Optimised architecture-based grading system as an independent prognostic factor in resected lung adenocarcinoma

Author:

Qiu Jin huan,Hu Gui ming,Zhang Rui zhen,Hu Menglong,Li Zongkuo,Zhang Yan,Wu Hui fang,Fu Wen jing,Zhang Min,Feng Yi kun,Niu Lihua,Ren Jing liORCID

Abstract

AimsConsidering morphological heterogeneity of lung adenocarcinoma (LUAD) and no objective prognostic grading system existing currently, we aim to establish an ‘optimised architecture-based grading system’ (OAGS) to predict prognosis for resected LUAD.MethodsA multicentral study involving three independent cohorts of LUAD was conducted. Predictive ability of the OAGS for recurrence-free probability (RFP) and overall survival (OS) was assessed in training cohort (n=228) by the area under the receiver operating characteristic curve (AUC), Harrell’s concordance index (C-index) and Kaplan-Meier survival analyses, which was validated in testing (n=135) and validation (n=226) cohorts.ResultsThe OAGS consists of: grade 1 for lepidic, papillary or acinar predominant tumour with no or less than 5% of high-grade patterns (cribriform, solid and or micropapillary), grade 2 for lepidic, papillary or acinar predominant tumour with 5% or more of high-grade patterns, and grade 3 for cribriform, solid or micropapillary predominant tumour. In all stages, the OAGS outperformed the pattern-dominant grading system and IASLC grading system for predicting RFP (C-index, 0.649; AUC, 0.742) and OS (C-index, 0.685; AUC, 0.754). Multivariate analysis identified it as an independent predictor of both (RFP, p<0.001; OS, p<0.001). Furthermore, in pT1-2aN0M0 subgroup, the OAGS maintained its ability to predict recurrence (C-index, 0.699; AUC, 0.769) and stratified patients into different risk groups of RFP (p<0.001). These results were confirmed in testing and validation cohorts.ConclusionsThe OAGS is an independent prognostic factor and shows a robust ability to predict prognosis for resected LUAD.

Funder

the Key Scientific Research Project Plans of Higher Education Institutions in Henan Province

the Joint Construction Project of Henan Medical Science and Technology Project

Publisher

BMJ

Subject

General Medicine,Pathology and Forensic Medicine

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