Clinical characteristics and survival in early-onset lung cancer: a multicenter cohort study.

Authors

Hongliang Liu, Bibo Li, Zhikai Yu, Jia Du, Xiu Liu, Yan Zhang, Qing Guo, Lihong Mu, Mei He

Published in

Frontiers in oncology. Volume 16. Pages 1906257. Epub Aug 12, 2026.

Abstract

The characteristics of early-onset lung cancer (EOLC) have not been extensively studied. Our research aimed to comprehensively assess the clinicopathological, genetic features and prognosis of EOLC.
In this retrospective study of lung cancer patients diagnosed at 26 Chongqing hospitals between January 2019 and December 2022 (18-74 years), we stratified them into early-onset lung cancer (<50 years) and late-onset lung cancer (≥50 years) groups. Furthermore, we used propensity score matching to balance baseline characteristics, compare overall survival and lung cancer-specific survival between early-onset lung cancer (EOLC) and late-onset lung cancer (LOLC) groups, and perform subgroup comparisons.
A total of 6,883 lung cancer patients were included in the final analysis, comprising 690 patients with EOLC and 6,193 patients with LOLC. Compared with the LOLC group, the EOLC group had more females and never-smokers. In clinical features, EOLC patients predominantly had adenocarcinoma (69.7% vs. 52.2%), more often presented with stage IV disease (49.3% vs. 44.0%), and had higher rates of bone (22.8% vs. 16.9%) and brain metastases (18.4% vs. 10.8%), yet were more likely to undergo surgery (31.0% vs. 22.4%). Significant differences in mutation rates were observed for HER2 (10.1% vs. 1.6%). After propensity score matching, late-onset was identified as an independent risk factor for adverse survival outcomes, the median overall survival was 42.7 months for EOLC versus 32.9 months for LOLC, with 1-, 3-, and 5-year survival rates of 78.0%, 54.4%, and 42.2% in the EOLC group, compared with 75.5%, 47.8%, and 35.4% in the LOLC group.
Despite more aggressive clinicopathological features, EOLC was associated with better survival outcomes. Moreover, distinct driver gene alteration profiles highlight the need to identify targetable alterations and implement targeted therapy in this enriched population.

PMID:
42656213
Bibliographic data and abstract were imported from PubMed on 27 Aug 2026.

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