prognostic predictors were identified by Kaplan-Meier analysis, competing risk model, and Fine-Gray multivariable regression model. Results: A total of 94,599 subjects were included, 88,632 of whom were staged at pN0(i−) and 5,967 were pN0(i+). Patients staged pN0(i+) had worse breast cancerspecific survival (BCSS) [hazard ratio (HR): 1.298, 95% CI = 1.069-1.576, P = 0.003] and higher breast cancer-specific death (BCSD) rate (Gray's test, P = 0.002) than pN0(i−) group. In the Fine-Gray multivariable regression analysis, the pN0(i+) group had higher BCSD rate (HR: 1.321, 95% CI = 1.109-1.575, P = 0.002) than pN0(i−) group. In subgroup analyses, no significant difference in BCSD was shown between the chemotherapy and non-chemotherapy subgroup (Gray's test, P = 0.069) or radiotherapy and non-radiotherapy subgroup (Gray's test, P = 0.096). Conclusion: ITC was independently related to the increase of the BCSD rate and could be identified as a reliable survival predictor for T1N0M0 FBC patients.

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Causes of death after breast cancer diagnosis: A US population‐based analysis

Cited by 133 publications

References 37 publications

Obesity, comorbidities, and treatment selection in Black and White women with early breast cancer

Obesity, comorbidities, and treatment selection in Black and White women with early breast cancer

Short-term mortality risks among patients with non-metastatic bladder cancer

A Competing Risk Analysis Model to Determine the Prognostic Value of Isolated Tumor Cells in Axillary Lymph Nodes for T1N0M0 Breast Cancer Patients Based on the Surveillance, Epidemiology, and End Results Database

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