Lymph Node Ratio Predicts Recurrence and Survival After R0 Resection for Non-Small Cell Lung Cancer

Advantages of robotic-assisted thoracic surgery after neoadjuvant therapy in NSCLC: A propensity score-matched analysis

BACKGROUND

Robot-assisted thoracic surgery (RATS) was advantageous in complex procedures. Neoadjuvant therapy leads to intra-operative difficulty in non-small cell lung cancer (NSCLC). The aim of this study was to compare RATS and video-assisted thoracic surgery (VATS) in neoadjuvant setting.

METHODS

This retrospective study included stage II-IIIB(N2) NSCLC patients who underwent surgery after receiving neoadjuvant therapy. Patients were grouped by RATS or VATS. The primary outcomes are R0 resection rate, operation time and estimated blood loss. The secondary outcome is the rate of conversion to thoracotomy. Demographic data, clinical data and pathological data were collected for analysis. Propensity score matching (PSM) was applied to balance bias.

RESULTS

Between July 2021 and June 2024, 118 patients received RATS and 317 patients received VATS were included. Before PSM, RATS was associated with a significantly shorter operative time (194 min vs. 223 min, p < 0.001) and a lower conversion rate to thoracotomy (8.47 % vs. 18.6 %, p = 0.015). However, no significant differences were observed in the R0 resection rate (p = 0.306) or mean estimated blood loss (p = 0.371). After PSM, RATS still demonstrated advantages in operation time (194 min vs 223 min, p = 0.001), reducing conversion caused by fibrosis or difficult exposure (p = 0.005), and number of N2 lymph nodes (p = 0.02). Single and multiple regressions both suggested RATS was associated with shorter operation time and lower conversion rate.

CONCLUSIONS

Our study suggested that RATS is a superior approach compared with VATS in neoadjuvant context, with advantages in shortening operation time, reducing conversion rate, and lymph node dissection.

Compartmental surgery for squamous cell carcinoma of the buccal mucosa: description of a new surgical technique

BACKGROUND

Oral squamous cell carcinoma (OSCC) is the sixth most common cancer globally. Patient survival varies depending on tumour stage and oral cavity subsites. Buccal mucosa neoplasia is rare and burdened by worse prognosis than other oral subsites, showing a high rate of loco-regional relapses within six months after treatment. According to NCCN guidelines, the gold standard treatment is radical surgery. In the oral cavity, the buccal mucosa subsite lacks anatomical barriers opposing neoplastic growth. At this level, the tumour cells could hypothetically spread along the fibres of the platysma muscle or the lymphatic networks of the peri-facial vessels without encountering any resistance. Due to the aggressive locoregional spread, radical surgery is mandatory to improve patient survival.

METHODS

This technical note describes the cheek compartmental surgical approach step by step. For intermediate-advanced stage cancer, the surgery should include the resection of the tumour with adequate free margins, the dissection of neck lymph nodes and the lymphatic network with the structures between the tumour (T) and the neck (N), the so-called "T-N tract". The buccal mucosa compartment may be defined as a three-dimensional space between the oral cavity mucosa, the vessel plane, and the lymph nodes of the neck (levels I-IV). These structures, connected by the platysma muscle and the facial vessels, may be considered the T-N tract of the mucosal cheek compartment.

RESULTS

By removing all the possible pathways of tumour spread via compartmental surgery (en-bloc resection of the tumour with T-N tract and lymphatic network and lymph nodes) for buccal mucosa cancers, one could provide better locoregional control of disease in intermediate-advanced stages.

CONCLUSION

This surgical technique may enable a more accurate control of the surgical margins, especially the deep margins.

Log odds of positive lymph nodes compared to positive lymph node ratio and number of positive lymph nodes in prognostic modeling for patients with NSCLC undergoing lobectomy or total pneumonectomy: a population-based study using Cox regression and XGBoost with SHAP analysis

Background

Methods such as the number of positive lymph nodes (nPLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) are used to predict prognosis in patients with non-small cell lung cancer (NSCLC). We hypothesized that LODDS could be a superior independent predictor of prognosis and aimed to compare its effectiveness with nPLN and LNR in predicting survival outcomes in stage I-IIIA NSCLC patients.

Methods

We utilized data from the Surveillance, Epidemiology, and End Results (SEER) 17 registry (2010-2019) to study NSCLC patients, focusing on those who underwent surgery with confirmed lymph node involvement (N1 or N2 disease). We aimed to compare overall survival (OS) and cancer-specific survival (CSS) based on nPLN, LNR, and LODDS. Kaplan-Meier and Cox regression analyses were employed to evaluate survival, with thresholds determined using X-tile software. An XGBoost model was constructed to predict overall survival in patients using three features: LODDS, LNR, and PLN. SHapley Additive exPlanations (SHAP) analysis was applied to assess feature importance and provide interpretable insights into the model's predictions.

Results

The study analyzed 3,132 eligible NSCLC patients from the SEER database, predominantly male (53.07%) with adenocarcinoma (43.65%) or squamous cell carcinoma (29.76%). Survival outcomes were assessed using nPLN, LNR, and LODDS. LODDS showed superior predictive value for both OS and CSS compared to nPLN and LNR, as indicated by a larger Log Likelihood Ratio (LLR) and smaller Akaike Information Criterion (AIC). Higher scores on npLN, LNR, and LODDS were strongly related with a poorer prognosis, according to Kaplan-Meier analyses (P < 0.001). The SHAP (SHapley Additive exPlanations) analysis of the XGBoost model demonstrated that the LODDS exhibited the highest SHAP values (0.25) for predicting overall survival in patients, consistently outperforming the LNR and the number of nPLN across both training and validation datasets.

Conclusions

Compared to the nPLN and LNR staging systems, LODDS demonstrates superior prognostic power for patients with stage I-IIIA NSCLC undergoing lobectomy or pneumonectomy. By integrating both positive and negative lymph node information, LODDS offers a refined risk stratification that is particularly valuable in cases with high lymph node heterogeneity.

Validation of IASLC 9th edition TNM classification for lung cancer: focus on N descriptor

BACKGROUND

We externally validated the proposed 9th edition of the TNM staging classification with our institution's prospectively collected data and compared it to the 8th edition for overall survival (OS) and freedom from recurrence (FFR).

METHODS

A retrospective analysis was conducted of 4029 cases of stage I-III non-small cell lung cancer that underwent surgical treatment from January 2004 to December 2020. Survival was compared using Kaplan-Meier curves and multivariable Cox regression analysis. The concordance index (C-index), Alkaike information criterion (AIC), and R2 were used to assess the discriminatory ability.

RESULTS

In the 9th edition, the N2 category (n = 352) was subdivided into N2a (n = 256, 72.7%) and N2b (n = 96, 27.3%). The TNM stage changes were as follows: (1) IIB to IIA, 151 cases (26.0%); (2) IIIA to IIB, 52 cases (11.5%); (3) IIIB to IIIA, 57 cases (61.3%); (4) IIIA to IIIB, 56 cases (12.4%). The survival curves of the proposed 9th edition demonstrated similar patterns to those of the 8th edition, but with a greater discriminative ability for OS and FFR. Subdividing N2 into N2a and N2b refined prognosis prediction. The C-index, AIC, and R2 demonstrated improved values in the proposed 9th edition compared to the 8th edition.

CONCLUSIONS

The proposed 9th edition of the TNM staging classification for lung cancer showed favorable prognostic validity and better discrimination ability than the 8th edition.

Prognostic value of lymph node ratio in stage III non-small-cell lung cancer: A retrospective cohort study

A growing number of studies have found that the lymph node ratio (LNR) is an important indicator of prognosis in non-small-cell lung cancer (NSCLC). Impact analysis for LNR was performed for survival in patients undergoing surgery for stage III NSCLC compared to the surveillance, epidemiology and end results databank. Clinicopathological variables, such as cancer-specific survival (CSS), were taken from the surveillance epidemiology and end result databank of stage III NSCLC patients who underwent surgery, and the LNR threshold stratification of NSCLC patients was computed by X-tile. CSS was assessed by the Kaplan-Meier method with CSS-independent risk factors calculated by multivariate Cox regression analysis. In total, 7011 lung cancer patients were included. Multifactorial analysis showed that LNR and positive node category had predictive value for stage III NSCLC. In patients with stage IIIA NSCLC, Kaplan-Meier analysis demonstrated that patients with T1-2N2 stage had clearly superior CSS than those with T3-4N1 stage (P < .001), which conflicted with the results from the assessment of primary tumor, lymph nodes, and metastasis/N stage. The cutoff values for LNR were 0.31 and 0.59. Kaplan-Meier analysis demonstrated that the CSS was substantially better in patients with LNR-low than in those with LNR-medium or LNR-high (P < .001), which was also proven by multivariate competing risk regression. Subgroup analysis suggested that the survival advantage of a lower LNR was achieved in all subgroups (sex, race, etc). In stage III NSCLC, the LNR is a valuable factor for assessing prognosis, in which a higher LNR indicates a worse prognosis.

The value of lymph nodes ratios in the prognosis of resectable remnant gastric cancer through the retrospective propensity score matching analysis

PURPOSE

Currently, the characteristics and prognosis of remnant gastric cancer (RGC) are not fully understood yet. The present study aimed to describe the details of clinicopathological features of resectable RGC and investigated the factors affecting survival after the curative operation.

METHODS

From Jan. 2006 to Dec. 2015, a total of 118 resectable RGC patients (the RGC group) and 236 age-, sex- and TNM stages-matched resectable gastric cancer (GC) patients (the control group) were recruited retrospectively. Clinicopathological characteristics and overall survival were compared between the two groups.

RESULTS

The overall survival rate was 46.61% for RGC patients compared to 55.08% for control groups (P < 0.01), and the mean overall survival time of RGC patients was 40.23 ± 32.27 months, compared to 55.06 ± 34.29 months in the control group (P = 0.023 after matching). The overall survival (OS) of RGC patients with stage IIb was much worse than IIa (P < 0.001) and similar to IIIa (P = 0.463) and IIIb (P = 0.014). Multivariate Cox proportional hazards model analysis revealed that TNM stage (HR: 3.899, P < 0.001) and lymph nodes ratio (LNR) (HR: 2.405, P = 0.028) were independent prognostic significance to OS.

CONCLUSIONS

The OS of RGC was much worse than GC with similar TNM stages, and LNR might consider a highly reliable indicator to evaluate the prognostic in RGC.

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.

Patients with Lower Positive Lymph Nodes Ratio May Benefit from Preoperative Radiotherapy in Stage III Non-Small Cell Lung Cancer

BACKGROUND

Although preoperative radiotherapy (PORT) is a promising therapeutic option for stage III non-small cell lung cancer (NSCLC), the efficacy of this treatment remains controversial. The positive lymph node ratio (PLNR) is recognized as an independent prognostic factor for survival. However, no previous studies have focused on the association between PLNR and PORT in stage III NSCLC.

METHODS

Data were collected from the Surveillance, Epidemiology and End Results (SEER) database, and all patients enrolled in this analysis were diagnosed during 2010-2015. The primary endpoint was overall survival (OS). Univariate and multivariate Cox regression analysis was used to identify factors associated with survival before and after case-control matching. PLNR was defined as the ratio of the number of positive lymph nodes to the total number of retrieved or examined lymph nodes. A cutoff value for PLNR was calculated using an X-tile model.

RESULTS

Overall, 391 patients with PORT and 2814 patients without PORT were enrolled in this study. The cohort after 1:1 case-control matching included 322 patients who received PORT and 322 patients without PORT. PORT was not associated with a significant effect on OS (HR  =  1.14; 95% CI: 0.91-1.43; P  =  0.825). Multivariate Cox regression analysis showed that PLNR (P < 0.001) was independently associated with OS in patients with stage III NSCLC. An X-tile model was used to identify a cutoff value for PLNR: the risk of death was significantly lower in patients with PLNR ≤0.41 who received PORT than in those with PLNR >0.41 who received PORT (HR  =  0.59; 95% CI: 0.38-0.91; P  =  0.015).

CONCLUSION

PLNR may be a prognostic factor for survival in patients with stage III NSCLC who undergo PORT. Lower PLNR is a predictor of better OS and thus warrants further study.

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.

The Effect of Examined Lymph Nodes and Lymph Node Ratio on Pathological Nodal Classification in the Lung Adenosquamous Carcinoma After Lobectomy

Objective

The effects of examined lymph nodes (LNs) and lymph node ratio (LNR) on pN classification and the prognosis are unclear in lung adenosquamous carcinoma (ASC) patients. Thus, this study aimed to investigate the significance of LNs and LNR in the prognosis of ASC and the impact of the abovementioned factors on the pN classification.

Methods

Patients diagnosed with pathological stage T1-4N0-2M0 ASC from the Surveillance Epidemiology and End Results database were included in the study. The primary clinical endpoint was cancer-specific survival (CSS). The optimal cutoff values of the LNs and LNR were determined. An LN indicator, including pN0 #LNs ≤9, pN0 #LNs >9, pN⁺ #LNR ≤0.53, and pN⁺ #LNR > 0.53, was developed. Concordance index (C-index) was used to compare the prognostic predictive ability between N classification and LN indicator. The univariable and multivariable Cox regression analyses were used in this study.

Results

The cohort of 1,416 patients were included in the study. The level of LNs stratified the patients without metastasis of lymph nodes (pN0 #LNs ≤9 vs. pN0 #LNs >9, unadjusted hazard ratio [HR] = 1.255, P = 0.037). Two groups based on the cutoff value of LNR differentiated prognosis of patients with metastasis of lymph nodes (pN⁺ #LNR >0.53 vs. pN⁺ #LNR ≤0.53, unadjusted HR = 1.703, P = 0.001). The LN indicator had a much better predictive ability over N classification in this cohort (LN indicator: C-index = 0.615; N classification: C-index = 0.602, P = 0.001).

Conclusions

We explored clinicopathological factors affecting prognosis in resected lung ASC patients. Besides, the LN indicator was confirmed to be played an essential role in affecting the survival rate in ASC patients. The high-level LNs or low-level LNR might be corelated to improved survival outcomes.

Establishment and Validation of a Nomogram Based on Negative Lymph Nodes to Predict Survival in Postoperative Patients with non-Small Cell Lung Cancer

Background: The importance of the negative lymph node (NLN) count has recently attracted attention. This study aimed to determine the prognostic value of NLN count in patients with non-small cell lung cancer (NSCLC) after radical surgery by constructing NLN-based prognostic models. Methods: This study included 33 756 patients pooled from the case listing session of the US Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and 545 patients collected from The First Affiliated Hospital of Shandong First Medical University between 2012 and 2016. X-tile software was used to calculate the optimal cutoff value for the NLN count. The associated clinical factors were determined using univariate and multivariate Cox analyses. Nomograms were developed using the SEER database and validated using hospital data. Results: The training cohort was divided into high and low NLN count subgroups based on the cancer-specific survival (CSS) and overall survival (OS), respectively. Multivariate analysis showed that NLN count was an independent prognostic factor, and the high NLN count subgroup had better CSS and OS than those of the low NLN count subgroup (HR = 0.632, 95% CI 0.551-0.724, P < .001 for CSS and HR = 0.641, 95% CI 0.571-0.720, P < .001 for OS). Nomograms were established, exhibiting good discrimination ability with a C-index of 0.789 (95% CI 0.778 −0.798) for CSS and 0.704 (95% CI, 0.694 −0.714) for OS. The calibration plots of the validation cohorts showed optimal agreement with the training cohort, with a C-index of 0.681 (95% CI 0.646 −0.716) for CSS and 0.645 (95% CI 0.614 −0.676) for OS. Conclusions: NLN count is a strong prognostic factor for OS and CSS in NSCLC patients and the prognostic model provides a useful risk stratification for NSCLC patients when applied to clinical practice.

Predictive Risk Factors for Early Recurrence of Stage pIIIA-N2 Non-Small Cell Lung Cancer

Purpose

Inflammatory biomarkers and clinical pathological factors have been reported to predict survival of patients with non-small cell lung cancer (NSCLC). The goal of this study was to identify risk factors for early recurrence in patients with pIIIA-N2 NSCLC who had undergone radial resection.

Methods

A retrospective analysis was conducted on 238 patients with pIIIA-N2 NSCLC who underwent surgical treatment at the First Affiliated Hospital of Wenzhou Medical University between December 2006 and August 2018. The early recurrence (ER) group included patients who recurred within one year of curative resection, while the non-early recurrence (NER) group included patients who did not recurrence or recurrence beyond one year. The univariate and multivariate Cox proportional risk analyses were used to identify prognostic factors associated with early recurrence, while the chi-square test was used for categorical data. Overall survival and recurrence-free survival were assessed by Kaplan–Meier estimates.

Results

A total of 69 patients experienced an early recurrence, while the remaining 169 patients did not relapse within one year. ER patients had a much worse prognosis than NER patients, with median survival times of 20.6 and 83.1 months, respectively. Multivariate analysis showed that smoking status, tumor size, metastatic lymph node ratio (LNR) and platelet-to-lymphocyte ratio (PLR) were independent risk factor of early recurrence. Patients with early recurrence were more likely to develop bone metastases.

Conclusion

Smoking history, large tumour size, and elevated LNR and PLR values in pIIIA-N2 NSCLC patients after complete resection may have a significant risk of early recurrence. Based on these independent risk indicators, this prediction model may successfully predict early recurrence and advise individual treatment.

Lymph Node Parameters Predict Adjuvant Chemoradiotherapy Efficacy and Disease-Free Survival in Pathologic N2 Non-Small Cell Lung Cancer

Pathologic N2 non-small cell lung cancer (NSCLC) is prominently intrinsically heterogeneous. We aimed to identify homogeneous prognostic subgroups and evaluate the role of different adjuvant treatments. We retrospectively collected patients with resected pathologic T1-3N2M0 NSCLC from the Shanghai Chest Hospital as the primary cohort and randomly allocated them (3:1) to the training set and the validation set 1. We had patients from the Fudan University Shanghai Cancer Center as an external validation cohort (validation set 2) with the same inclusion and exclusion criteria. Variables significantly related to disease-free survival (DFS) were used to build an adaptive Elastic-Net Cox regression model. Nomogram was used to visualize the model. The discriminative and calibration abilities of the model were assessed by time-dependent area under the receiver operating characteristic curves (AUCs) and calibration curves. The primary cohort consisted of 1,312 patients. Tumor size, histology, grade, skip N2, involved N2 stations, lymph node ratio (LNR), and adjuvant treatment pattern were identified as significant variables associated with DFS and integrated into the adaptive Elastic-Net Cox regression model. A nomogram was developed to predict DFS. The model showed good discrimination (the median AUC in the validation set 1: 0.66, range 0.62 to 0.71; validation set 2: 0.66, range 0.61 to 0.73). We developed and validated a nomogram that contains multiple variables describing lymph node status (skip N2, involved N2 stations, and LNR) to predict the DFS of patients with resected pathologic N2 NSCLC. Through this model, we could identify a subtype of NSCLC with a more malignant clinical biological behavior and found that this subtype remained at high risk of disease recurrence after adjuvant chemoradiotherapy.

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.

A Nomogram to Predict Long-Term Survival Outcomes of Patients Who Undergo Pneumonectomy for Non-small Cell Lung Cancer With Stage I-IIIB

Background: In this study, we aim to establish a nomogram to predict the prognosis of non-small cell lung cancer (NSCLC) patients with stage I-IIIB disease after pneumonectomy. Methods: Patients selected from the Surveillance, Epidemiology, and End Results (SEER, N = 2,373) database were divided into two cohorts, namely a training cohort (SEER-T, N = 1,196) and an internal validation cohort (SEER-V, N = 1,177). Two cohorts were dichotomized into low- and high-risk subgroups by the optimal risk prognostic score (PS). The model was validated by indices of concordance (C-index) and calibration plots. Kaplan-Meier analysis and the log-rank tests were used to compare survival curves between the groups. The primary observational endpoint was cancer-specific survival (CSS). Results: The nomogram comprised six factors as independent prognostic indictors; it significantly distinguished between low- and high-risk groups (all P < 0.05). The unadjusted 5-year CSS rates of high-risk and low-risk groups were 33 and 60% (SEER-T), 34 and 55% (SEER-V), respectively; the C-index of this nomogram in predicting CSS was higher than that in the 8th TNM staging system (SEER-T, 0.629 vs. 0.584, P < 0.001; SEER-V, 0.609 vs. 0.576, P < 0.001). In addition, the PS might be a significant negative indictor on CSS of patients with white patients [unadjusted hazard ration (HR) 1.008, P < 0.001], black patients (unadjusted HR 1.007, P < 0.001), and Asian or Pacific Islander (unadjusted HR 1.008, P = 0.008). In cases with squamous cell carcinoma (unadjusted HR 1.008, P < 0.001) or adenocarcinoma (unadjusted HR 1.008, P < 0.001), PS also might be a significant risk factor. Conclusions: For post-pneumonectomy NSCLC patients, the nomogram may predict their survival with acceptable accuracy and further distinguish high-risk patients from low-risk patients.

The lymph node ratio predicts cancer-specific survival of node-positive non-small cell lung cancer patients: a population-based SEER analysis

Background

Lymph node ratio (LNR) has been suggested to be an effective prognostic tool for stratifying non-small cell lung cancer (NSCLC) cases. In this study, we sought to determine cancer-specific survival (CCS) of NSCLC cases from the SEER registry and used the X-tile method to optimize CCS-based LNR cut-off points for prognostic stratification of node-positive NSCLC.

Methods

CSS and other clinicopathologic variables were retrieved from the SEER registry. Kaplan-Meier methods were used to calculate CSS. The optimal cut-off points for LNR classification were determined by the X-tile approach. Multivariate Cox regression analysis was performed to identify independent risks of CSS.

Results

Totally 11,341 lung cancer patients were included. Their median CSS was 22 months (range 0,143). The median LNR was 0.22 (Q1,Q3: 0.11, 0.50). X-tile analysis showed that the optimal LNR cut-off points were 0.28 and 0.81, dividing the cohort into low (LNR1 ≤ 0.28; n = 6580, 58%), middle (0.28 < LNR2 < 0.81; n = 3025, 26.7%), and high (LNR3 > 0.81; n = 1736, 15.3%) subsets. Kaplan-Meier analysis showed that patients with a low LNR had a significantly higher CCS versus patients with middle or high LNR (P < 0.001). Multivariate competing risks regression analysis revealed that LNR was an independent and significant adverse predictor of CSS (LNR2 vs. LNR1: SHR: 1.56, 95%CI: 1.47,1.67, P < 0.001; LNR3 vs. LNR1: SHR: 2.54, 95%CI: 2.30,2.80, P < 0.001).

Conclusions

LNR is an independent prognostic factor of node-positive NSCLC and its optimal cut-off values established using the robust x-tile method effectively define subpopulations of node-positive NSCLC cases, which is important in guiding selection of treatment strategies clinically.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13019-020-01390-x.

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.

Relationship of lymph node status with survival and recurrence among women with endometrial cancer

OBJECTIVE

To explore the relationship of lymph node ratio (LNR) and other lymph node parameters with disease-free (DFS) and overall (OS) survival among women with endometrial cancer.

METHODS

Retrospective analysis of data of women diagnosed with endometrial cancer at Hacettepe University Hospitals, Ankara, Turkey, between 2003 and 2013. Women who had their surgical procedure, pathology review, and follow-up at Hacettepe University Hospitals were included in the study. Receiver operator characteristic (ROC) curve analysis was used to determine the threshold LNR associated with survival.

RESULTS

Overall, 376 women were included in the study. A higher number of excised metastatic lymph nodes was associated with decreased survival. ROC curve analysis determined a threshold LNR of 0.03. Women with LNR higher than 0.03 had decreased DFS (P<0.001) and OS (P<0.001) relative to those with LNR of 0.03 or lower. LNR of 0.1 was found to be a significant cutoff value for DFS (P=0.023) and OS (P=0.036) among women with at least one metastatic lymph node.

CONCLUSION

LNR may be used as a prognostic tool in endometrial cancer. Future studies will help to define a precise threshold of LNR in order to implement this prognostic factor in daily practice.

Combining node location and node ratio as a prognostic factor for surgical resected non-small cell lung cancer: a population-based study

Background

In the TNM system only the anatomic location is used to define nodal status. In this study we aim to evaluate the effectiveness of combining the location and ratio of metastatic lymph node (pN-NR) for the prognosis of non-small cell lung cancer (NSCLC).

Methods

Patients with pN1/pN2 NSCLC were retrieved from the SEER database. The optimal cut point of NR was determined with the maximal selecting test. All patients were divided into 4 categories with combination of pN (pN1 or pN2) and NR (low or high). The pN-NR was investigated as a predictor of overall survival (OS) and cause-specific survival (CSS) using Cox regression models. Survival curves were plotted using the Kaplan-Meier method and the difference was compared with log-rank test.

Results

A total of 12,170 patients were enrolled. The optimal cut point of NR was 0.3. Patients were divided into 4 groups: pN1-NR <0.3, pN1-NR ≥0.3, pN2-NR <0.3 and pN2-NR ≥0.3. The pN-NR was an independent prognostic factor for survival. Compared with pN1-NR <0.3, the hazard ratio of OS was 1.405 (95% CI: 1.295-1.524), 1.183 (95% CI: 1.113-1257) and 1.717 (95% CI: 1.607-1.835) times higher for pN1-NR ≥0.3, pN2-NR <0.3 and pN2-NR ≥0.3 group, respectively. The survival curves of OS separated well between the 4 pN-NR groups, with 5-year OS 47.1% for pN1-NR <0.3, 43.0% for pN2-NR <0.3, 35.0% for pN1-NR ≥0.3 and 28.5% for pN2-NR ≥0.3, and the P value between neighboring curves was statistically significantly. The same trend was observed for CSS. Subgroup analysis revealed similar results except the pneumonectomy group.

Conclusions

pN-NR could be a good predictor for the prognosis of NSCLC.

The assessment of the optimal number of examined lymph nodes and prognostic models based on lymph nodes for predicting survival outcome in patients with stage N3b gastric cancer

BACKGROUND

The optimal number of examined lymph nodes (ELNs) and the prognostic value of different nodal staging systems remain unclear in the context of N3b gastric cancer.

AIM

To evaluate the optimal number of ELNs and compare the predictive ability of the ELN number, LN ratio (LNR), and log odds of metastatic LNs (LODDS) for overall survival (OS) in patients with resected stage N3b gastric adenocarcinoma in an international database.

METHODS

A total of 868 patients diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database (training cohort) and 144 patients diagnosed between 2011 and 2016 at the Liaoning Cancer Hospital (validation cohort) were identified. Cutoff values were established with X-tile. The 5-year OS rates were compared using Kaplan-Meier curves. Multivariate analysis was conducted with a Cox regression model. The Harrell's concordance index and Akaike's information criterion were used to compare the predictive accuracy of different nodal staging systems.

RESULTS

The ELN number, LNR, and LODDS were independent prognostic factors for both the training and validation cohorts in the multivariate analysis. Patient with ≤26 ELNs, LNR of more than 0.9, and LODDS of more than 1.0 were associated with decrease OS. The LNR and LODDS had similar discriminatory ability for OS and performed better than the ELN number in the Eastern and Western populations.

CONCLUSION

The optimal number of ELN may be 27 or more because LNs retrieved ≤26 was an independent risk factor for the prognosis. The prognostic prediction efficacy of LNR and LODDS was similar and better than that of ELN. Thus, LNR and LODDS could both serve as valid tools to predict OS for stage N3b patients.

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.

Oncologic Outcomes of Surgery Versus SBRT for Non-Small-Cell Lung Carcinoma: A Systematic Review and Meta-analysis

BACKGROUND

The optimal treatment of stage I non-small-cell lung carcinoma is subject to debate. The aim of this study was to compare overall survival and oncologic outcomes of lobar resection (LR), sublobar resection (SR), and stereotactic body radiotherapy (SBRT).

METHODS

A systematic review and meta-analysis of oncologic outcomes of propensity matched comparative and noncomparative cohort studies was performed. Outcomes of interest were overall survival and disease-free survival. The inverse variance method and the random-effects method for meta-analysis were utilized to assess the pooled estimates.

RESULTS

A total of 100 studies with patients treated for clinical stage I non-small-cell lung carcinoma were included. Long-term overall and disease-free survival after LR was superior over SBRT in all comparisons, and for most comparisons, SR was superior to SBRT. Noncomparative studies showed superior long-term overall and disease-free survival for both LR and SR over SBRT. Although the papers were heterogeneous and of low quality, results remained essentially the same throughout a large number of stratifications and sensitivity analyses.

CONCLUSION

Results of this systematic review and meta-analysis showed that LR has superior outcomes compared to SBRT for cI non-small-cell lung carcinoma. New trials are underway evaluating long-term results of SBRT in potentially operable patients.

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.

[Correlation between Lymph Node Ratio and Clinicopathological Features and Prognosis of IIIa-N2 Non-small Cell Lung Cancer]

BACKGROUND

IIIa-N2 non-small cell lung cancer was significant different in survival, although N stage of lung cancer based on anatomic location of metastasis lymph node. Lymph node ratio considered of prognostic factor might be the evaluation index for IIIa-N2 non-small cell lung cancer prognosis. Therefore, the aim of the study was to evaluate the correlation between lymph node ratio and clinicopathological features and prognosis of IIIa-N2 non-small cell lung cancer prognosis.

METHODS

A total of 288 cases of pathological IIIa-N2 non-small cell lung cancer were enrolled who received radical resection at the Department of Thoracic Surgery II, Peking University Cancer Hospital from January 2006 to December 2016. The univariate analysis between clinicopathological variables and lymph node ratio used Pearson's chi-squared test. Cox regression was conducted to identify the independent prognosis factors for IIIa-N2 non-small cell lung cancer.

RESULTS

There were 139 cases in the lower lymph node ratio group, another 149 cases in the higher lymph node ratio group. Adenocarcinoma (χ²=5.924, P=0.015), highest mediastinal lymph node metastasis (χ²=46.136, P<0.001), multiple-number N2 metastasis (χ²=59.347, P<0.001), multiple-station N2 metastasis (χ²=77.387, P<0.001) and skip N2 lymph node metastasis (χ²=61.524, P<0.001) significantly impacted lymph node ratio. The total number of lymph node dissection was not correlated with the lymph node ratio (χ²=0.537, P=0.464). Cox regression analysis confirmed that adenocarcinoma (P=0.008), multiple-number N2 metastasis (P=0.025) and lymph node ratio (P=0.001) were the independent prognosis factors of disease free survival. The 5-year disease free survival was 18.1% in the higher lymph node ratio group, and 44.1% in the lower. Lymph node ratio was the independent prognosis factor of overall survival (P<0.001). The 5-year overall survival was 36.7% in the higher lymph node ratio group, and 64.1% in the lower.

CONCLUSIONS

Lymph node ratio was correlative with the pathology, highest mediastinal lymph node metastasis, multiple-number N2 metastasis, multiple-station N2 metastasis and skip N2 lymph node metastasis. Lymph node ratio was the independent prognosis factor for IIIa-N2 non-small cell lung cancer.

The prognostic significance of the lymph node ratio in oral cancer differs for anatomical subsites

The aim of this study was to validate the prognostic significance of the lymph node ratio (LNR) in patients suffering from oral squamous cell carcinoma in regard to different anatomical subsites. A cohort of 430 patients was investigated to determine the rates of primary metastasis and local and regional disease recurrence. Correlation analysis of the LNR with relevant clinical and pathological parameters was performed. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the prognostic impact for different subsites. Significantly differing rates of primary metastasis and loco-regional disease recurrence were found for cancer of different anatomical subsites of the head and neck. Furthermore, ROC curve analysis suggested that LNR has prognostic relevance in subsets of cancer (tongue, P< 0.001; alveolar process, P= 0.04; maxilla, P= 0.03; buccal mucosa, P= 0.02). The LNR of cancer located in the soft palate (P= 0.6) and floor of the mouth (P= 0.11) showed little or no association with the clinical outcome. There is the need for a more sensitive consideration of the LNR as a factor in the assessment of risk and the treatment decision, as the anatomical subsite plays a crucial role in its impact on the clinical outcome.

The Prognostic Value Of Lymph Node Ratio In Patients With N2 Stage Lung Squamous Cell Carcinoma: A Nomogram And Heat Map Approach

Background

Lymph node ratio (LNR), defined as the ratio of the number of positive lymph nodes to the total of all resected nodes, has been reported to be a predictor of survival of patients with several types of cancer. However, the prognostic value of LNR and other factors in patients with resected N2 stage lung squamous cell carcinoma has never been considered.

Methods

Data from 1778 patients with resected N2 stage lung squamous cell carcinoma were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The optimal cutoff value of LNR was identified by X-tile. A multivariable Cox model and corresponding nomogram were constructed to predict overall survival (OS) and cancer-specific survival (CSS). Both the cutoff value of LNR and the model were further validated in 146 similar patients treated in Zhongshan Hospital. Heat maps were created to visualize the distribution of LNR and the number of positive lymph nodes with the predicted survival probabilities.

Results

The optimal cutoff value for LNR was identified as 0.42. Multivariable analysis showed that age, sex, tumor laterality, type of surgery, T stage, chemotherapy and LNR were independently correlated with OS. Harrell’s C-index of the nomogram (0.64) was significantly higher than the index of the T stage-based model (0.54). Calibration curves showed good agreement between predicted and observed survival probabilities. The robustness of the model was also demonstrated by external validation.

Conclusion

LNR less than 0.42 was associated with improved OS and CSS for patients with resected N2 stage lung squamous cell carcinoma.

A prognostic score system with lymph node ratio in stage IIIA-N2 NSCLC patients after surgery and adjuvant chemotherapy

PURPOSE

The survival of patients with IIIA-N2 non-small cell lung cancer after surgery followed by adjuvant chemotherapy is heterogeneous. The aim of this study is to form a prognostic system and a heat map method to visualize the overall survival rates in those patients.

METHODS

Univariate and multivariate Cox hazards regression models and the associated Wald Chi square coefficient were used to form the prognostic score system. Recursive partitioning analysis was used to determine the cutoff values of lymph node ratio and prognostic score in SEER cohort and validated in FDUSCC cohort. Meanwhile, a heat map method was used to visualize the overall survival probabilities of 3, 5 and 10 years for individual patient of both cohorts.

RESULTS

Lymph node ratio (with cutoff of 0.36) significantly correlates with overall survival of these patients. In addition, in patients with the same level of N2 disease, lymph node ratio still significantly affects survival. Also, after the multivariate analysis in SEER cohort, six factors were independent prognostic factors including age, sex, type of surgery, size, lymph node ratio and differentiation. A prognostic sore system with these factors (with cutoff of 12) was validated as a predictor for overall survival in FDUSCC cohort.

CONCLUSIONS

This prognostic score system including lymph node ratio can predict the survival rates of IIIA-N2 patient after surgery and post-operative chemotherapy. Lymph node ratio could be a useful supplementation in TNM stage classification for IIIA-N2 patients. The heat map method can visualize the predicted overall survival of an individual patient.

Feasibility of nodal classification for non-small cell lung cancer by merging current N categories with the number of involved lymph node stations

Introduction

The aim of this study was to assess the prognoses of patients with non‐small cell lung cancer (NSCLC) according to the current nodal (N) categories of the tumor, node and metastasis (TNM) classification and the number of involved lymph node stations.

Methods

Five hundred and seventy patients with NSCLC underwent surgery from 1 January 2005 to 31 December 2009 and were analysed retrospectively. Postoperative overall survival was analysed according to two nodal classifications: the current N0, N1, N2 and N3 categories and those based on the number of involved nodal stations: N0, N1a (single N1), N1b (multiple N1), N2a1 (single N2 without N1), N2a2 (single N2 with N1), N2b1 (multiple N2 without N1) and N2b2 (multiple N2 with N1).

Results

Five‐year survival rates were 76.1%, 53.4% and 26.3% for N0, N1 and N2, respectively (P < 0.001). When survival was analysed by the number of involved nodal stations, the groups with significant differences were maintained; otherwise, they were merged, and new codes were assigned as follows for exploratory analyses: NA (N0), NB (N1a), NC (N1b, N2a (i.e., N2a1 and N2a2) and N2b1) and ND (N2b2). Five‐year survival rates were 76.1%, 60.0%, 39.1%, and 11.4% for NA, NB, NC and ND, respectively, and there were significant differences among them. This N classification was an independent prognostic factor in multivariate analyses.

Conclusion

Pending prospective and international validation, it is practical to merge the current N categories with the number of involved lymph node stations when evaluating the postoperative prognosis of NSCLC patients.

Log Odds Could Better Predict Survival in Muscle-Invasive Bladder Cancer Patients Compared with pN and Lymph Node Ratio

Background: The aim of this study was to assess the prognostic value of lymph node-associated variables, pN, lymph node ratio (LNR) and log odds (LODDS), in patients with bladder cancer.

Methods: In the discovery cohort, 3358 patients with muscle-invasive bladder cancer (MIBC) and treated with radical cystectomy were identified from the Surveillance, Epidemiology, and End Results (SEER) database. A total of 173 patients with MIBC who underwent radical cystectomy at Shanghai Cancer Center between 2010 and 2013 were enrolled in the validation cohort. LNR and LODDS were calculated in two cohorts and prognostic value was compared between these two variables.

Results: In the two cohorts, survival differences between LODDS, LNR and pN (from the 7^th AJCC TNM system) cohorts were statistically significant. Univariate and multivariate analyses confirmed that LNR and LODDS were independent prognostic factors and LODDS was better at predicting prognosis than pN and LNR for patients with MIBC. Moreover, LODDS had a better discriminative ability and model fit, proven by the highest Harrell's concordance index and lowest AIC among the three variables. Furthermore, scatter plots of pN, LNR and LODDS revealed that several groups of LNR and pN were heterogeneous and could be better stratified by LODDS in terms of prognosis estimation.

Conclusion: LODDS has significant prognostic value for patients with MIBC. Moreover, LODDS is better at predicting prognosis for MIBC patients compared with pN and LNR.

A prognostic model based on lymph node metastatic ratio for predicting survival outcome in gastric cancer patients with N3b subclassification

BACKGROUND

Determining the survival outcome for gastric cancer patients with metastases to more than 15 regional lymph nodes is difficult. This study aims to develop a lymph node metastatic ratio (LNR)-based prognostic model to predict the survival outcome after D2 surgery in such patient groups.

METHODS

Our study retrospectively enrolled 139 gastric cancer patients with metastases to more than 15 regional lymph nodes who underwent D2 surgery between 2007 and 2014. Clinicopathologic variables to predict overall survival (OS) using multivariate Cox regression were selected to create a prognostic model.

RESULTS

The prognostic model for predicting OS was developed based on five independent factors, namely, T-classification (T2 or T3 vs. T4), LNR (<0.80 vs. ≥0.80), carcinoembryonic antigen level (<5 vs. ≥5 ng/ml), Eastern Cooperative Oncology Group performance scale (scale 0-1 vs. ≥2), and adjuvant chemotherapy (yes vs. no). Using the prognostic score, patients were stratified into good, intermediate, and poor prognostic groups. The median OS in the good, intermediate, and poor prognostic risk groups was 32.0 months (95% confidence interval [CI]: 22.3-41.7), 12.4 months (95% CI: 8.5-16.3), and 5.4 months (95% CI: 2.1-8.7), respectively. The c-index of the prognostic model was 0.79 (95% CI: 0.71-0.87).

CONCLUSION

This study developed an accurate LNR-based prognostic model for predicting the survival outcome after D2 surgery in gastric cancer patients with metastasis to more than 15 regional lymph nodes. This model might assist clinicians in prognostic stratification of such patients and convince eligible patients to receive adjuvant chemotherapy.

Nomogram and recursive partitioning analysis to predict overall survival in patients with stage IIB-III thoracic esophageal squamous cell carcinoma after esophagectomy

We have developed statistical models for predicting survival in patients with stage IIB-III thoracic esophageal squamous cell carcinoma (ESCC) and assessing the efficacy of adjuvant treatment. From a retrospective review of 3,636 patients, we created a database of 1,004 patients with stage IIB-III thoracic ESCC who underwent esophagectomy with or without postoperative radiation. Using a multivariate Cox regression model, we assessed the prognostic impact of clinical and histological factors on overall survival (OS). Logistic analysis was performed to identify factors to include in a recursive partitioning analysis (RPA) to predict 5-year OS. The nomogram was evaluated internally based on the concordance index (C-index) and a calibration plot. The median survival time in the training dataset was 30.9 months, and the 5-year survival rate was 33.9%. T stage, differentiated grade, adjuvant treatment, tumor location, lymph node metastatic ratio (LNMR), and the presence of vascular carcinomatous thrombi were statistically significant predictors of 5-year OS. The C-index of the nomogram was 0.70 (95% CI 0.67-0.73). RPA resulted in a three-class stratification: class 1, LNMR ≤ 0.15 with adjuvant treatment; class 2, LNMR ≤ 0.15 without adjuvant treatment and LNMR > 0.15 with adjuvant treatment; and class 3, LNMR > 0.15 without adjuvant treatment. The three classes were statistically significant for OS (P < 0.001). Thus, the nomogram and RPA models predicted the prognosis of stage IIB-III ESCC patients and could be used in decision-making and clinical trials.

A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery

OBJECTIVE

Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction.

METHODS

A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center.

RESULTS

A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores.

CONCLUSIONS

This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making.

Prognostic value of number of negative lymph node in patients with stage II and IIIa non-small cell lung cancer

Background

The definitive validation evidence of the implications of lymph node metastases regarding the survival of Non-Small Cell Lung Cancer (NSCLC) patients is lacking. We aimed to evaluate the prognostic impact of several lymph node metastases-associated risk factors including Number of Negative Lymph Node (NLN) and risk-stratify NSCLC patients into subsets with different prognosis.

Method

A total of 482 patients with N1 and N2 NSCLC were included in this study. The prognostic importance of a set of risk factors was examined by univariate and multivariate analysis. The cut-off points and 5 years survival rates were calculated to test the best grouping system to stratify the patients with difference outcome.

Results

Our analysis indicated that both Ratio of the Metastatic Lymph nodes (RML) and Number of Negative Lymph Node (NLN) were associated with overall survival (OS) and disease free survival (DFS). RML percentage 20% and 55%, and NLN counts 10 and 30 were proved as the optimal cut-off points to predict OS by classifying patients into 3 groups, respectively. RML and NLN actually are more powerful in predicting survival outcome for male patients compared to female patients. Stratified survival analyses using combined factors indicated that the 5-year survival rate (5-YSR) is high in RML I + NLN I/III subgroup (5-YSR = 57.1% and 43.3%) and low in RML III + NLN II/III subgroup (5-YSR = 0.0 % each).

Conclusions

NLN is a strong prognostic factor for OS and DFS of stage II/IIIa NSCLC patients, and provides a useful classification scheme for NSCLC patients when combined with RML.

Lymph node ratio is a prognostic factor for non-small cell lung cancer

The lymph node ratio (LNR) is defined as the number of pathologically positive LNs divided by the number of LNs examined. Some studies reported that high LNR was significantly associated with poor survival of non-small cell lung cancer (NSCLC). However, other studies could not confirm this result. PubMed, Embase, and the Cochrane Register of Controlled Trials were searched for relevant studies published up to July 2015. Primary outcome was the relationship between LNR and disease-specific survival (DSS) and overall survival (OS). Twelve studies with 25138 NSCLC patients were included in this meta-analysis. Higher LNR was significantly associated with decreased OS (HR = 1.93; 95% CI 1.64 – 2.28; P < 0.00001) and DSS (HR = 1.82; 95% CI 1.55 – 2.14; P < 0.00001). In the subgroup analysis, N1 stage NSCLC patients with higher LNR also showed decreased OS (HR = 1.60; 95% CI 1.25 – 2.28; P = 0.0002) and DSS (HR = 1.82; 95% CI 1.55 – 2.21; P < 0.0001). This meta-analysis indicated that LNR was an independent predictor of survival in patients with NSCLC.

Improving the pathologic evaluation of lung cancer resection specimens

Accurate post-operative prognostication and management heavily depend on pathologic nodal stage. Patients with nodal metastasis benefit from post-operative adjuvant chemotherapy, those with mediastinal nodal involvement may also benefit from adjuvant radiation therapy. However, the quality of pathologic nodal staging varies significantly, with major survival implications in large populations of patients. We describe the quality gap in pathologic nodal staging, and provide evidence of its potential reversibility by targeted corrective interventions. One intervention, designed to improve the surgical lymphadenectomy, specimen labeling, and secure transfer between the operating theatre and the pathology laboratory, involves use of pre-labeled specimen collection kits. Another intervention involves application of an improved method of gross dissection of lung resection specimens, to reduce the inadvertent loss of intrapulmonary lymph nodes to histologic examination for metastasis. These corrective interventions are the subject of a regional dissemination and implementation project in diverse healthcare systems in a tri-state region of the United States with some of the highest lung cancer incidence and mortality rates. We discuss the potential of these interventions to significantly improve the accuracy of pathologic nodal staging, risk stratification, and the quality of specimens available for development of stage-independent prognostic markers in lung cancer.

The impact of positive nodal chain ratio on individualized multimodality therapy in non-small-cell lung cancer

This study aimed to analyze the prognostic significance of the positive nodal chain ratio (NCR) in non-small-cell lung cancer (NSCLC). A total of 208 pIIIa-N2 NSCLC patients who underwent complete surgical resections with a systematic nodal dissection were enrolled. The median values of NCR and the positive lymph node ratio (LNR) were used to grouping patients. The differences of overall survival (OS) and disease-free survival (DFS) between the different groups were compared. The median values of NCR and LNR were 0.31 and 0.45, respectively. The patients were separated into group A (NCR ≤0.45 and LNR ≤0.31; 91 cases), group B (NCR ≤0.45 and LNR >0.31 or NCR >0.45 and LNR ≤0.31; 51 cases), and group C (NCR >0.45 and LNR >0.31; 66 cases) according to their combined LCR and LNR values. Groups A, B, and C exhibited significantly different prognoses (5-year OS: 43.7, 25.2, and 12.3 %, respectively, p < 0.0001; 5-year DFS: 30.4, 23.3, and 8.6 %, respectively, p < 0.0001). Multivariate analyses revealed that this novel grouping method based on the combination of NCR and LNR was an independent prognostic factor for 5-year OS and 5-year DFS in pIIIa-N2 NSCLC. In group C, patients who received no postoperative treatment, adjuvant chemotherapy alone, or chemoradiotherapy exhibited different 5-year OS rates (0.0, 11.6, and 37.5 %, respectively, p = 0.003) and 5-year DFS rates (0.0, 7.5, and 25.0 %, respectively, p = 0.009). Therefore, postoperative chemoradiotherapy may significantly improve the prognosis of patients displaying NCR >0.45 and LNR >0.31. NCR combined with LNR may be more effective to guide individualized multimodality therapy including postoperative chemoradiotherapy for pIIIa-N2 NSCLC.

Prognostic value of lymph node ratio in patients with advanced epithelial ovarian cancer

OBJECTIVE

Lymph node status is an established prognostic factor in epithelial ovarian cancer (EOC). Lymph node ratio (number of positive LN/number of resected LN) reflects both qualitative and quantitative lymph node spread as well as surgical effort and extent of disease. We evaluated whether LNR is a more precise prognostic factor than conventional lymph node status in patients with EOC.

METHODS

The present retrospective study includes 809 patients with EOC, who underwent primary cytoreductive surgery between 2000-2013. Clinico-pathological parameters and survival data were extracted from a prospectively maintained tumor registry database. The optimal cut-off point for LNR was calculated by using Martingale residuals. Survival analyses were calculated using Kaplan-Meier method and Cox regression models.

RESULTS

Lymphadenectomy was performed in 693 (85.7%) out of 809 patients. Median number of removed LN was 64 (IQR 25-75%: 39-84). LNR of 0.25 was identified as the optimal prognostic cut-off value. The estimated 5-year-OS rates were 69.3% for patients with node-negative EOC compared to 33.1% for patients with any lymph node metastasis (p<0.001). The estimated 5-year-OS rates were 42.5% for patients with LNR≤0.25, and 18.0% for patients with LNR>0.25 (p<0.001). Additionally in multivariate analysis LNR>0.25 was approved to be an independent prognostic factor for overall survival (adjusted HR 1.44, 95% CI 1.04-2.00; p=0.028).

CONCLUSION

LNR more precisely predicts overall survival than conventional lymph node status in EOC patients undergoing primary debulking surgery.

Prognostic value of metastatic N1 lymph node ratio and angiolymphatic invasion in patients with pathologic stage IIA non-small cell lung cancer

With regard to pathologic stage IIA (pIIA) non-small cell lung cancer (NSCLC), there is a paucity of literature evaluating the risk factors for disease-free survival (DFS) and overall survival (OS). The aim of this study was to identify the prognostic factors of DFS and OS in patients with NSCLC pIIA.We performed a retrospective review of 98 stage II patients (7th edition of the American Joint Committee on Cancer) who underwent lung resection from January 2005 to February 2011. Of these, 23 patients were excluded for this study because of loss of follow-up or different substage, and 75 patients with pIIA were included for further univariate and multivariate analysis. Risk factors for DFS and OS were analyzed, including age, gender, smoking history, operation method, histology, differential grade, visceral pleural invasion, angiolymphatic invasion, and metastatic N1 lymph node ratio (LNR).Of the 75 patients with pIIA NSCLC who were examined, 29 were female and 46 were male, with a mean age of 61.8 years (range: 34-83 years). The average tumor size was 3.188 cm (range: 1.10-6.0 cm). Under univariate analysis, angiolymphatic invasion and metastatic N1 LNR were risk factors for DFS (P = 0.011, P = 0.007). Under multivariate analysis, angiolymphatic invasion and metastatic N1 LNR were all independent risk factors for DFS, while adjuvant chemotherapy and higher metastatic N1 LNR were independent prognostic factors for OS.For patients with pIIA, higher metastatic N1 LNR and angiolymphatic invasion were related to poor DFS. In addition to DFS, higher metastatic N1 LNR was also a poor prognostic factor for OS rates and adjuvant therapy effectiveness. Clinical physicians should devise different postsurgical follow-up programs depending on these factors, especially for patients with high risk.