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


Aims Considering 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.

Methods A 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.

Results The 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.

Conclusions The OAGS is an independent prognostic factor and shows a robust ability to predict prognosis for resected LUAD.

  • lung neoplasms
  • pathology department
  • hospital
  • biomarkers
  • tumour
  • diagnosis

Data availability statement

Data are available through contacting the corresponding author.

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