Literature DB >> 33905897

Validation Study of the International Association for the Study of Lung Cancer Histologic Grading System of Invasive Lung Adenocarcinoma.

Mariyo Rokutan-Kurata1, Akihiko Yoshizawa2, Kentaro Ueno3, Naoki Nakajima1, Kazuhiro Terada1, Masatsugu Hamaji4, Makoto Sonobe5, Toshi Menju4, Hiroshi Date4, Satoshi Morita3, Hironori Haga1.   

Abstract

INTRODUCTION: A histologic grading system for invasive lung adenocarcinoma (ADC) has been proposed by the International Association for the Study of Lung Cancer (IASLC) Pathology Committee in June 2020. This study evaluated the prognostic value of the IASLC histologic grading system (the IASLC system) in a large Japanese cohort.
METHODS: We performed comprehensive histologic subtyping using the semiquantitative estimation of five major patterns and complex glandular patterns in patients with a completely resected lung ADC and determined the histologic grade using the IASLC system. Concordance index and receiver-operating characteristic curves were used to evaluate the clinical utility of the IASLC system for recurrence and death; the comparison was performed with the architectural-pattern system (the Arch system) and the grading system on the basis of the two most predominant patterns (the Sica's system).
RESULTS: Of 1002 patients with invasive ADC, 235 had recurrent disease and 166 died of lung cancer. The concordance index and area under the curve of the IASLC system were 0.777 and 0.807 for recurrence and 0.767 and 0.776 for death, respectively. These were similar to those of the Arch system (0.763 and 0.796 for recurrence, 0.743 and 0.755 for death) and the Sica's system (0.786 and 0.814 for recurrence, 0.762 and 0.773 for death).
CONCLUSIONS: We reported that the IASLC system for invasive lung ADC has prognostic significance by evaluating a large Japanese cohort. We believe that the IASLC grading system will provide physicians with better information for postsurgery treatment.
Copyright © 2021 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Area under the curve (AUC); Concordance index (C-index); Histological grading system; Invasive lung adenocarcinoma; Predictive model

Year:  2021        PMID: 33905897     DOI: 10.1016/j.jtho.2021.04.008

Source DB:  PubMed          Journal:  J Thorac Oncol        ISSN: 1556-0864            Impact factor:   15.609


  3 in total

1.  Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study.

Authors:  Likun Hou; Tingting Wang; Donglai Chen; Chunyan Wu; Chang Chen; Yunlang She; Jiajun Deng; Minglei Yang; Yu Zhang; Mengmeng Zhao; Yifan Zhong; Minjie Ma; Guofang Zhao; Yongbing Chen; Dong Xie; Yuming Zhu; Qiankun Chen
Journal:  Mod Pathol       Date:  2022-01-10       Impact factor: 7.842

2.  Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification.

Authors:  Huan Lin; Xipeng Pan; Zhengyun Feng; Lixu Yan; Junjie Hua; Yanting Liang; Chu Han; Zeyan Xu; Yumeng Wang; Lin Wu; Yanfen Cui; Xiaomei Huang; Zhenwei Shi; Xin Chen; Xiaobo Chen; Qingling Zhang; Changhong Liang; Ke Zhao; Zhenhui Li; Zaiyi Liu
Journal:  J Transl Med       Date:  2022-06-07       Impact factor: 8.440

3.  Comprehensive analysis of mutational profile and prognostic significance of complex glandular pattern in lung adenocarcinoma.

Authors:  Jinsong Bai; Chaoqiang Deng; Qiang Zheng; Di Li; Fangqiu Fu; Yuan Li; Yang Zhang; Haiquan Chen
Journal:  Transl Lung Cancer Res       Date:  2022-07
  3 in total

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