Can Differences in Breast Cancer Utilities Explain Disparities in Breast Cancer Care?


  • No conflicts of interest to declare.

  • Versions of this work were presented at the 2004 Annual Meeting of the NIH Building Interdisciplinary Research Careers in Women's Health (BIRCWH) Program, Bethesda, MD, the 2005 Annual Meeting of the Society of General Internal Medicine, New Orleans, LA, and the 2005 Regional BIRCWH Meeting, Providence, RI.

Address correspondence and requests for reprints to Dr. Schleinitz: DGIM, Rhode Island Hospital, 593 Eddy Street, MPB-1, Providence, RI 02903 (e-mail:


BACKGROUND: Black, older, and less affluent women are less likely to receive adjuvant breast cancer therapy than their counterparts. Whereas preference contributes to disparities in other health care scenarios, it is unclear if preference explains differential rates of breast cancer care.

OBJECTIVE: To ascertain utilities from women of diverse backgrounds for the different stages of, and treatments for, breast cancer and to determine whether a treatment decision modeled from utilities is associated with socio-demographic characteristics.

PARTICIPANTS: A stratified sample (by age and race) of 156 English-speaking women over 25 years old not currently undergoing breast cancer treatment.

DESIGN AND MEASUREMENTS: We assessed utilities using standard gamble for 5 breast cancer stages, and time-tradeoff for 3 therapeutic modalities. We incorporated each subject's utilities into a Markov model to determine whether her quality-adjusted life expectancy would be maximized with chemotherapy for a hypothetical, current diagnosis of stage II breast cancer. We used logistic regression to determine whether socio-demographic variables were associated with this optimal strategy.

RESULTS: Median utilities for the 8 health states were: stage I disease, 0.91 (interquartile range 0.50 to 1.00); stage II, 0.75 (0.26 to 0.99); stage III, 0.51 (0.25 to 0.94); stage IV (estrogen receptor positive), 0.36 (0 to 0.75); stage IV (estrogen receptor negative), 0.40 (0 to 0.79); chemotherapy 0.50 (0 to 0.92); hormonal therapy 0.58 (0 to 1); and radiation therapy 0.83 (0.10 to 1). Utilities for early stage disease and treatment modalities, but not metastatic disease, varied with socio-demographic characteristics. One hundred and twenty-two of 156 subjects had utilities that maximized quality-adjusted life expectancy given stage II breast cancer with chemotherapy. Age over 50, black race, and low household income were associated with at least 5-fold lower odds of maximizing quality-adjusted life expectancy with chemotherapy, whereas women who were married or had a significant other were 4-fold more likely to maximize quality-adjusted life expectancy with chemotherapy.

CONCLUSIONS: Differences in utility for breast cancer health states may partially explain the lower rate of adjuvant therapy for black, older, and less affluent women. Further work must clarify whether these differences result from health preference alone or reflect women's perceptions of sources of disparity, such as access to care, poor communication with providers, limitations in health knowledge or in obtaining social and workplace support during therapy.