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

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.

Proposed novel grading system for stage I invasive lung adenocarcinoma and a comparison with the 2020 IASLC grading system

“…16,17 Consequently, the establishment of a prognostic grading system is essential in identifying patients at higher risk of recurrence, as they may benefit from adjuvant therapy. Lung adenocarcinomas are histologically heterogeneous, and traditional histological classifications are not sufficient to stratify patient prognosis despite the inclusion of numerous parameters to grading systems, such as main subtypes 5 or the secondary histological pattern, 18 nuclear grade, 19 mitotic grade, 20 presence of STAS, 6 and necrosis. 21 For example, the combined architectural/mitotic grading system established by Kadota et 6 However, Barletta et al proposed that mitosis cannot predict the outcome of lung adenocarcinoma.…”

“…This grading system provides better patient stratification in terms of DFS than the conventional subjective grading system 18 . Qiu et al established the optimized architecture‐based grading system (OAGS) based on histological morphology and the ratio of high‐grade patterns (cribriform, solid and/or micropapillary), and this model has demonstrated a robust ability to predict prognosis for resected lung adenocarcinoma (LUAD) 5 . However, the morphological heterogeneity of LUAD often results in poor interobserver agreement within different prognostic models.…”

Prognostic Implications of the Predominant Histologic Subtype in Stage I Lung Adenocarcinoma: Lack of Association with Overall Survival Based on Multi-Aspect Survival Analyses

“…20 Other publications reporting the prognostic value of histologic subtypes differed from our study in that they included adenocarcinomas of stage II or higher. 4,5,7,[9][10][11][13][14][15][16]22,23 In this study, we performed multi-aspect survival analyses. In principle, Cox proportional hazard regression analysis is based on the assumption that the event will eventually occur and the survival curve will decrease to zero.…”

“…[4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] Speci cally, adenocarcinoma of the lepidic-predominant subtype showed the most favorable outcomes, followed by the acinar/papillary and solid/micropapillary subtypes. 4,5,7,[9][10][11][13][14][15][16][17]19,20,22,23 The value of this prognostic strati cation was proven in early-stage adenocarcinoma and in advanced disease. [4][5][6][7][8][9][10][11][13][14][15][16][17][18][19][20]22,23 The staging system b...…”

“…4,5,7,[9][10][11][13][14][15][16][17]19,20,22,23 The value of this prognostic strati cation was proven in early-stage adenocarcinoma and in advanced disease. [4][5][6][7][8][9][10][11][13][14][15][16][17][18][19][20]22,23 The staging system by the American Joint Commission on Cancer (AJCC) is the cornerstone for predicting the prognosis of patients with lung cancer. 24 The eighth-edition staging system adopted the solid portion size on CT and the invasive component size on microscopy to determine the clinical and pathologic T category, respectively.…”