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Developing and validating an integrated gross tumor volume (GTV)-TNM stratification system for supplementing unresectable locally advanced non-small cell lung cancer treated with concurrent chemoradiotherapy

Authors :
Bo Qiu
Zhangkai J. Cheng
Qiwen Li
Yin Zhou
Bin Wang
DaQuan Wang
Zhouguang Hui
FangJie Liu
Jibin Li
SuPing Guo
Haoqiang He
Xiaoyan Huang
JinYu Guo
Yi-Ming Wang
Xin-Lei Ai
Hui Liu
Nan Hu
Zhengfei Zhu
NaiBin Chen
C. Xie
Source :
Radiation Oncology (London, England), Radiation Oncology, Vol 15, Iss 1, Pp 1-12 (2020)
Publication Year :
2020
Publisher :
BioMed Central, 2020.

Abstract

Purpose The gross tumor volume (GTV) could be an independent prognostic factor for unresectable locally advanced non-small cell lung cancer (LANSCLC). We aimed to develop and validate a novel integrated GTV-TNM stratification system to supplement LANSCLC sub-staging in patients treated with concurrent chemoradiotherapy (CCRT). Methods We performed a retrospective review of 340 patients with unresectable LANSCLC receiving definitive CCRT. All included patients were divided into two randomized cohorts. Then the Kaplan–Meier method and Cox regression were calculated to access the prognostic value of the integrated GTV-TNM stratification system, which was further validated by the area under the receiver operating characteristic curve (AUC) score and F1-score. Results The optimal outcome-based GTV cut-off values (70 and 180 cm3) of the modeling cohort were used to determine each patient’s integrated GTV-TNM stratum in the whole cohort. Our results indicated that a lower integrated GTV-TNM stratum could had better overall survival and progression-free survival (all P P = 0.027) and F1-score (0.655 vs. 0.615, P Conclusions We proposed a novel integrated GTV-TNM stratification system to supplement unresectable LANSCLC sub-staging due to its prognostic value independent of TNM stage and other clinical characteristics, suggesting that it could be considered in individual treatment decision-making process.

Details

Language :
English
ISSN :
1748717X
Volume :
15
Database :
OpenAIRE
Journal :
Radiation Oncology (London, England)
Accession number :
edsair.doi.dedup.....a6aa3f1b3fff01474812671e38548094