4.5 Article

Risk stratification model for patients with stage I invasive lung adenocarcinoma based on clinical and pathological predictors

期刊

TRANSLATIONAL LUNG CANCER RESEARCH
卷 10, 期 5, 页码 2205-+

出版社

AME PUBL CO
DOI: 10.21037/tlcr-21-393

关键词

Pathological stage I lung invasive adenocarcinoma; new pathological classification; risk stratification model; the eighth edition TNM classification

资金

  1. National Natural Science Foundation of China [81572253, 81372525]

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This study aimed to propose a new pathological classification and prognostic model for resected stage I invasive adenocarcinoma. Results showed certain subtypes in the new pathological reclassification and stage IB were independent predictors for poorer recurrence-free survival (RFS) and overall survival (OS). The risk model for RFS had an advantage in early recurrence prediction compared to TNM classification, while no significant difference was observed in long-term RFS or OS.
Background: The aim of this study was to propose a new kind of pathological classification and further establish a prognostic model for resected stage I invasive adenocarcinoma (IADC). Methods: Clinicopathological data were collected from 2 hospitals. The new proposed pathological reclassification was defined according to certain subtype instead of a predominant one. Survival curves were plotted by Kaplan-Meier analysis. Cox regressions were analyzed for recurrence-free survival (RFS) and overall survival (OS), through which prognostic scores and stratification models were established. The comparison between risk models and the eighth edition of tumor, node, metastasis (TNM) classification was conducted through receiver operating characteristic curves (ROC), as identified by the area under the curve (AUC) and z test. Results: In all, 1,196 patients were enrolled. At multivariable analysis, solid and micropapillary of the new pathological reclassification, along with stage IA3 and IB were independent predictors for poorer RFS. Stage IB and smoking status significantly indicated worse OS. After normalization and standardization of log-hazard ratio (HR), personalized scores were calculated and the risk stratifications with 3 risk groups were generated. Compared with TNM classification, the risk model of RFS showed advantage over early-recurrence prediction (1-year: 0.653 vs. 0.556, P=0.033; 3-year: 0.663 vs. 0.076, P=0.008). No marked difference was observed in long-term RFS or OS. Conclusions: Considering the harboring of certain patterns may be a new concept in adenocarcinoma classification. The risk stratification model based on this pathological classification and the eighth TNM classification showed remarkable superiority over TNM alone in predicting early recurrence of stage I adenocarcinoma. However, TNM classification remained valuable for long- term recurrence and survival prediction.

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