Abstract C126: Disparities in time-to-treat insured patients with newly diagnosed cancer in a vertically integrated healthcare system

Abstract Purpose. After a cancer diagnosis, delays in initiating treatment may impact treatment response, disease progression, adverse health events, and overall survival. Race and socioeconomic status (SES) may be factors in initiating cancer treatment. Complicating this issue is the lack of insurance or underinsurance. Thus, the purpose of this study was to assess the influence of race/ethnicity and SES on time to treatments for insured patients diagnosed with cancer in a vertically integrated healthcare system. Methods. We conducted a cross-sectional nested study within a cohort of patients diagnosed with cancer between 2010 and 2018 from Kaiser Permanente Southern California (KPSC), a vertically integrated healthcare system. Patients of all ages and all cancer anatomical sites were included. Patients with in-situ cancers were excluded, with no other exclusion criteria. The main independent variables are race/ethnicity and SES, and the dependent variable is time to initial treatment. All information was pulled from the KPSC Cancer Registry, including race/ethnicity, and treatments (surgical; radiation; chemotherapy; immunotherapy; hormonal). SES was categorized into quintiles based on geocoded expected income using home addresses from census tract data. For each patient, we calculated days from diagnosis to first treatment. Results. We identified 153,270 patients of all ages with cancers of all anatomical sites diagnosed between 2010 and 2018, of which 125,943 received treatment. When examining racial groups, the mean time to treatment for White, Black, Hispanic, Asian/PI, and other patients was 42.5, 52.6, 44.3, 44.1, and 41.2 days, respectively. For White patients, mean time to treatment was 42.4 days in the lower 20% income quintile and 42.7 days in the top 20% income quintile. For Black patients, mean time to treat was 53.9 days in the lower 20% income quintile and 52.8 days in the top 20% income quintile. For Hispanic patients, mean time to treat was 45.8 days in the lower 20% income quintile and 42.1 days in the top 20% income quintile. For Asian/PI patients, mean time to treat was 44.1 days in the lower 20% income quintile and 43.5 days in the top 20% income quintile. For other patients, mean time to treat was 51.4 days in the lower 20% income quintile and 39.2 days in the top 20% income quintile. Within each SES quintile, Black patients consistently started cancer treatment later than other racial/ethnic groups. Conclusion. We found minimal disparities in time to initial treatment based on SES in this vertically integrated system of care. Within each of the White, Black, and Asian racial groups, the difference in time to treatment between the highest and lowest SES groups was less than 2%. This difference was closer to 7% in Hispanic patients. Additional work is necessary to elucidate reasons why Black patients initiate cancer treatments later than other racial groups and if this affects recurrence or survival. Citation Format: Robert Cooper, Reina Haque, Andrea Young, Zimin Zhuang. Disparities in time-to-treat insured patients with newly diagnosed cancer in a vertically integrated healthcare system [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C126.

Authors

Institutions

Publication Details

Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2024-09-21
DOI
https://doi.org/10.1158/1538-7755.disp24-c126
Primary Topic
Economic and Financial Impacts of Cancer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract C126: Disparities in time-to-treat insured patients with newly diagnosed cancer in a vertically integrated healthcare system

Robert Michael Cooper, Zimin Zhuang, Andrea S. Young, Reina Haque
Cancer Epidemiology Biomarkers & Prevention
Economic and Financial Impacts of Cancer
article

Abstract C126: Disparities in time-to-treat insured patients with newly diagnosed cancer in a vertically integrated healthcare system

Robert Michael Cooper, Zimin Zhuang, Andrea S. Young, Reina Haque
article en

Abstract

Abstract Purpose. After a cancer diagnosis, delays in initiating treatment may impact treatment response, disease progression, adverse health events, and overall survival. Race and socioeconomic status (SES) may be factors in initiating cancer treatment. Complicating this issue is the lack of insurance or underinsurance. Thus, the purpose of this study was to assess the influence of race/ethnicity and SES on time to treatments for insured patients diagnosed with cancer in a vertically integrated healthcare system. Methods. We conducted a cross-sectional nested study within a cohort of patients diagnosed with cancer between 2010 and 2018 from Kaiser Permanente Southern California (KPSC), a vertically integrated healthcare system. Patients of all ages and all cancer anatomical sites were included. Patients with in-situ cancers were excluded, with no other exclusion criteria. The main independent variables are race/ethnicity and SES, and the dependent variable is time to initial treatment. All information was pulled from the KPSC Cancer Registry, including race/ethnicity, and treatments (surgical; radiation; chemotherapy; immunotherapy; hormonal). SES was categorized into quintiles based on geocoded expected income using home addresses from census tract data. For each patient, we calculated days from diagnosis to first treatment. Results. We identified 153,270 patients of all ages with cancers of all anatomical sites diagnosed between 2010 and 2018, of which 125,943 received treatment. When examining racial groups, the mean time to treatment for White, Black, Hispanic, Asian/PI, and other patients was 42.5, 52.6, 44.3, 44.1, and 41.2 days, respectively. For White patients, mean time to treatment was 42.4 days in the lower 20% income quintile and 42.7 days in the top 20% income quintile. For Black patients, mean time to treat was 53.9 days in the lower 20% income quintile and 52.8 days in the top 20% income quintile. For Hispanic patients, mean time to treat was 45.8 days in the lower 20% income quintile and 42.1 days in the top 20% income quintile. For Asian/PI patients, mean time to treat was 44.1 days in the lower 20% income quintile and 43.5 days in the top 20% income quintile. For other patients, mean time to treat was 51.4 days in the lower 20% income quintile and 39.2 days in the top 20% income quintile. Within each SES quintile, Black patients consistently started cancer treatment later than other racial/ethnic groups. Conclusion. We found minimal disparities in time to initial treatment based on SES in this vertically integrated system of care. Within each of the White, Black, and Asian racial groups, the difference in time to treatment between the highest and lowest SES groups was less than 2%. This difference was closer to 7% in Hispanic patients. Additional work is necessary to elucidate reasons why Black patients initiate cancer treatments later than other racial groups and if this affects recurrence or survival. Citation Format: Robert Cooper, Reina Haque, Andrea Young, Zimin Zhuang. Disparities in time-to-treat insured patients with newly diagnosed cancer in a vertically integrated healthcare system [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C126.

Cancer Epidemiology Biomarkers & PreventionVol. 33(9_Supplement)
Kaiser Permanente (US)
No poverty
Openalex Percentile: Top 80%
Economic and Financial Impacts of Cancer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.