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Association of Race/Ethnicity and Population Density with Disparities in Timeliness of Rectal Cancer Therapy

Hill, Susanna S.
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Student Authors
Faculty Advisor
Karim AlaviRobert Goldberg
Academic Program
Master of Science in Clinical Investigation
Document Type
Master's Thesis
Publication Date
2020-04-30
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Abstract

Objective:

Access to care is key to effective rectal cancer treatment. We hypothesized that ethnic/racial minorities living in high population density areas would have the greatest delays in cancer care compared to whites living in medium population density areas.

Methods:

Using 2004-2016 National Cancer DataBase data, we identified stage I-III patients with invasive rectal adenocarcinoma who underwent surgery. The data were analyzed by race/ethnicity (whites, blacks, or Hispanics) and population density (metropolitan or urban/rural). Multivariable ANCOVA was performed to evaluate the duration of time from diagnosis to surgery.

Results:

The study population consisted of 76,131 patients: 65,172 Non-Hispanic whites (NHW; 85.6%), 6,167 Non-Hispanic blacks (NHB; 8.1%), and 4,792 Hispanics (6.3%). Of these, 61,363 patients (80.6%) lived in metropolitan areas.

Among direct-to-surgery patients, the greatest difference in mean time from diagnosis to surgery was 20.3 days (urban/rural NHW, 53.3 days, vs. metropolitan Hispanics, 73.6 days). Among patients receiving neoadjuvant therapy, the greatest difference in mean time from diagnosis to surgery was 18.8 days (urban/rural NHW, 136.9 days, vs. metropolitan NHB, 155.7 days).

After multivariable adjustment for several socioeconomic and clinical factors, among direct-to-surgery patients, metropolitan Hispanics had a 16.5-day delay (95% CI 12.9-20.0) compared with urban/rural NHW. In patients receiving neoadjuvant therapy, metropolitan NHB had an 18.1-day delay (95% CI 16.1-20.0) compared to urban/rural NHW.

Conclusion:

The combination of high population density and racial/ethnic minority status was associated with delays in rectal cancer care that persisted after adjusting for other important factors. Understanding which populations are at risk and perceived obstacles to timely care will help inform interventions to minimize treatment access disparities.

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10.13028/p39z-2298
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