Log odds of positive lymph nodes as a novel prognostic indicator in NSCLC staging

Lymph Node Log-Odds Ratio Accurately Defines Prognosis in Resectable Non-Small Cell Lung Cancer

Objectives: The ratio of positive and resected lymph nodes (LN ratio) has been shown to be prognostic in non-small cell lung cancer (NSCLC). Contrary to the LN ratio, calculating the LN log-odds ratio (LN-LOR) additionally considers the total number of resected lymph nodes. We aim to evaluate LN-LOR between positive and resected lymph nodes as a prognostic factor in operable NSCLC. Methods: Patients with NSCLC who underwent curative intent lobectomy treated at two high-volume centers were retrospectively studied. LN-LOR was dichotomized according to impact on OS and further combined with N descriptors and correlated with clinical variables and survival. Results: 944 patients were included. Cut-off analysis revealed that an LN-LOR of −0.34 significantly discriminated patients according to OS (p < 0.001, chi-squared test 41.26). When combined with N1 and N2 descriptors, LN-LOR low risk (median OS not reached and 83 months) and LN-LOR high-risk patients (median OS 50 and 59 months) had similar survival irrespective of the anatomical location of the positive lymph nodes. Multivariable Cox regression analysis revealed that age (HR 1.02, 95% CI 1.001–1.032), sex (male, HR 1.65, 95% CI 1.25–2.19), histological subtype (HR 2.11, 95% CI 1.35–3.29), pathological stage (HR 1.23, 95% CI 1.01–1.45) and LN-LOR risk groups (low risk, HR 0.48, 95% CI 0.32–0.72) were independent prognostic factors for OS. Conclusions: This retrospective two-center analysis shows that LN-LOR is significantly associated with OS in resectable NSCLC and might better reflect the biological behavior of the disease, regardless of anatomical lymph node locations. This finding may additionally support the value of extensive LN dissection.

Construction and validation of nomograms based on the log odds of positive lymph nodes to predict the prognosis of lung neuroendocrine tumors

Background

This research aimed to investigate the predictive performance of log odds of positive lymph nodes (LODDS) for the long-term prognosis of patients with node-positive lung neuroendocrine tumors (LNETs).

Methods

We collected 506 eligible patients with resected N1/N2 classification LNETs from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The study cohort was split into derivation cohort (n=300) and external validation cohort (n=206) based on different geographic regions. Nomograms were constructed based on the derivation cohort and validated using the external validation cohort to predict the 1-, 3-, and 5-year cancer-specific survival (CSS) and overall survival (OS) of patients with LNETs. The accuracy and clinical practicability of nomograms were tested by Harrell’s concordance index (C-index), integrated discrimination improvement (IDI), net reclassification improvement (NRI), calibration plots, and decision curve analyses.

Results

The Cox proportional-hazards model showed the high LODDS group (-0.79≤LODDS) had significantly higher mortality compared to those in the low LODDS group (LODDS<-0.79) for both CSS and OS. In addition, age at diagnosis, sex, histotype, type of surgery, radiotherapy, and chemotherapy were also chosen as predictors in Cox regression analyses using stepwise Akaike information criterion method and included in the nomograms. The values of C-index, NRI, and IDI proved that the established nomograms were better than the conventional eighth edition of the TNM staging system. The calibration plots for predictions of the 1-, 3-, and 5-year CSS/OS were in excellent agreement. Decision curve analyses showed that the nomograms had value in terms of clinical application.

Conclusions

We created visualized nomograms for CSS and OS of LNET patients, facilitating clinicians to bring individually tailored risk assessment and therapy.

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.

Dynamic nomograms combining N classification with ratio-based nodal classifications to predict long-term survival for patients with lung adenocarcinoma after surgery: a SEER population-based study

BACKGROUND

The prognostic roles of three lymph node classifications, number of positive lymph nodes (NPLN), log odds of positive lymph nodes (LODDS), and lymph node ratio (LNR) in lung adenocarcinoma are unclear. We aim to find the classification with the strongest predictive power and combine it with the American Joint Committee on Cancer (AJCC) 8th TNM stage to establish an optimal prognostic nomogram.

METHODS

25,005 patients with T1-4N0-2M0 lung adenocarcinoma after surgery between 2004 to 2016 from the Surveillance, Epidemiology, and End Results database were included. The study cohort was divided into training cohort (13,551 patients) and external validation cohort (11,454 patients) according to different geographic region. Univariate and multivariate Cox regression analyses were performed on the training cohort to evaluate the predictive performance of NPLN (Model 1), LODDS (Model 2), LNR (Model 3) or LODDS+LNR (Model 4) respectively for cancer-specific survival and overall survival. Likelihood-ratio χ2 test, Akaike Information Criterion, Harrell concordance index, integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used to evaluate the predictive performance of the models. Nomograms were established according to the optimal models. They're put into internal validation using bootstrapping technique and external validation using calibration curves. Nomograms were compared with AJCC 8th TNM stage using decision curve analysis.

RESULTS

NPLN, LODDS and LNR were independent prognostic factors for cancer-specific survival and overall survival. LODDS+LNR (Model 4) demonstrated the highest Likelihood-ratio χ2 test, highest Harrell concordance index, and lowest Akaike Information Criterion, and IDI and NRI values suggested Model 4 had better prediction accuracy than other models. Internal and external validations showed that the nomograms combining TNM stage with LODDS+LNR were convincingly precise. Decision curve analysis suggested the nomograms performed better than AJCC 8th TNM stage in clinical practicability.

CONCLUSIONS

We constructed online nomograms for cancer-specific survival and overall survival of lung adenocarcinoma patients after surgery, which may facilitate doctors to provide highly individualized therapy.

Alternative methods of lymph node staging in lung cancer: a narrative review

The nodal status indicator in non-small cell lung cancer is one of the most crucial prognostic factors available. However, there are still many arguments among scientists regarding whether the currently used nodal status descriptor should be changed in the forthcoming editions of the Tumor Node Metastasis classification or whether it is precise enough and should be maintained as is. We reviewed studies concerning nodal factor classifications to evaluate their accuracy in non-small cell lung cancer patients and to address the previously mentioned challenge. We reviewed the PubMed database regarding the following classifications: ongoing 8^th edition of the Tumor Node Metastasis classification, number of positive lymph nodes, number of negative lymph nodes, number of dissected lymph nodes, lymph node ratio, nodal chains, log odds of positive lymph nodes, zone-based classification and one that is based on the number of lymph node stations involved. Moreover, we analysed data regarding various combinations of these classifications. Our analysis showed that the present nodal staging may not accurately categorize every lung cancer patient. The number of positive lymph nodes and lymph node ratio or the log odds of positive lymph nodes (as the mathematical modification of lymph node ratio) are more legitimate, as they possess very robust data and should be considered initially as additional factors that can be incorporated in ongoing nodal staging systems. Forthcoming non-small cell lung cancer staging systems could benefit from the addition of quantitative-based parameters. Additionally, the minimal extent of lymphadenectomy should be established as staging benefits from it. International, prospective validation studies need to be performed to optimize the cut-off values and prognostic groups and to confirm the superiority of the newly suggested descriptors in non-small cell lung cancer nodal staging.

Prognostic value of log odds of positive lymph nodes in node-positive lung squamous cell carcinoma patients after surgery: a SEER population-based study

Background

Log odds of positive lymph nodes (LODDS) is a novel and promising ratio-based lymph node (LN) staging system in many malignancies. This study aimed to evaluate the prognostic value of LODDS, and comprehensively compare the prognostic predictive performance of LODDS with the American Joint Committee on Cancer (AJCC) N classification, number of positive lymph node (NPLN), and lymph node ratio (LNR) among node-positive lung squamous cell carcinoma (SCC) patients after surgery.

Methods

We identified 2,561 patients with N1/N2 stage SCC diagnosed between 2004 and 2014 from the Surveillance, Epidemiology, and End Results (SEER) database. X-tile analysis was used to calculate the optimal cut-off value for each staging system. Univariable and Multivariable Cox regression analyses were used to assess the association of cancer-specific survival (CSS), and overall survival (OS) with N, NPLN, LNR, and LODDS, separately, and integrally. Moreover, linear trend χ² score, likelihood ratio (LR) test, Akaike information criterion (AIC), and Harrell concordance index (C-index) were adopted as criteria for assessing the predictive ability of each model.

Results

The optimal cut-off values for NPLN, LNR, and LODDS were 3, 0.28, and −0.37, respectively. N, NPLN, LNR, and LODDS were identified as independent prognostic predictors for CSS and OS in patients with SCC when each of them was incorporated into multivariable Cox model separately. Additionally, LODDS had the higher linear trend χ² score, higher LR χ² test score, lower AIC, and higher C-index compared to the other three systems. Moreover, a combination of N, NPLN, and LODDS was superior to any staging system alone for predicting prognosis.

Conclusions

LODDS showed better predictive performance than N, NPLN, and LNR among patients with node-positive SCC after surgery. A combination of LODDS and the current AJCC TNM classification has the potential for becoming a better staging method to more precisely predicting prognosis.

Negative Lymph Node Count Predicts Survival of Resected Non-small Cell Lung Cancer

PURPOSE

The purpose of this study was to explore the association between the negative lymph node (NLN) count and survival, as well as compare the prognostic value of the positive lymph node (PLN) count, lymph node ratio (the PLN count/total lymph nodes examined, LNR), and NLN count in patients with non-small cell lung cancer (NSCLC).

METHODS

We identified patients diagnosed with NSCLC between 2005 and 2011 from the Surveillance, Epidemiology, and End Results database. Outcomes of interest were lung cancer-specific survival (LCSS) and overall survival (OS). Cases were divided into several groups based on the PLN count, NLN count, and LNR. The prognostic significance of the PLN count, NLN count, and LNR models was analyzed with the Kaplan-Meier method and the Cox regression model.

RESULTS

39,959 patients with surgical resection for NSCLC were identified. Univariate analysis demonstrated that a greater count of NLNs was associated with better LCSS (P < 0.001) and OS (P < 0.001). Subgroup analysis showed that the NLN count could predict survival in both node-negative and node-positive patients. Multivariable analysis revealed that the NLN count was an independent prognostic factor for LCSS and OS.

CONCLUSION

The NLN count is an independent prognostic factor of OS and LCSS in patients with NSCLC, as well as the PLN count and LNR. The prognostic value of the PLN count, NLN count, and LNR shows no difference.

Prognostic value of lymph node ratio in non-small-cell lung cancer: a meta-analysis

BACKGROUND

This meta-analysis aimed to investigate the prognostic value of lymph node ratio in non-small-cell lung cancer.

METHODS

We searched systematically for eligible studies in PubMed, Web of Science, Medline (via Ovid) and Cochrane library through 6 November 2018. The primary outcome was overall survival. Disease-free survival and cancer-specific survival were considered as secondary outcomes. Hazard ratio with corresponding 95% confidence interval were pooled. Quality assessment of included studies was conducted. Subgroup analyses were performed based on N descriptors, types of tumor resection, types of lymphadenectomy and study areas. Sensitivity analysis and evaluation of publication bias were also performed.

RESULTS

Altogether, 20 cohorts enrolling 76 929 patients were included. Mean Newcastle-Ottawa Scale was 7.65 ± 0.59, indicating the studies' quality was high. The overall result showed non-small-cell lung cancer patients with lower lymph node ratio was associated with better overall survival (HR: 1.946; 95% CI: 1.746-2.169; P < 0.001), disease-free survival (HR: 2.058; 95% CI: 1.717-2.467; P < 0.001) and cancer-specific survival (HR: 2.149; 95% CI: 1.864-2.477; P < 0.001). Subgroup analysis prompted types of lymphadenectomy and the station of positive lymph node have an important effect on the prognosis. No significant discovery was found in sensitivity analysis.

CONCLUSION

Patients with lower lymph node ratio was associated with better survival, indicating that lymph node ratio may be a promising prognostic predictor in non-small-cell lung cancer. The type of lymphadenectomy, an adequate examined number and the removed stations should be considered for more accurate prognosis assessment.

Comparison of three lymph node staging schemes for predicting the outcome in patients with small bowel adenocarcinoma: A population-based cohort and international multicentre cohort study

BACKGROUND

The prognostic roles of three common lymph node staging schemes, number of positive lymph nodes (pN), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) in small bowel adenocarcinoma (SBA) are unclear. We assessed their prognostic ability in SBA.

METHODS

A total of 2128 patients diagnosed with SBA between 1988 and 2010 from the Surveillance, Epidemiology, and End Results (SEER) database and 186 patients from 15 hospitals in France and China were identified. We evaluated the prognostic ability of the schemes in both continuous and stratified patterns using R2, Harrell's C, and time-dependent receiver operating characteristic curve analyses.

FINDINGS

For continuous pattern, the LODDS had a better capacity of discrimination and higher accuracy of prognosis than pN and LNR. Similarly, the stratified LODDS classification had a better performance of discrimination and higher accuracy of prognosis than the pN and LNR classification. The multivariable model using the LODDS classification also showed superiorly predictive accuracy and discriminatory capacity to those of the 7th and, 8th TNM node and LNR classification. These results were fully validated in an independent international multicentre cohort.

INTERPRETATION

The LODDS scheme showed a better prognostic performance than the LNR or pN schemes in patients with SBA regardless of continuous or stratified pattern. The LODDS scheme could serve as an auxiliary to lymph node staging systems in future revisions of the American Joint Committee on Cancer (AJCC) manual. FUND: This work was funded by the Zhejiang Province Natural Science Fund of China.

Comparison of different prognostic models for predicting cancer-specific survival in bladder transitional cell carcinoma

OBJECTIVE

To construct the newly valuable nomogram which can compare the predictive performance with American Joint Committee on Cancer (AJCC) staging system in bladder transitional cell carcinoma (BTCC).

METHODS

BTCC patients were screened (2004-2015) from the SEER database. The nomogram incorporating lymph node ratio was constructed to evaluate individualized cancer-specific survival.

RESULTS

The C-index of the nomogram for predicting cancer-specific survival was 0.743 (95% CI: 0.720-0.766), which was higher than C-index of the AJCC staging system.

CONCLUSION

Lymph node ratio can be a reliable prognostic indicator for BTCC. The proposed nomogram showed more satisfactory predictive accuracy and wider applicability than current AJCC staging system in individualized prediction of BTCC patients.