Reconsidering the American Joint Committee on Cancer Eighth Edition TNM Staging Manual Classifications for T2b and T3 NSCLC

Pathological T3 Non-Small Cell Lung Cancer with satellite nodules: Number or size, what does matter?

BACKGROUND

Non-small Cell Lung Cancer (NSCLC) with intralobar satellite nodule are defined as T3 (T3SN). We investigated the main features of these tumors and analyzed their impact on Overall Survival (OS).

METHODS

This was a retrospective multicentric study including all pT3SN NSCLC operated on between 2005 and 2020, excluding patients with multifocal ground-glass opacities; who received induction therapies; N3 or stage IV. The diameter of largest (LgN) and smallest nodule (SmN), the total diameter (sum of diameter of all nodules, TS), and the number of SN were measured.

RESULTS

Among 102 patients, 64.7 % were male. 84.3 % of patients had one SN (84.3 %), 9.8 % two SN while 5.9 % more than 2 SN. 63 patients were pN0. LgN (p = 0.001), SN (p = 0.005) and TS (p = 0.014) were significantly related to lymph-node metastasis; the LgN and TS were related to visceral pleural invasion (p < 0.001). Five-year OS was 65.1 %; at univariable analysis more than 2 satellite nodules, LgN and TS were significantly related to worse OS; at multivariable analysis, TS (Hazard Ratio [HR] 1.116 95 % Confidence Interval [CI] 1.008-1.235, p = 0.034) was an independent prognostic factors for OS. No significant prognostic factors were found for DFS at multivariable analysis. In pN0 patients, LgN (HR 1.051, 95 % CI 1.066-1.099, p = 0.027) and non-adenocarcinoma (HR 5.315 CI 95 % 1.494-18.910, p = 0.010) influenced OS.

CONCLUSIONS

Tumor size is related to tumor's local invasiveness. TS is an independent prognostic factor for OS. Patients with more than 2 SN seem to be at higher risk for death and recurrence.

Predictive value of CT and 18F-FDG PET/CT features on spread through air space in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma, a leading cause of cancer-related mortality, demands precise prognostic indicators for effective management. The presence of spread through air space (STAS) indicates adverse tumor behavior. However, comparative differences between 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography(PET)/computed tomography(CT) and CT in predicting STAS in lung adenocarcinoma remain inadequately explored. This retrospective study analyzes preoperative CT and 18F-FDG PET/CT features to predict STAS, aiming to identify key predictive factors and enhance clinical decision-making.

METHODS

Between February 2022 and April 2023, 100 patients (108 lesions) who underwent surgery for clinical lung adenocarcinoma were enrolled. All these patients underwent 18F-FDG PET/CT, thin-section chest CT scan, and pathological biopsy. Univariate and multivariate logistic regression was used to analyze CT and 18F-FDG PET/CT image characteristics. Receiver operating characteristic curve analysis was performed to identify a cut-off value.

RESULTS

Sixty lesions were positive for STAS, and 48 lesions were negative for STAS. The STAS-positive was frequently observed in acinar predominant. However, STAS-negative was frequently observed in minimally invasive adenocarcinoma. Univariable analysis results revealed that CT features (including nodule type, maximum tumor diameter, maximum solid component diameter, consolidation tumor ratio, pleural indentation, lobulation, spiculation) and all 18F-FDG PET/CT characteristics were statistically significant difference in STAS-positive and STAS-negative lesions. And multivariate logistic regression results showed that the maximum tumor diameter and SUVmax were the independent influencing factors of CT and 18F-FDG PET/CT in STAS, respectively. The area under the curve of maximum tumor diameter and SUVmax was 0.68 vs. 0.82. The cut-off value for maximum tumor diameter and SUVmax was 2.35 vs. 5.05 with a sensitivity of 50.0% vs. 68.3% and specificity of 81.2% vs. 87.5%, which showed that SUVmax was superior to the maximum tumor diameter.

CONCLUSION

The radiological features of SUVmax is the best model for predicting STAS in lung adenocarcinoma. These radiological features could predict STAS with excellent specificity but inferior sensitivity.

Long-Term Survival of American Joint Committee on Cancer 8th Edition Staging Descriptors for Clinical M1a Non-Small Cell Lung Cancer

BACKGROUND

The American Joint Committee on Cancer (AJCC) 8th edition TNM staging manual for non-small cell lung cancer (NSCLC) M1a descriptors includes tumors presenting with malignant pleural or pericardial effusion (ie, M1a-Effusion), pleural or pericardial nodule(s) (ie, M1a-Pleural), or separate tumor nodule(s) in a contralateral lobe (ie, M1a-Contralateral).

RESEARCH QUESTION

Is M1a NSCLC presenting with malignant pleural or pericardial effusion associated with worse survival compared with other types of M1a NSCLC?

STUDY DESIGN AND METHODS

Patients with cT1-4, N0-3, M1a NSCLC (satisfying a single M1a descriptor of M1a-Effusion, M1a-Pleural, or M1a-Contralateral), according to AJCC eighth edition staging criteria, in the National Cancer Database from 2010 to 2015 were included. Overall survival was evaluated by using Kaplan-Meier analysis, multivariable-adjusted Cox proportional hazards modeling, and propensity score matching.

RESULTS

Of the 25,716 patients who met study eligibility criteria, 12,756 (49.6%) presented with M1a-Effusion tumors, 3,589 (14.0%) with M1a-Pleural tumors, and 9,371 (36.4%) with M1a-Contralateral tumors. In multivariable-adjusted analysis, compared to M1a-Effusion tumors, both M1a-Pleural tumors (hazard ratio, 0.68; 95% CI, 0.64-0.71; P < .001) and M1a-Contralateral tumors (hazard ratio, 0.66; 95% CI, 0.64-0.69; P < .001) were associated with better overall survival. No significant differences were found in overall survival between patients with M1a-Pleural tumors vs M1a-Contralateral tumors. In a propensity score-matched analysis of 5,581 patients with M1a-Effusion tumors and 5,581 patients with other M1a tumors (ie, M1a-Contralateral or M1a-Effusion), those with M1a-Effusion tumors had worse 5-year overall survival than patients with other M1a tumors (M1a-Effusion 6.4% [95% CI, 5.7-7.1] vs M1a-Other 10.6% [95% CI, 9.7-11.5]; P < .001).

INTERPRETATION

In this national analysis of AJCC 8th edition cT1-4, N0-3, M1a NSCLC, tumors with malignant pleural or pericardial effusion were associated with worse overall survival than tumors with either pleural or contralateral pulmonary nodules. These findings may be taken into consideration for the upcoming ninth edition of the AJCC lung cancer staging guidelines.

Completeness of Resection and Long-Term Survival of Patients Undergoing Resection for Pathologic T3 NSCLC: An International Association for the Study of Lung Cancer Analysis

INTRODUCTION

Currently, tumors with different histopathologic characteristics and oncologic outcomes comprise the T3 category of the eight edition TNM classification for lung cancers. To better understand the T3 category, we evaluated completeness of resection and long-term survival in patients undergoing resection for T3 NSCLC.

METHODS

The International Association for the Study of Lung Cancer 1999 to 2010 database was queried for patients with pathologic T3N0M0 NSCLC who underwent lobectomy or pneumonectomy. The primary outcome evaluated was overall survival (OS) stratified by T3 descriptors and completeness of resection.

RESULTS

Of 1448 patients with T3N0M0 tumors, 1187 (82.0%) had a single descriptor defining them as T3. T3 tumors with chest wall infiltration (CWI) or parietal pleura infiltration (PL3) had the highest rates of incomplete resection (9.8% and 8.4%, respectively), and those classified as T3 by size only had the lowest rate of incomplete resection (2.9%). Individual T3 descriptors were associated with significant differences in OS (p = 0.005). When tumors with similar survival and complete resection rates were grouped, patients with T3 tumors characterized by size or the presence of a separate nodule (SN) in the same lobe had better 5-year OS than patients with tumors characterized by PL3 or CWI (size/SN 60% versus CWI/PL3 53%, p = 0.017) independent of completeness of resection.

CONCLUSIONS

Significant differences in 5-year OS were associated with size, SN, PL3, or CWI T3 descriptors. Subdividing pathologic T3N0M0 tumors according to the presence or absence of CWI or PL3 may increase the prognostic accuracy of tumor staging.

Prognostic factors and survival prediction of resected non-small cell lung cancer with ipsilateral pulmonary metastases: a study based on the Surveillance, Epidemiology, and End Results (SEER) database

BACKGROUND

Prognostic factors and survival outcomes of non-small cell lung cancer (NSCLC) with Ipsilateral pulmonary metastasis (IPM) are not well-defined. Thus, this study intended to identify the prognostic factors for these patients and construct a predictive nomogram model.

METHODS

One thousand, seven hundred thirty-two patients with IPM identified between 2000 to 2019 were from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified using multivariate Cox regression analyses. Nomograms were constructed to predict the overall survival (OS), C-index, the area under the curve (AUC), and the calibration curve to determine the predictive accuracy and discrimination; the decision curve analysis was used to confirm the clinical utility.

RESULTS

Patients were randomly divided into training (n = 1213) and validation (n = 519) cohorts. In the training cohort, the multivariable analysis demonstrated that age, sex, primary tumor size, N status, number of regional lymph nodes removed, tumor grade, and chemotherapy were independent prognostic factors for IPM. We constructed a 1-year, 3-year, and 5-year OS prediction nomogram model using independent prognostic factors. The C-index of this model for OS prediction was 0.714 (95% confidence interval [CI], 0.692 to 0.773) in the training cohort and 0.695 (95% CI, 0.660 to 0.730) in the validation cohort. Based on the AUC of the receiver operating characteristic analysis, calibration plots, and decision curve analysis, we concluded that the prognosis model of IPM exhibited excellent performance. Patients with total nomogram points greater than 96 were considered high-risk.

CONCLUSION

We constructed and internally validated a nomogram to predict 1-year, 3-year, and 5-year OS for NSCLC patients with IPM according to independent prognostic factors. This nomogram demonstrated good calibration, discrimination, clinical utility, and practical decision-making effects for the prognosis of NSCLC patients with IPM.

Reconsidering the T category for the T3 non-small cell lung cancer with additional tumor nodules in the same lobe: A population-based study

Background

This study aimed to evaluate the prognosis of the T3 non-small cell lung cancer (NSCLC) patients with additional tumor nodules in the same lobe (T3-Add), and externally validate the current T category of this population.

Methods

NSCLC data deposited in the Surveillance, Epidemiology, and End Results (SEER) dataset was extracted. Survivals were estimated using the Kaplan-Meier method with a log-rank test. Propensity score matching (PSM) was performed to reduce bias. The least absolute shrinkage and selection operator (LASSO)-penalized Cox model was used to determine the prognostic factors.

Results

A total of 41,370 eligible cases were included. There were 2,312, 20,632, 12,787, 3,374 and 2,265 cases in the T3-Add, T1, T2, T3 and T4 group, respectively. The Kaplan-Meier curves demonstrated that the survivals of the T3-Add patients were superior to those of the T3 patients both before and after PSM. Additionally, the OS of the T3-Add patients were worse than that of the T2 patients, but the CSS differences between these two groups were not statistically significant. In the subset analyses, the survivals of the T3-Add patients were inferior to those of the T2a patients, but were comparable to those of the T2b patients (5-year OS rate: 54.3% vs. 57.2%, P = 0.884; 5-year CSS rate: 76.2% vs. 76.8%, P = 0.370). In the T3-Add &amp; T2b matched pair, multivariable Cox analysis further confirmed that T category was not a prognostic factor for survivals.

Conclusion

T3-Add and T2b NSCLC patients had similar survivals, and we proposed that it is necessary to reconsider the T category of the patients with additional nodules in the same lobe in the forthcoming 9th edition of TNM staging manual.

Reconsidering T component of cancer staging for T3/T4 non-small-cell lung cancer with additional nodule

Background

Non-small-cell lung cancer (NSCLC) with additional nodule(s) located in the same lobe or ipsilateral different lobe were designated as T3 and T4, respectively, which was merely defined by anatomical location of additional nodule(s), regardless of other prognostic factors.

Methods

A total of 4711 patients with T1-4, N0-2, M0 NSCLC undergoing complete resection were identified between 2009 and 2014, including 145 patients with additional nodule(s) in the same lobe (T3-Add) and 174 patients with additional tumor nodule(s) in ipsilateral different lobe (T4-Add). Overall survival (OS) was compared using multivariable Cox regression models and propensity score matching analysis (PSM).

Results

T3-Add patients [T3-Add versus T3, hazard ratio (HR), 0.695; 95% confidence interval (CI), 0.528-0.915; p = 0.009] and comparable OS with T2b patients through multivariable Cox analysis, and further validated by PSM. T4-Add patients carried a wide spectrum of prognosis, and the largest diameter of single tumor was screened out as the most effective indicator for distinguishing prognosis. T4-Add (⩽3 cm) patients had better OS than T4 patients [T4-Add (⩽3 cm) versus T4, HR, 0.629; 95% CI, 0.455-0.869; p = 0.005] and comparable OS with T3 patients. And T4-Add (>3 cm) patients had comparable OS with T4 patients.

Conclusion

NSCLC patients with additional nodule(s) in the same lobe and ipsilateral different lobe (maximum tumor diameter ⩽ 3 cm) should be further validated and considered restaging as T2b and T3 in the forthcoming 9th tumor, node, and metastasis staging system.