1. A tool to predict disparities in the timeliness of surgical treatment for breast cancer patients in the USA
- Author
-
Christopher G. Verdone, Jennifer A. Bayron, Cecilia Chang, Chihsiung E. Wang, Elin R. Sigurdson, Allison A. Aggon, Andrea Porpiglia, Maureen V. Hill, Mary T. Pronovost, and Richard J. Bleicher
- Subjects
Diversity ,Cancer Research ,Disparities ,Breast Neoplasms ,Medicare ,United States ,Preclinical Study ,Breast cancer ,Risk factors ,Socioeconomic Factors ,Oncology ,Socioeconomic status ,Ethnicity ,Humans ,Female ,Equity and inclusion ,Delays ,Healthcare Disparities ,Aged - Abstract
Purpose Breast cancer outcomes are impaired by both delays and disparities in treatment. This study was performed to assess their relationship and to provide a tool to predict patient socioeconomic factors associated with risk for delay. Methods The National Cancer Database was reviewed between 2004 and 2017 for patients with non-metastatic breast cancer managed with upfront surgery. Times to treatment were measured from the date of diagnosis. Patient, tumor, and treatment factors were assessed with attention paid to sociodemographic variables. Results 514,187 patients remained after exclusions, with 84.3% White, 10.8% Black, 3.7% Asian, and Hispanics comprising 5.6% of the cohort. Medicaid and uninsured patients had longer mean adjusted time to surgery (≥ 46 days) versus private (36.7 days), Medicare (35.9 days), or other governmental insurance (39.8 days). After adjustment, Black race and Hispanic ethnicity were most impactful, adding 6.0 and 6.4 preoperative days, 10.9 and 11.5 days to chemotherapy, 11.1 and 9.1 days to radiation, and 12.5 and 8.9 days to endocrine therapy, respectively. Income, education, and insurance, among other factors, also affected delay. A nomogram, including race and sociodemographic factors, was created to predict the risk of preoperative delay. Conclusion Significant disparities exist in timeliness of care for factors, including but not limited to, race and ethnicity. Although exact causes cannot be discerned, these data indicate population subsets whose intervals of care risk being longer than those specified by national quality standards. The nomogram created here may help direct resources to those at highest risk of incurring a treatment delay. Supplementary Information The online version contains supplementary material available at 10.1007/s10549-021-06460-9.
- Published
- 2022