Symptom Experience, Management, and Outcomes According to Race and Social Determinants Including Genomics, Epigenomics, and Metabolomics (SEMOARS + GEM): an Explanatory Model for Breast Cancer Treatment Disparity

J Cancer Educ. 2020 Jun;35(3):428-440. doi: 10.1007/s13187-019-01571-w.

Abstract

Even after controlling for stage, comorbidity, age, and insurance status, black women with breast cancer (BC) in the USA have the lowest 5-year survival as compared with all other races for stage-matched disease. One potential cause of this survival difference is the disparity in cancer treatment, evident in many population clinical trials. Specifically, during BC chemotherapy, black women receive less relative dose intensity with more dose reductions and early chemotherapy cessation compared with white women. Symptom incidence, cancer-related distress, and ineffective communication, including the disparity in patient-centeredness of care surrounding patient symptom reporting and clinician assessment, are important factors contributing to racial disparity in dose reduction and early therapy termination. We present an evidence-based overview and an explanatory model for racial disparity in the symptom experience during BC chemotherapy that may lead to a reduction in dose intensity and a subsequent disparity in outcomes. This explanatory model, the Symptom Experience, Management, Outcomes and Adherence according to Race and Social determinants + Genomics Epigenomics and Metabolomics (SEMOARS + GEM), considers essential factors such as social determinants of health, clinician communication, symptoms and symptom management, genomics, epigenomics, and pharmacologic metabolism as contributory factors.

Keywords: African-American; Breast cancer; Chemotherapy; Dose intensity; Social determinants; Symptom; Treatment disparity.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / ethnology*
  • Breast Neoplasms / mortality
  • Breast Neoplasms / therapy
  • Epigenomics*
  • Ethnicity / statistics & numerical data*
  • Female
  • Genomics*
  • Healthcare Disparities*
  • Humans
  • Metabolomics*
  • Social Determinants of Health*