Validation Study of New IASLC Histology Grading System in Stage I Non-Mucinous Adenocarcinoma Comparing With Minimally Invasive Adenocarcinoma

Prognostic impact of the IASLC grading system of lung adenocarcinoma: a systematic review and meta-analysis

AIMS

Tumour grading is an essential part of the pathologic assessment that promotes patient management. The International Association for the Study of Lung Cancer (IASLC) proposed a grading system for non-mucinous lung adenocarcinoma in 2020. We aimed to validate the prognostic impact of this novel grading system on overall survival (OS) and recurrence-free survival (RFS) based on literature data.

METHODS AND RESULTS

The review protocol was registered in PROSPERO (CRD42023396059). We aimed to identify randomized or non-randomized controlled trials published after 2020 comparing different IASLC grade categories in Medline, Embase, and CENTRAL. Hazard ratios (HRs) with 95% confidence intervals (CIs) of OS and RFS were pooled and the Quality In Prognosis Studies (QUIPS) tool was used to assess the risk of bias in the included studies. Ten articles were eligible for this review. Regarding OS estimates, grade 1 lung adenocarcinomas were better than grade 3 both in univariate and multivariate analyses (HROSuni = 0.19, 95% CI: 0.05-0.66, p = 0.009; HROSmulti = 0.21, 95% CI: 0.12-0.38, p < 0.001). Regarding RFS estimates, grade 3 adenocarcinomas had a worse prognosis than grade 1 in multivariate analysis (HRRFSmulti: 0.22, 95% CI: 0.14-0.35, p < 0.001).

CONCLUSION

The literature data and the result of our meta-analysis demonstrate the prognostic relevance of the IASLC grading system. This supports the inclusion of this prognostic parameter in daily routine worldwide.

Invasion and Grading of Pulmonary Non-Mucinous Adenocarcinoma

Lung adenocarcinoma staging and grading were recently updated to reflect the link between histologic growth patterns and outcomes. The lepidic growth pattern is regarded as "in-situ," whereas all other patterns are regarded as invasive, though with stratification. Solid, micropapillary, and complex glandular patterns are associated with worse prognosis than papillary and acinar patterns. These recent changes have improved prognostic stratification. However, multiple pitfalls exist in measuring invasive size and in classifying lung adenocarcinoma growth patterns. Awareness of these limitations and recommended practices will help the pathology community achieve consistent prognostic performance and potentially contribute to improved patient management.

High-risk features associated with recurrence in stage I lung adenocarcinoma

OBJECTIVE

There is a lack of knowledge regarding the use of prognostic features in stage I lung adenocarcinoma (LUAD). Thus, we investigated clinicopathologic features associated with recurrence after complete resection for stage I LUAD.

METHODS

We performed a retrospective analysis of patients with pathologic stage I LUAD who underwent R0 resection from 2010 to 2020. Exclusion criteria included history of lung cancer, induction or adjuvant therapy, noninvasive or mucinous LUAD, and death within 90 days of surgery. Fine and Gray competing-risk regression assessed associations between clinicopathologic features and disease recurrence.

RESULTS

In total, 1912 patients met inclusion criteria. Most patients (1565 [82%]) had stage IA LUAD, and 250 developed recurrence: 141 (56%) distant and 109 (44%) locoregional only. The 5-year cumulative incidence of recurrence was 12% (95% CI, 11%-14%). Higher maximum standardized uptake value of the primary tumor (hazard ratio [HR], 1.04), sublobar resection (HR, 2.04), higher International Association for the Study of Lung Cancer grade (HR, 5.32 [grade 2]; HR, 7.93 [grade 3]), lymphovascular invasion (HR, 1.70), visceral pleural invasion (HR, 1.54), and tumor size (HR, 1.30) were independently associated with a hazard of recurrence. Tumors with 3 to 4 high-risk features had a higher cumulative incidence of recurrence at 5 years than tumors without these features (30% vs 4%; P < .001).

CONCLUSIONS

Recurrence after resection for stage I LUAD remains an issue for select patients. Commonly reported clinicopathologic features can be used to define patients at high risk of recurrence and should be considered when assessing the prognosis of patients with stage I disease.

18 F-FDG PET/CT characteristics of IASLC grade 3 invasive adenocarcinoma and the value of 18 F-FDG PET/CT for preoperative prediction: a new prognostication model

OBJECTIVE

This study is performed to investigate the imaging characteristics of the International Association for the Study of Lung Cancer grade 3 invasive adenocarcinoma (IAC) on PET/CT and the value of PET/CT for preoperative predicting this tumor.

MATERIALS AND METHODS

We retrospectively enrolled patients with IAC from August 2015 to September 2022. The clinical characteristics, serum tumor markers, and PET/CT features were analyzed. T test, Mann-Whitney U test, χ 2 test, Logistic regression analysis, and receiver operating characteristic analysis were used to predict grade 3 tumor and evaluate the prediction effectiveness.

RESULTS

Grade 3 tumors had a significantly higher maximum standardized uptake value (SUV max ) and consolidation-tumor-ratio (CTR) ( P  < 0.001), while Grade 1 - 2 tumors were prone to present with air bronchogram sign or vacuole sign ( P  < 0.001). A stepwise logistic regression analysis revealed that smoking history, CEA, SUV max , air bronchogram sign or vacuole sign and CTR were useful predictors for Grade 3 tumors. The established prediction model based on the above 5 parameters generated a high AUC (0.869) and negative predictive value (0.919), respectively.

CONCLUSION

Our study demonstrates that grade 3 IAC has a unique PET/CT imaging feature. The prognostication model established with smoking history, CEA, SUV max , air bronchogram sign or vacuole sign and CTR can effectively predict grade 3 tumors before the operation.

Updates on lung adenocarcinoma: invasive size, grading and STAS

Advancements in the classification of lung adenocarcinoma have resulted in significant changes in pathological reporting. The eighth edition of the tumour-node-metastasis (TNM) staging guidelines calls for the use of invasive size in staging in place of total tumour size. This shift improves prognostic stratification and requires a more nuanced approach to tumour measurements in challenging situations. Similarly, the adoption of new grading criteria based on the predominant and highest-grade pattern proposed by the International Association for the Study of Lung Cancer (IASLC) shows improved prognostication, and therefore clinical utility, relative to previous grading systems. Spread through airspaces (STAS) is a form of tumour invasion involving tumour cells spreading through the airspaces, which has been highly researched in recent years. This review discusses updates in pathological T staging, adenocarcinoma grading and STAS and illustrates the utility and limitations of current concepts in lung adenocarcinoma.

Micropapillary and solid components as high-grade patterns in IASLC grading system of lung adenocarcinoma: Clinical implications and management

OBJECTIVES

The grading system proposed by the International Association for the Study of Lung Cancer is based on a combination of predominant histologic subtypes and the proportion of high-grade components with a cutoff of 20%. We aimed to examine the clinical implications of the grading system beyond the discrimination of patient prognosis, while assessing the biological differences among high-grade subtypes.

METHODS

We retrospectively reviewed 648 consecutive patients with resected lung adenocarcinomas and examined their clinicopathologic, genotypic, and immunophenotypic features and treatment outcomes. Besides the differences among grades, the clinical impact of different high-grade components: micropapillary (MIP) and solid (SOL) patterns, was individually evaluated.

RESULTS

Survival outcomes were well-stratified according to the grading system. Grade 3 tumors exhibited aggressive clinicopathologic features, while being an independent prognostic factor in multivariable analysis. A small proportion (<20 %) of high-grade components in grade 2 had a negative prognostic impact. The prognostic difference bordering on the 20 % cutoff of the MIP proportion was validated; however, the proportion of SOL component did not affect prognosis. A survival benefit from adjuvant chemotherapy was observed in grade 3 tumors regardless of histologic subtype, but not in grade 1-2 tumors. The molecular and immunophenotypic features were different among grades, but still heterogeneous in grade 3, with MIP harboring frequent EGFR mutation and SOL exhibiting high PD-L1 expression. The treatment outcome after recurrence was worse in grade 3, but tumors with MIP pattern had an equivalent prognosis to that of grade 1-2 tumors, reflecting the high frequency of molecular targeted therapy.

CONCLUSIONS

In addition to stratifying patient prognosis, the current grading system could discriminate clinical course, therapeutic effects of adjuvant chemotherapy, and molecular and immunophenotypic features. Further stratification based on biological heterogeneity in grade 3 remains necessary to enhance the role of the grading system in guiding patient management.

Clinical implication of the 2020 International Association for the Study of Lung Cancer histologic grading in surgically resected pathologic stage 1 lung adenocarcinomas: Prognostic value and association with computed tomography characteristics

OBJECTIVES

To investigate the incremental prognostic value of the 2020 International Association for the Study of Lung Cancer (IASLC) histologic grading system over traditional prognosticators in surgically resected pathologic stage 1 lung adenocarcinomas and to identify the clinical and radiologic characteristics of lung adenocarcinomas reclassified by the 2020 histologic grading system.

MATERIALS AND METHODS

We retrospectively enrolled 356 patients who underwent surgery for pathologic stage 1 adenocarcinoma between January 2016 and December 2017. The histologic grading was classified according to the predominant histologic subtype (conventional system) and the updated 2020 IASLC grading system. The clinical and computed tomography (CT) characteristics were compared according to the reclassification of the updated system. The performance of prognostic models for recurrence-free survival based on the combination of pathologic tumor size, histologic grade, and CT-based information was compared using the c-index.

RESULTS

Postoperative recurrence occurred in 6.7% of patients during the follow-up period (mean, 1589.2 ± 406.7 days). Fifty-nine of 244 (24.2%) tumors with intermediate grades in the conventional system were reclassified as grade 3 with the updated grading system. They showed significantly larger solid proportions and higher percentages of pure solid nodules on CT compared to tumors without reclassification (n = 185) (P < 0.05). Prognostic prediction models based on pathology tumor size and histologic grades had significantly higher c-indices (0.754-0.803) compared to the model based on pathologic tumor size only (c-index:0.723, P < 0.05).

CONCLUSION

The 2020 IASLC histologic grading system has significant incremental prognostic value over the pathologic stage in surgically resected pathologic stage 1 lung adenocarcinoma. Reclassified lung adenocarcinomas using the updated grading system have a larger solid proportion and a higher percentage of pure solid nodules on CT.

Predictive scoring of high-grade histology among early-stage lung cancer patients: The MOSS score

BACKGROUND

Poor prognosis associated with adenocarcinoma of International Association for the Study of Lung Cancer (IASLC) grade 3 has been recognized. In this study we aimed to develop a scoring system for predicting IASLC grade 3 based before surgery.

METHODS

Two retrospective datasets with significant heterogeneity were used to develop and evaluate a scoring system. The development set was comprised of patients with pathological stage I nonmucinous adenocarcinoma and they were randomly divided into training (n = 375) and validation (n = 125) datasets. Using multivariate logistic regression, a scoring system was developed and internally validated. Later, this new score was further tested in the testing set which was comprised of patients with clinical stage 0-I non-small cell lung cancer (NSCLC) (n = 281).

RESULTS

Four factors that were related to IASLC grade 3 were used to develop the new scoring system the MOSS score; male (M, point 1), overweight (O, point 1), size>10 mm (S, point 1), and solid lesions (S, point 3). Predictability of IASLC grade 3 increased from 0.4% to 75.2% with scores from 0 to 6. The area under the curve (AUC) of the MOSS was 0.889 and 0.765 for the training and validation datasets, respectively. The MOSS score exhibited similar predictability in the testing set (AUC: 0.820).

CONCLUSION

The MOSS score, which combines preoperative variables, can be used to identify high-risk early-stage NSCLC patients with aggressive histological features. It can support clinicians in determining a treatment plan and surgical extent. Further refinement of this scoring system with prospective validation is needed.