Prognostic relevance of regional lymph-node distribution in patients with N1-positive non-small cell lung cancer: A retrospective single-center analysis

Can stage-IIB lung cancer be divided into subgroups in terms of prognosis? A modelling study. Acta Chir Belg 2024;124:191-199. [PMID: 37615953 DOI: 10.1080/00015458.2023.2251802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

INTRODUCTION

Whether changes should be made to the TNM classification of non-small cell lung cancer (NSCLC) according to the newly proposed nodal classification is unclear. We aim to compare the survival between stage-IIB subsets using a modelling study performed using the newly proposed nodal classification.

PATIENTS AND METHODS

A total of 682 patients with stage-IIB NSCLC based on the 8th TNM classification were analysed. Hazard ratio (HR) values calculated from survival comparisons between stage-IIB subgroups were used to create a model for patients with stage-IIB NSCLC, and modelling was performed according to the HR values that were close to each other.

RESULTS

Patients with T1N1a cancer had the best survival rate (58.2%), whereas the worst prognosis was observed in those with T2bN1b cancer (39.2%). The models were created using the following HR results: Model A (T1N1a, n = 85; 12.4%), Model B (T2a/T2bN1a and T3N0, n = 438; 64.2%), and Model C (T1/T2a/T2bN1b, n = 159; 23.4%). There was a significant difference between the models in terms of overall survival (p = 0.03). The median survival time was 69 months in Model A, 56 months in Model B, and 47 months in Model C (Model A vs. Model B, p = 0.224; Model A vs. Model C, p = 0.01; and Model B vs. Model C, p = 0.04). Multivariate analysis showed that age (p < 0.001), pleural invasion (p < 0.001), and the developed modelling system (p = 0.02) were independently negative prognostic factors.

CONCLUSION

There was a prognostic difference between stage-IIB subsets in NSCLC patients. The model created for stage-IIB lung cancer showed a high discriminatory power for prognosis.

Association of metastatic nodal size with survival in non-surgical non-small cell lung cancer patients: Recommendations for clinical N staging

Background

This study aims to analyze the prognostic significance of the metastatic lymph node (mLN) size in non-small cell lung cancer (NSCLC) patients receiving chemoradiotherapy (CRT) to provide some information for the optimization of clinical nodal (cN) staging.

Methods

A retrospective study with 325 NSCLC patients was conducted between January 2011 and December 2018 at two participating institutes. We evaluated the potential relationship between the mLN size and the survival to propose a potential revised nodal (rN) staging.

Results

Kaplan–Meier analyses showed significant differences in the overall survival (OS) based on the cN staging and the size of mLNs (N0, ≤2 cm, and >2 cm). We found that the nodal size correlated statistically with the response to CRT. The HRs of OS for patients with bulky mLNs increase significantly compared with patients in the non-bulky mLNs group in the cN2-3 group. Interestingly, the HRs of patients with bulky cN2 disease and non-bulky cN3 disease were similar to each other. We classified the patients into five subsets: N0, rN1(cN1), rN2(non-bulky cN2), rN3a(bulky cN2, and non-bulky cN3), and rN3b(bulky cN3). In our study, the rN stage showed better prognostic discrimination than the 8th IASLC cN staging and was an independent prognostic factor for survival.

Conclusions

In addition to the anatomic location, the size of mLNs correlated statistically with the response to CRT and should be incorporated into the cN staging system to predict survival more accurately.

A Comprehensive Comparison of Different Nodal Subclassification Methods in Surgically Resected Non-Small-Cell Lung Cancer Patients

INTRODUCTION

The revision of the N descriptor in non-small-cell lung cancer has been widely discussed in the past few years. Many different subclassification methods based on number or location of lymph nodes have been proposed for better distinguishing different N patients. This study aimed to systematically collect them and provide a comprehensive comparison among different subclassification methods in a large cohort.

METHOD

Pathological N1 or N2 non-small-cell lung cancer patients undergoing surgical resection between 2005 and 2016 in the Western China Lung Cancer Database were retrospectively reviewed. A literature review was conducted to collect previous subclassification methods. Kaplan-Meier and multivariable Cox analyses were used to examine the prognostic performance of subclassification methods. Decision curve analysis, Akaike's information criterion, and area under the receiver operating curve concordance were also performed to evaluate the standardized net benefit of the subclassification methods.

RESULTS

A total of 1625 patients were identified in our cohort. Eight subclassification methods were collected from previous articles and further grouped into subclassification based on number categories (node number or station number), location categories (lymph node zone or chain) or combination of number and location categories. Subclassification based on combination of lymph node location and number tended to have better discrimination ability in multivariable Cox analysis. No significant superiority among the different subclassification methods was observed in the three statistical models.

CONCLUSION

Subclassification based on the combination of location and number could be used to provide a more accurate prognostic stratification in surgically resected NSCLC and is worth further validation.

Hemangiosis carcinomatosa as an independent risk factor for long-term survival in Non-Small Cell Lung Cancer patients

OBJECTIVES

Recent studies have shown that blood vessel invasion (V1) influences the long-term survival of patients with Non-Small Cell Lung Cancer (NSCLC). The aim of the present study was to emphasize V1 as an independent risk factor. We evaluated the effects of V1 on the survival of NSCLC patients with UICC stages I, II, and III after surgery.

METHODS

This retrospective study includes 747 consecutive patients with NSCLC who underwent anatomic resection and radical lymphadenectomy at our institution between January 2012 and December 2020. V1- were compared to V0-patients (no blood vessel invasion). All patients received adjuvant therapy according to European guidelines when indicated. After excluding patients with detection of lymphangiosis carcinomatosa, tumor-cells at the resection margin, distant metastases and those, that received neoadjuvant therapy, 1-, 3- and 5- year survival rates were assessed by Kaplan-Meier method. To proof V1 as an independent risk factor, a propensity score matched (PSM) analysis was performed regarding age, gender, UICC-stage, lymph-node involvement, and comorbidities.

RESULTS

A total of 461 patients (V0: 440; V1: 21) were included in this analysis. Baseline characteristics did not show any significant difference. Mean age in V0-group was 65.7 ± 10.5 years and 64.1 ± 8.6 years in V1-group (p-value = 0.5). In the V0-group 54.8% were male, whereas in the V1-group this number was 66.7% (p-value = 0.37). Mean survival in V1-group was significantly shorter compared to V0-group (V1: 45.8 ± 9.3 months; V0: 81.1 ± 1.1 months; p-value<0.001). This was confirmed after applying a propensity score matched analysis (V0: 99.9 ± 4.9 months; V1: 45.8 ± 9.3 months; p-value<0.001) - V1 is a prognostic marker independent of UICC stage. The 1-, 3- and 5-year survival rates were significantly shorter for V1-patients (1-year: V0: 100%; V1: 70.6%; p-value = 0.012) (3-year: V0: 95.2%; V1: 46.2%; p-value = 0.002) (5-year: V0: 90.5%; V1: 36.4%; p-value = 0.003).

CONCLUSION

As we have shown with our investigations, V1 has a major impact on long-term survival in NSCLC patients and furthermore, acts as an independent risk factor. Due to our small but specified sample size, our statement should be confirmed by a multicenter study. In the meantime, we suggest making the implementation of the V0/V1 specification mandatory in the tumor classification.

The impacts of isolated N1 lymph nodes metastasis on prognosis in non-small cell lung cancer: A single-center experience

Background: This study aims to investigate long-term results related to N1 group metastases with respect to anatomical localization and many external parameters and to examine the effect of these parameters on prognosis in patients with in nonsmall cell lung cancer.

Methods: Between January 2006 and May 2019, a total of 52 patients (44 males, 8 females; mean age: 59.9±9.5 years; range, 42 to 80 years) who underwent lobectomy due to primary lung malignancy were retrospectively analyzed. The N1 lymph nodes were divided into three anatomical groups as hilar, peribronchial, and intraparenchymal. Demographic features, tumor features, follow-up characteristics, and survival and diseasefree survival parameters were analyzed for each group. The results were also examined in terms of number of metastasis, number of metastatic levels, rate of metastasis, and histopathological type.

Results: The five-year survival rate was 66.4% in the peribronchial group and 50% in the hilar group. The five-year disease-free survival rate was 45.7% in the peribronchial group and 37.5% in the hilar group. There was no statistically significant difference between the groups in terms of survival and disease-free survival for anatomical localization, number of metastasis, number of metastatic levels, rate of metastasis, and histopathological type (p>0.05 for all).

Conclusion: The structure that would be formed by examining N1 in terms of parameters such as subtitle levels, number of metastasis, number of metastatic stations, rate of metastasis or combinations of these would have a more impact on the decisions in the follow-up and treatment process in this patient population.

New PET/CT criterion for predicting lymph node metastasis in resectable advanced (stage IB-III) lung cancer: The standard uptake values ratio of ipsilateral/contralateral hilar nodes

Background

The aim of the present study was to use surgical and histological results to develop a simple noninvasive technique to improve nodal staging using preoperative PET/CT in patients with resectable lung cancer.

Methods

Preoperative PET/CT findings (pStage IB–III 182 patients) and pathological diagnoses after surgical resection were evaluated. Using PET/CT images to determine the standardized uptake value (SUV) ratio, the SUV_max of a contralateral hilar lymph node (on the side of the chest opposite to the primary tumor) was measured simultaneously. The I/C‐SUV ratio was calculated as ipsilateral hilar node SUV/contralateral hilar node SUV. Receiver operating characteristic (ROC) curves were then used to analyze those data.

Results

Based on ROC analyses, the cutoff I/C‐SUV ratio for diagnosis of lymph node metastasis was 1.34. With a tumor ipsilateral lymph node SUV_max ≥2.5, an IC‐SUV ratio ≥1.34 had the highest accuracy for predicting N1/N2 metastasis; the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of nodal staging were 60.66, 85.11, 84.09, 62.5 and 71.29%, respectively.

Conclusions

When diagnosing nodal stage, a lymph node I/C‐SUV ratio ≥1.34 can be an effective criterion for determining surgical indications in advanced lung cancer.

Prognostic significance of the N1 classification pattern: a meta-analysis of different subclassification methods

OBJECTIVES

The number of positive lymph node stations has been viewed as a subclassification in the N1 category in the new revision of tumour node metastasis (TNM) staging. However, the survival curve of these patients overlapped with that of some patients in the N2 categories. Our study focused on the prognostic significance of different subclassifications for N1 patients.

METHODS

We systematically searched PubMed, Ovid, Web of Science and the Cochrane Library on the topic of N1 lymph node dissection. Hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were used to assess the prognostic significance of N1 metastases. I2 statistics was used to evaluate heterogeneity among the studies: If significant heterogeneity existed (P ≤ 0.10; I2 >50%), a random effect model was adopted.

RESULTS

After a careful investigation, a total of 17 articles were included in the analysis. The results showed that patients with non-small-cell lung cancer with multistation N1 disease have worse survival compared with those with single-station N1 disease (HR 1.53, 95% CI 1.32-1.77; P < 0.001; I2 = 5.1%). No significant difference was observed between groups when we assessed the number of positive lymph nodes (single or multiple) (HR 1.25, 95% CI 0.96-1.64; P = 0.097; I2 = 72.5%). Patients with positive hilar zone lymph nodes had poorer survival than those limited to the intrapulmonary zone (HR 1.80, 95% CI 1.57-2.07; P < 0.001; I2 = 0%). A subgroup analysis conducted according to the different validated lymph node maps showed a stable result.

CONCLUSIONS

Our result confirmed the prognostic significance of the N1 subclassification based on station number. Meanwhile, location-based classifications, especially zone-based, were also identified as prognostically significant, which may need further confirmation and validation in the staged population.

Development and Validation of a Combined Model for Preoperative Prediction of Lymph Node Metastasis in Peripheral Lung Adenocarcinoma

Background

Based on the “seed and soil” theory proposed by previous studies, we aimed to develop and validate a combined model of machine learning for predicting lymph node metastasis (LNM) in patients with peripheral lung adenocarcinoma (PLADC).

Methods

Radiomics models were developed in a primary cohort of 390 patients (training cohort) with pathologically confirmed PLADC from January 2016 to August 2018. The patients were divided into the LNM (−) and LNM (+) groups. Thereafter, the patients were subdivided according to TNM stages N0, N1, N2, and N3. Radiomic features from unenhanced computed tomography (CT) were extracted. Radiomic signatures of the primary tumor (R1) and adjacent pleura (R2) were built as predictors of LNM. CT morphological features and clinical characteristics were compared between both groups. A combined model incorporating R1, R2, and CT morphological features, and clinical risk factors was developed by multivariate analysis. The combined model’s performance was assessed by receiver operating characteristic (ROC) curve. An internal validation cohort containing 166 consecutive patients from September 2018 to November 2019 was also assessed.

Results

Thirty-one radiomic features of R1 and R2 were significant predictors of LNM (all P < 0.05). Sex, smoking history, tumor size, density, air bronchogram, spiculation, lobulation, necrosis, pleural effusion, and pleural involvement also differed significantly between the groups (all P < 0.05). R1, R2, tumor size, and spiculation in the combined model were independent risk factors for predicting LNM in patients with PLADC, with area under the ROC curves (AUCs) of 0.897 and 0.883 in the training and validation cohorts, respectively. The combined model identified N0, N1, N2, and N3, with AUCs ranging from 0.691–0.927 in the training cohort and 0.700–0.951 in the validation cohort, respectively, thereby indicating good performance.

Conclusion

CT phenotypes of the primary tumor and adjacent pleura were significantly associated with LNM. A combined model incorporating radiomic signatures, CT morphological features, and clinical risk factors can assess LNM of patients with PLADC accurately and non-invasively.

Prognostic Impact of PD-L1 Expression in pN1 NSCLC: A Retrospective Single-Center Analysis

Simple Summary

The analysis of prognostic biomarkers (e.g., PD-L1) helps to define treatment for lung cancer patients. To date, these markers have only been examined in metastatic or inoperable situations. We analyzed the PD-L1 expression-levels of tumors from 277 lung cancer patients that underwent curative intent surgery. PD-L1 was identified as a prognostic factor, depending on histologic subtype.

Abstract

The programmed death-ligand 1 (PD-L1) plays a crucial role in immunomodulatory treatment concepts for end-stage non-small cell lung cancer (NSCLC). To date, its prognostic significance in patients with curative surgical treatment but regional nodal metastases, reflecting tumor spread beyond the primary site, is unclear. We evaluated the prognostic impact of PD-L1 expression in a surgical cohort of 277 consecutive patients with pN1 NSCLC on a tissue microarray. Patients with PD-L1 staining (clone SP263) on >1% of tumor cells were defined as PD-L1 positive. Tumor-specific survival (TSS) of the entire cohort was 64% at five years. Low tumor stage (p < 0.0001) and adjuvant therapy (p = 0.036) were identified as independent positive prognostic factors in multivariate analysis for TSS. PD-L1 negative patients had a significantly better survival following adjuvant chemotherapy than PD-L1 positive patients. The benefit of adjuvant therapy diminished in patients with PD-L1 expression in more than 10% of tumor cells. Stratification towards histologic subtype identified PD-L1 as a significant positive predictive factor for TSS after adjuvant therapy in patients with adenocarcinoma, but not squamous cell carcinoma. Routine PD-L1 assessment in curative intent treatment may help to identify patients with a better prognosis. Further research is needed to elucidate the predictive value of PD-L1 in an adjuvant setting.

Validation of the 8th Edition Nodal Staging and Proposal of New Nodal Categories for Future Editions of the TNM Classification of Non-Small Cell Lung Cancer

BACKGROUND

The International Association for the Study of Lung Cancer (IASLC) N classifications, which depend on the location and involvement of the lymph nodes, provide accurate prognoses. This study validated the efficiency of classifications using a single-institution dataset and proposed a modified system based on 5-level N1 node dissection.

METHODS

From January 2005 to December 2014, 1851 patients with completely resected non-small cell lung cancer were reviewed. According to the IASLC recommendations, N1 is further subdivided into N1a (single) and N1b (multiple), N2 is divided into N2a1 (single station without N1), N2a2 (single station with N1), and N2b (multiple station). Additionally, we evaluated dividing N0 into N0a (with level 13/14 examination) and N0b (without level 13/14 examination), and N1 into N1a* (only level 13/14 positive) and N1b* (level 10-12 positive). Overall survival was also compared.

RESULTS

Multivariate analysis showed that the N classifications recommended by the IASLC and those proposed and evaluated by this study could both significantly predict the prognoses of patients (p < 0.001, respectively). There was no significant difference in survival between N1b and N1a (hazard ratio [HR] 1.049, p = 0.83) and N2a1 and N1b (HR 1.314, p = 0.261); however, there were significant differences between N0a and N0b (HR 1.778, p < 0.001) and N1a* and N1b* (HR 2.014, p = 0.019). The survival curve of N1a* overlapped N0b (HR 0.997, p = 0.991), and N2a1 overlapped N1b* (HR 0.842, p = 0.444).

CONCLUSION

More detailed nodal information is required to facilitate future revisions of N staging.

Value of N1 Lymph Node Examination in the Prognosis of Patients With pT1-3N0M0 Non-Small Cell Lung Cancer

Objective

This study aimed to analyze the relationship between the number of examined lymph nodes (ELNs) at the N1 station and the postoperative clinicopathological features and prognosis of patients with pT1-3N0M0 non-small cell lung cancer (NSCLC).

Methods

The cut-off value of the number of ELNs at the N1 station was obtained using X-tile software analysis. Kaplan-Meier survival curve analysis and the Cox proportional hazard model were used to study the impact of the number of ELNs at the N1 station on the prognosis of postoperative patients with pT1-3N0M0 NSCLC.

Results

The median survival time and 1-, 3- and 5-year survival rates of 0 ELNs at the N1 station were 28.0 months and 74.8%, 45.4%, and 21.2%, respectively. The median survival time and 1-, 3-, and 5-year survival rates of 1–4 ELNs at the N1 station were 45.0 months and 85.5%, 55.4%, and 39.1%, respectively. In the group with ≥ 5 ELNs at the N1 station, the median survival time and the 1-, 3- and 5-year survival rates were 59.0 months and 94.0%, 62.7%, and 48.2%, respectively. Both univariate and multivariate Cox regression analyses showed that the number of ELNs at the N1 station, T stage and operation type were independent factors affecting the prognosis of patients with pT1-3N0M0 NSCLC.

Conclusion

Increasing the number of ELNs at the N1 station is positively correlated with the long-term survival rate of patients with T1-3N0M0 NSCLC. At least 5 LNs at the N1 station should be examined in pathological examination.

Prognostic Value of Red Blood Cell Distribution Width in Resected pN1 Lung Adenocarcinoma

Simple Summary

Red blood cell distribution width is a measure of the variation of erythrocyte volume. Impaired erythropoiesis can lead to a wide variation in erythrocyte dimension—defined as anisocytosis—indicating that pathological modifications are taking place. Recently, red blood cell distribution width has been advocated as an effective prognostic factor in cardiovascular diseases, acute kidney injury, autoimmune disease, and oncologic settings. In many advanced and several early-stage oncologic conditions, it has shown excellent prognostic efficacy; we therefore investigated what prognostic role red blood cell distribution width may have in resected lung cancer, focusing on pN1 adenocarcinoma patients in whom adjuvant treatments—although well-established—are still proposed case by case. Our findings suggest that red blood cell distribution width is strictly related to disease-free survival; it could therefore be considered as a further tool for planning postoperative adjuvant treatments and setting up an adequate follow-up program.

Abstract

Background: Red blood cell distribution width is a measure of the variation of erythrocyte volume and has recently been advocated as a prognostic tool in neoplastic and non-neoplastic diseases. We studied the prognostic role of preoperative red blood cell distribution width (RDW) in resected pN1 lung adenocarcinoma patients. Methods: Sixty-seven consecutive pN1 lung adenocarcinoma patients operated in the last two years were retrospectively evaluated in the present study. Age, sex, smoking status, type of surgical resection, neoadjuvant and adjuvant treatments, pathological stage, T and N status, tumor size, preoperative hemoglobin (Hb) and RDW, preoperative neutrophils, lymphocytes, and their ratio were collected for each patient. Outpatient follow-up was performed and date of relapse was recorded. Results: There were 24 females (35.8%). Twenty-eight patients (41.8%) belonged to stage 3A and thirty-nine patients (58.2%) to stage 2B. Mean preoperative RDW % was 14.1 (IQR: 12.9–14.8). Univariate analysis disclosed preoperative RDW as strictly related to disease-free survival (p = 0.02), which was confirmed in the exploratory multivariable analysis (p = 0.003). Conclusions: Pre-operative RDW is an effective prognostic factor of disease-free survival in resected pN1 lung adenocarcinoma; it could therefore be considered as a further tool for planning postoperative adjuvant treatments and setting up an adequate follow-up program.