Journal article
RACIAL DISPARITIES IN CANCER GUIDELINE CONCORDANT TREATMENT USING SEER DATA FOR NON-SMALL CELL LUNG CANCER PATIENTS
JTO clinical and research reports, Vol.6(1), 100747
01/2025
DOI: 10.1016/j.jtocrr.2024.100747
PMCID: PMC11699381
PMID: 39758596
Abstract
Despite efforts to achieve healthcare equality, racial/ethnic disparities persist in lung cancer survival in the United States, with Non-Hispanic Black patients experiencing higher mortality compared to Non-Hispanic Whites. Prior research often focused on single treatments, overlooking the broad range of options available. We aimed to highlight disparities in survival and receipt of comprehensive lung cancer treatment by developing a Guideline Concordant Initial Treatment (GCIT) indicator based on disease stage and recommended treatment.
Using SEER data on 377,370 Non-Small Cell Lung Cancer patients, we derived a GCIT indicator based on National Comprehensive Cancer Network guidelines. Observed probabilities and logistic regression models adjusted for age, disease stage, and race were used to assess racial disparities in treatment and survival, with the Kaplan-Meier method evaluating survival rates. Racial/ethnic groups analyzed included Non-Hispanic White, Non-Hispanic Black, Asian/Pacific Islander, Hispanic, and American Indian/Alaska Native.
Non-Hispanic Black patients had lower odds of receiving GCIT (OR 0.80; 95% CI 0.78–0.82) and surviving two years post-diagnosis (OR 0.80; 95% CI 0.78–0.82). Non-Hispanic Asians had the highest odds of receiving GCIT (OR 1.02; 95% CI 0.99–1.05). Patients receiving GCIT showed improved survival, with early-stage patients experiencing median survival of 67-102 months, compared to 11-17 months for those without GCIT.
Receiving GCIT significantly improves survival across all races, though disparities in receipt are observed. Interventions are needed to ensure equitable access to guideline-concordant care and reduce survival disparities for patients.
Details
- Title: Subtitle
- RACIAL DISPARITIES IN CANCER GUIDELINE CONCORDANT TREATMENT USING SEER DATA FOR NON-SMALL CELL LUNG CANCER PATIENTS
- Creators
- Eric Ababio Anyimadu - Electrical and Computer Engineering, University of IowaJacklyn Engelbart - University of IowaJason Semprini - Department of Health Management & Policy, University of IowaAmanda Kahl - Department of Epidemiology, University of IowaCameron Trentz - Electrical and Computer Engineering, University of IowaJohn M. Buatti - Department of Radiation Oncology, University of IowaThomas Casavant - University of Iowa, Electrical and Computer EngineeringMary Charlton - Department of Epidemiology, University of IowaGuadalupe Canahuate - Electrical and Computer Engineering, University of Iowa
- Resource Type
- Journal article
- Publication Details
- JTO clinical and research reports, Vol.6(1), 100747
- DOI
- 10.1016/j.jtocrr.2024.100747
- PMID
- 39758596
- PMCID
- PMC11699381
- NLM abbreviation
- JTO Clin Res Rep
- ISSN
- 2666-3643
- eISSN
- 2666-3643
- Publisher
- Elsevier Inc
- Grant note
- University of Iowa Jumpstarting Tomorrow ProgramNational Insitute of Health (NIH) /National Cancer Institute (NCI): HHSN261201800012I/HHSN26100001, P30 CA086862 NIH-NIDCD: DC002842, DC012049, DC017955
This work received support from The University of Iowa Jumpstarting Tomorrow Program, the National Insitute of Health (NIH) /National Cancer Institute (NCI) contract number: HHSN261201800012I/HHSN26100001; NIH/NCI P30 CA086862) and NIH-NIDCD grants DC002842, DC012049, and DC017955.
- Language
- English
- Electronic publication date
- 10/2024
- Date published
- 01/2025
- Academic Unit
- Electrical and Computer Engineering; Health Management and Policy; Epidemiology; Surgery; Radiation Oncology; Neurosurgery; Otolaryngology
- Record Identifier
- 9984738164902771
Metrics
16 Record Views