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Lepidic-Type Lung Adenocarcinomas: Is It Safe to Observe for Growth Prior to Treating?

医学 内科学 危险系数 淋巴结 比例危险模型 单变量分析 阶段(地层学) 肿瘤科 逻辑回归 肺癌 腺癌 胃肠病学 癌症 多元分析 置信区间 生物 古生物学
作者
Lye-Yeng Wong,Irmina A. Elliott,Douglas Z. Liou,Leah M. Backhus,Natalie S. Lui,Joseph B. Shrager,Mark F. Berry
出处
期刊:The Annals of Thoracic Surgery [Elsevier]
标识
DOI:10.1016/j.athoracsur.2024.03.003
摘要

Abstract

Background

Lepidic-type adenocarcinomas (LPA) can be multi-focal, and treatment is often deferred until there is observed growth. This study investigated the potential downside of that strategy by evaluating the relationship of nodal involvement with tumor size and survival.

Methods

The impact of tumor size on lymph node involvement and survival was evaluated for National Cancer Database patients who received surgery without induction therapy as primary treatment for cT1-3N0M0 histologically confirmed LPA from 2006-2019 using logistic regression, Kaplan-Meier, and Cox analyses.

Results

Positive nodes occurred in 442 (5.3%) of 8,286 patients. The incidence of having positive nodes approximately doubled with each 1cm increment increase in size. Patients with positive nodes were more likely to have larger tumors (27mm vs 20mm,p<0.001) and clinical T2+ disease (40.7% vs 26.8%,p<0.001) compared to node-negative patients, but tumor size was the only significant independent predictor of having positive nodal disease in logistic regression analysis; this association grew stronger with each incremental centimeter increase in size. Patients with positive nodes were more likely to undergo adjuvant radiation (23.5% vs 1.1%,p<0.001) and chemotherapy (72.9% vs 7.9%,p<0.001), and expectedly had worse survival compared to the node negative group in univariate (5-year overall survival 50.9% vs 81.1%,p<0.001) and multivariable (Hazard ratio 2.56 [95% CI 2.14-3.05],p<0.001) analyses.

Conclusions

Nodal involvement is relatively uncommon in early-stage LPAs but steadily increases with tumor size and is associated with dramatically worse survival. This data can be used to inform treatment decisions when evaluating LPA patients.
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