Cause-specific mortality among patients with different molecular subtypes of T1-2N0M0 breast cancer: A population-based study

Medicine (Baltimore). 2021 Oct 29;100(43):e27605. doi: 10.1097/MD.0000000000027605.

Abstract

The objective of our study is to investigate mortality pattern and quantitatively assess prognostic risk for cause-specific death among T1-2N0M0 breast cancer survivors.The representative data of T1-2N0M0 breast cancer patients diagnosed between 2010 and 2016 was retrieved from the Surveillance, Epidemiology, and End Results program. Standardized mortality ratios (SMRs) were calculated taking US population as a reference. Cox regression analysis was conducted to analyze the potential prognostic factors for cause-specific mortality.A total of 161,966 patients were identified from the Surveillance, Epidemiology, and End Results database. After a median follow-up of 41 months, mortality occurred in 10,567 patients, of which 30.9% and 22.7% were attributed to breast cancer and cardiovascular diseases (CVDs). The standardized mortality ratios of CVD were 4.78, 4.27, 3.78, and 4.95 in patients with HR+/HER2+, HR-/HER2+, HR+/HER2-, and HR-/HER2- breast cancer compared to general US population, respectively. Cox proportional hazards regression analysis showed that the adjusted HRs of breast cancer-specific mortality were 0.999 (95% confidence interval [CI]: 0.879-1.135), 1.454 (95% CI: 1.246-1.697), 2.145 (95% CI: 1.962-2.345) for HR+/HER2+, HR-/HER2+, and HR-/HER2- breast cancer, respectively, as compared with HR+/HER2- subtype; HRs of CVD-specific death were 1.215 (95% CI: 1.041-1.418), 1.391 (95% CI: 1.209-1.601), and 1.515 (95% CI: 1.213-1.892), respectively. In addition, we found that older age at diagnosis, and black race were also independent predictors of CVD-specific death.In the present study, we revealed the mortality pattern of cause-specific mortality, and identified prognostic factors of overall mortality, breast cancer-specific mortality, and CVD-specific mortality in T1-2N0M0 breast cancer survivors, supporting early detection and more efficient CVD care for these patients.

MeSH terms

  • Adult
  • Age Factors
  • Age of Onset
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / mortality*
  • Breast Neoplasms / pathology*
  • Cancer Survivors / statistics & numerical data*
  • Cause of Death
  • Female
  • Humans
  • Middle Aged
  • Mortality / trends
  • Neoplasm Grading
  • Prognosis
  • Proportional Hazards Models
  • Racial Groups / statistics & numerical data
  • Regression Analysis
  • SEER Program