Evaluating Clinical Outcomes Across Sex and Ethnicity in Patients With Early-Stage Non-small Cell Lung Cancer (NSCLC).

Publication/Presentation Date

10-1-2025

Abstract

BACKGROUND: Although there are well-studied sex and racial/ethnic disparities within lung cancer patients, they do not examine the interface of these inequities. We aim to utilize a national database to evaluate clinical outcomes and disparities within racial/ethnic groups of female patients with early-stage lung cancer.

METHODS: The 2020 National Cancer Database (NCDB) was queried for patients with clinical stage I non-small cell lung cancer (NSCLC) with known vital status between 2010 and 2019. Patients with carcinoid tumors were excluded. Demographic data, clinicopathologic variables, 30-d, 90-d, 5-y mortality, and 5-y overall survival were analyzed.

RESULTS: A total of 344,223 patients met the inclusion criteria, of which 187,588 were female (54.4%). Within ethnic subgroups, 5-y survival was highest among Asian/Pacific Islander women (API) (77.8%) (P < 0.001). API women had the highest rates of surgical resection (75.7%), with higher rates of nodes examined (73.1%) and nodal upstaging (13.4%) (P < 0.001). Black and White women had the lowest rates of 5-y survival (60%, 58.8%) and surgical resection (59.1%, 62.2%) (P < 0.001). API women had the least comorbidities (CCI = 0, 71.1%; P < 0.001) and highest rates of well-differentiated tumors (28.7%, P < 0.001).

CONCLUSIONS: API women had the highest survival rates, highest rates of surgical resection with nodal sampling, and low-grade tumors. Black and White women had the lowest rates of overall survival and surgical resection. This disparity in guideline-concordant surgery highlights the importance of acknowledging the racial/ethnic heterogeneity among women with early-stage NSCLC and that female lung cancer patients should not be treated as a monolith.

Volume

314

First Page

59

Last Page

70

ISSN

1095-8673

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

40716200

Department(s)

Administration and Leadership

Document Type

Article

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