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

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Title: Risk stratification model for patients with stage I invasive lung adenocarcinoma based on clinical and pathological predictors
Authors: Wang, Yiyang Browse this author
Zheng, Difan Browse this author
Luo, Jizhuang Browse this author
Zhang, Jie Browse this author
Pompili, Cecilia Browse this author
Ujiie, Hideki Browse this author
Matsuura, Natsumi Browse this author
Chen, Haiquan Browse this author
Yao, Feng Browse this author
Keywords: Pathological stage I lung invasive adenocarcinoma
new pathological classification
risk stratification model
the eighth edition TNM classification
Issue Date: May-2021
Publisher: AME Publishing Company
Journal Title: Translational Lung Cancer Research
Volume: 10
Issue: 5
Start Page: 2205
End Page: 2217
Publisher DOI: 10.21037/tlcr-21-393
Abstract: 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.
Type: article
Appears in Collections:北海道大学病院 (Hokkaido University Hospital) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 氏家 秀樹

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