Revolutionizing T3-4N0-2M0 gastric cancer staging with an innovative pathologic N classification system.

BACKGROUND: The current pathologic N (pN) classification exhibits limitations in the prognostic stratification of patients with pT3-4N0-2M0 gastric cancer (GC). Therefore, this study aimed to develop and validate a new lymph nodal staging method based on the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). METHODS: Data from 7883 patients with pT3-4N0-2M0 GC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and Zhejiang Cancer Provincial Hospital. Optimal cutoff values for ELNs and LNR were determined using X-tile software. Kaplan-Meier methods, Log-rank tests, and Cox regression analyses were employed in this study. Patients were categorized into 3 new pN stages: new pN0 (pN0 with ELNs of >16), new pN1 (pN0 with ELNs of ≤16 or pN1-2 with LNR of ≤0.15), and new pN2 (pN1-2 with LNR of >0.15). The prognostic predictive power of both current and new pN staging was evaluated using the Akaike information criterion (AIC), Bayesian information criterion, concordance index (C-index), and receiver operating characteristic curve. RESULTS: The new pN classification exhibited excellent performance in Kaplan-Meier survival analysis. After adjusting for confounding factors, the new pN staging emerged as an independent prognostic indicator in patients with GC. In the SEER cohort, the new pN staging demonstrated enhanced prognostic prediction accuracy over the American Joint Committee on Cancer pN staging (AIC: 75578.85 vs 75755.06; C-index: 0.642 vs 0.630; P < .001). Similar findings were validated in the Chinese cohort. CONCLUSION: This study developed and validated an improved pN classification for patients with pT3-4N0-2M0 GC. Surgeons should consider ELNs and LNR when assessing postoperative prognosis in patients with GC.

Prognostic value of nodal staging classification and number of examined lymph nodes among patients with ampullary cancer.

BACKGROUND: Metastatic disease in the regional lymph nodes (LNs) is a strong indicator of worse outcomes among patients after curative-intent resection of ampullary cancer (AC). This study aimed to ascertain the threshold number of examined LNs (ELNs) for AC to compare the prognosis accuracy of various nodal classification schemes relative to long-term prognosis. METHODS: Patients who underwent pancreatoduodenectomy (PD) for AC (2004-2019) were identified using the National Cancer Database. Locally weighted regression scatter plot smoothing (LOWESS) curves were used to ascertain the optimal cut point for ELNs. The accuracy of the American Joint Committee on Cancer N classification, LN ratio, and log odds transformation (LODDS) ratio to stratify patients relative to survival was examined. RESULTS: Among 8127 patients with AC, 67% were male with a median age of 67 years (IQR, 59-74). Tumors were most frequently classified as T3 (34.9%), followed by T2 (30.6%); T1 (12.9%) and T4 (17.6%) were less common. LN metastasis was identified in 4606 patients (56.7%). Among patients with nodal disease, 37.0% and 19.7% had N1 and N2 disease, respectively. The LOWESS curves identified an inflection cutoff point in the hazard of survival at 20 ELNs. The survival benefit of 20 ELNs was more pronounced among patients without LN metastasis vs patients with N1 disease (median overall survival [OS]: 54.1 months [IQR, 45.9-62.1] in ≥20 ELNs vs 39.0 months [IQR, 35.8-42.2] in <20 ELNs; P < .001) or N2 disease (median OS: 22.5 months [IQR, 18.9-26.2] in ≥20 ELNs vs 25.4 months [IQR, 23.3-27.6] in <20 ELNs; P < .001). When comparing the 4 different N classification schemes, the LODDS classification scheme yielded the highest predictive ability. CONCLUSIONS: Evaluation of a minimum of 20 LNs was needed to stratify patients with AC relative to the prognosis and to minimize stage migration. The LODDS nodal classification scheme had the highest prognostic accuracy to differentiate survival among patients after PD for AC.

Effect of examining lymph nodes count on mortality risk in resected T1 non-small-cell lung cancer.

OBJECTIVES: This study aims to estimate the effect of the examined lymph node count (ELNC) on the cancer-related mortality risk and non-cancer-related mortality risk in patients with resected T1 non-small-cell lung cancer (NSCLC). METHODS: Patients diagnosed as primary T1 NSCLC between 2000 and 2017 were extracted from the Surveillance, Epidemiology and End Results database. Patients were divided into 2 groups according to the ELNC cutoff value, which was calculated based on overall survival outcomes. Propensity score matching was used to equalize the differences in baseline characteristics between groups. RESULTS: A total of 38 242 resected T1 NSCLC patients were extracted from the database with the ELNC cutoff value of 8. After propensity score matching, 27 676 patients were included in this study. Examining ≥8 ELNC was associated with a more accurate assessment of lymph node (LN) metastasis and significantly improving the prognosis. These trends remained consistent in subgroup analysis by histology type. In competing risk mode, examining ≥8 LNs could significantly reduce the risk of death from lung cancer, risk of death from chronic obstructive pulmonary disease, and risk of death from cardiac diseases. In the subgroup analysis, these trends were consistent. CONCLUSIONS: Given the mortality risk associated with lung cancer, chronic obstructive pulmonary disease, and cardiac diseases, at least 8 LNs should be examined in surgery for T1 NSCLC.

The minimum number of examined lymph nodes was 24 for optimal survival of pathological T2-4 gastric cancer: a multi-center, hospital-based study covering 20 years of data.

INTRODUCTION: The current National Comprehensive Cancer Network (NCCN) guidelines recommend that at least 16 lymph nodes should be examined for gastric cancer patients to reduce staging migration. However, there is still debate regarding the optimal management of examined lymph nodes (ELNs) for gastric cancer patients. In this study, we aimed to develop and test the minimum number of ELNs that should be retrieved during gastrectomy for optimal survival in patients with gastric cancer. METHODS: We used the restricted cubic spline (RCS) to identify the optimal threshold of ELNs that should be retrieved during gastrectomy based on the China National Cancer Center Gastric Cancer (NCCGC) database. Northwest cohort, which sourced from the highest gastric cancer incidence areas in China, was used to verify the optimal cutoff value. Survival analysis was performed via Kaplan-Meier estimates and Cox proportional hazards models. RESULTS: In this study, 12,670 gastrectomy patients were included in the NCCGC cohort and 4941 patients in the Northwest cohort. During 1999-2019, the average number of ELNs increased from 17.88 to 34.45 nodes in the NCCGC cohort, while the number of positive lymph nodes remained stable (5-6 nodes). The RCS model showed a U-curved association between ELNs and the risk of all-cause mortality, and the optimal threshold of ELNs was 24 [Hazard ratio (HR) = 1.00]. The ELN ≥ 24 group had a better overall survival (OS) than the ELN < 24 group clearly (P = 0.003), however, with respect to the threshold of 16 ELNs, there was no significantly difference between the two groups (P = 0.101). In the multivariate analysis, ELN ≥ 24 group was associated with improved survival outcomes in total gastrectomy patients [HR = 0.787, 95% confidence interval (CI): 0.711-0.870, P < 0.001], as well as the subgroup analysis of T2 patients (HR = 0.621, 95%CI: 0.399-0.966, P = 0.035), T3 patients (HR = 0.787, 95%CI: 0.659-0.940, P = 0.008) and T4 patients (HR = 0.775, 95%CI: 0.675-0.888, P < 0.001). CONCLUSION: In conclusion, the minimum number of ELNs for optimal survival of gastric cancer with pathological T2-4 was 24.

The minimal number of examined lymph nodes for accurate nodal staging and favorable prognosis in T1-2 supraglottic laryngeal squamous cell carcinoma.

OBJECTIVE: The study aimed to investigate the minimal number of examined lymph nodes (ELNs) for accurate assessment of lymph node status and favorable prognosis in patients with stage T1-2 supraglottic laryngeal squamous cell carcinoma (LSCC) who received radical resection. METHODS: Patients with stage T1-2 supraglottic LSCC from the Surveillance, Epidemiology, and End Results (SEER) database and the Chinese Academy of Medical Sciences, Cancer Hospital/National Cancer Center (NCC) were reviewed. The association of the ELN count with the identification of nodal metastasis and overall survival (OS) was analyzed using a multivariate regression model. Locally weighted scatterplot smoothing fitting curve and the 'changepoint' package were adopted to identify the optimal cut points using R. RESULTS: A total of 429 patients from the SEER database and 53 patients from NCC were enrolled. The probability of identifying nodal metastasis was positively related to the ELN count. For patients diagnosed with pathological stage N0 (pN0) disease, the mortality risks rapidly decreased when the amount of ELNs exceeded ten, and those with ELNs >10 had better OS. CONCLUSION: An adequate amount of ELNs benefits precise nodal staging in patients with stage T1-2 supraglottic LSCC. Ten lymph nodes are the minimum number of ELNs. For pN0 patients, an ELN count ≤10 is an unfavorable prognostic factor.

A Nomogram Based on the Log Odds of Positive Lymph Nodes Predicts the Prognosis of Patients with Colon Neuroendocrine Tumors After Surgery: A Surveillance, Epidemiology, and End Results Population-Based Study.

PURPOSE: This work focused on determining the highly efficient nodal classification system from American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) classification (eighth edition), positive lymph node, log odds of positive lymph nodes (LODDS), lymph node ratio, examined lymph node, and establishing the new nomogram for predicting cancer-specific survival in colon neuroendocrine tumors (CNETs). METHODS: From the Surveillance, Epidemiology, and End Results database, 943 CNET cases undergoing radical operation were enrolled, and randomized as training (n = 663) or validation set (n = 280). For the above 5 lymph node classification systems, their prediction performances were compared with C-index, Akaike information criterion (AIC), and area under the receiver operating characteristic curve. Univariate together with multivariate regression was carried out for identifying independent risk factors. Afterward, this work established 1 nomogram and confirmed its accuracy based on C-index, calibration curves, together with the area under the curve value. Besides, it was compared with the AJCC TNM classification system with regard to model prediction performance. RESULTS: LODSS achieved the greatest area under the curve and C-index, whereas the smallest AIC. Upon multivariate regression, age, histologic grade, T stage, M stage, and LODDS independently predicted the risk of CNETs. For the validation set, the C-index of the nomogram was 0.794, and the area under the curves at 1, 3, and 5 years was 0.826, 0.857, and 0.870, separately. Additionally, as revealed by the C-index, AIC, decision curve analysis, as well as Kaplan-Meier analysis, our nomogram had superior performance to the AJCC TNM classification system. CONCLUSIONS: For postoperative patients with CNETs, the LODDS might achieve the best prediction performance. Moreover, the LODDS-based nomograms might show superior survival prediction performance to the AJCC TNM classification system (eighth edition).

The optimal number of examined lymph nodes for accurate staging of intrahepatic cholangiocarcinoma: A multi-institutional analysis using the nodal staging score model.

BACKGROUND: This study aims to develop a nodal staging score (NSS) to determine the optimal number of lymph nodes (LNs) examined in intrahepatic cholangiocarcinoma (iCCA) patients. METHODS: Clinicopathologic data were collected from the SEER database (development cohort, n = 2782) and seven Chinese tertiary hospitals (validation cohort, n = 363). NSS was constructed based on a binomial distribution to indicate the probability of nodal disease absence. In addition, its prognostic value was examined by survival analysis and multivariable modeling on pN0 patients. RESULTS: A model fit was performed in node-positive patients and a subgroup analysis was performed according to clinical characteristics. Statistically significant differences were only found in the subgroups when divided by the tumor size of 3 cm. As the number of examined lymph nodes (ELNs) increased, the likelihood of missing a metastatic LN decreased. NSS escalated as ELNs increased in groups with different tumor sizes, with plateaus at 7 and 11 LNs ensuring an NSS of 90.0% for ≤3 cm and >3 cm tumors, respectively. For pN0 patients, multivariate analysis revealed that NSS was an independent prognostic factor for overall survival (OS) and recurrence-free survival (RFS). CONCLUSIONS: For accurate staging of iCCA, the optimal number of ELNs was related to tumor size. We recommend that at least 7 and 11 LNs should be examined for tumor size ≤3 cm and >3 cm, respectively. Therefore, the NSS model could be helpful to make clinical decisions for pN0 iCCA.

The optimal number of examined lymph nodes for accurate nodal staging and favorable prognosis of oral tongue squamous cell carcinoma.

OBJECTIVE: The study aimed to determine the optimal count of examined lymph nodes (ELN) for accurate assessment of lymph node status and favorable long-term survival in patients with oral tongue squamous cell carcinoma (OTSCC) who received radical resection. METHODS: Patients with OTSCC who received radical resection between 2004 and 2015 were enrolled from the Surveillance, Epidemiology, and End Results database (SEER) and were randomly divided into two cohorts. The association of ELN count with nodal migration and overall survival (OS) was analyzed using a multivariate regression model with the adjustment of relevant factors. Locally weighted scatterplot smoothing (LOWESS) and 'strucchange' package were adopted to identify the optimal cut points using R. RESULTS: A total of 2077 patients were included in this study. The optimal cut points of ELN count for accurate nodal staging and favorable OS were 19 and 15, respectively. The probability of detecting positive lymph nodes (PLN) significantly increased in patients with ELN count ≥ 19 in comparison to those with ELN count < 19 (training set, P < 0.001; validation set, P = 0.012). A better postoperative prognosis was observed in patients with ELN count ≥ 15 than those with fewer ELN (training set, P = 0.001, OR: 0.765; validation set, P = 0.016, OR: 0.678). CONCLUSION: The optimal cut point of ELN count to ensure the accuracy of nodal staging and to achieve a favorable postoperative prognosis were 19 and 15, respectively. The ELN count beyond the cutoff values might improve the accuracy of cancer staging and OS.

Survival Outcome of Gastric Signet Ring Cell Carcinoma Based on the Optimal Number of Examined Lymph Nodes: A Nomogram- and Machine-Learning-Based Approach.

The optimal number of examined lymph nodes (ELNs) for gastric signet ring cell carcinoma recommended by National Comprehensive Cancer Network guidelines remains unclear. This study aimed to determine the optimal number of ELNs and investigate its prognostic significance. In this study, we included 1723 patients diagnosed with gastric signet ring cell carcinoma in the Surveillance, Epidemiology, and End Results database. X-tile software was used to calculate the cutoff value of ELNs, and the optimal number of ELNs was found to be 32 for adequate nodal staging. In addition, we performed propensity score matching (PSM) analysis to compare the 1-, 3-, and 5-year survival rates; 1-, 3-, and 5-year survival rates for total examined lymph nodes (ELNs < 32 vs. ELNs ≥ 32) were 71.7% vs. 80.1% (p = 0.008), 41.8% vs. 51.2% (p = 0.009), and 27% vs. 30.2% (p = 0.032), respectively. Furthermore, a predictive model based on 32 ELNs was developed and displayed as a nomogram. The model showed good predictive ability performance, and machine learning validated the importance of the optimal number of ELNs in predicting prognosis.

Prognostic significance of examined lymph node count in older patients with stage T1N0M0 pulmonary carcinoid tumours: a population-based propensity score-matched analysis.

BACKGROUND: The optimal number of examined lymph nodes (ELNs) for older early-stage pulmonary carcinoid tumour (PC) patients is unknown. AIMS: To explore the prognostic effect of the ELN count in older patients with stage T1N0M0 PC resection. METHODS: Clinical data from the Surveillance, Epidemiology, and End Results database on stage T1N0M0 PC older patients (age ≥ 65 years) who underwent sublobar resection and lobectomy between 2000 and 2018 were retrospectively analysed for two ELNs-stratified (≥ 7 vs. < 7 ELNs) propensity score-matched (PSM) groups. Overall survival (OS) was calculated and compared with Kaplan-Meier analysis and log-rank test, respectively, and the independent prognostic factors were estimated using a Cox proportional hazard model. RESULTS: Among 1077 participants (median dissected LN 4; mean ELNs 6.19 ± 7.04), 393 (36.49%) in the ≥ 7 ELNs group had better 5- and 10-year OS than the < 7 ELNs group (before PSM: 5-year OS = 93.01 vs. 85.22%, 10-year OS = 72.38 vs. 58.99%, p < 0.001; after PSM: 5-year OS = 93.12 vs. 85.97%, 10-year OS = 75.25 vs. 60.03%, p = 0.001). Subgroup analysis stratified by histologic type and surgical method showed a similar survival trend. Age-stratified analysis showed that, compared with the < 7 ELNs group, the ≥ 7 ELNs group had better 5- and 10-year OS but only better 5-year OS in participants > 75 years. Compared with the < 7 ELNs group, subgroup analysis by tumour size showed superior OS with 1.1-3.0 cm tumours in the ≥ 7 ELNs group, but no significant intergroup difference with tumours < 1.0 cm. Multivariate Cox analysis showed ≥ 7 ELNs was associated with improved OS. CONCLUSION: Higher ELNs correlated with increased long-term survival in older early­stage PC patients, and a minimum of 7 ELNs are recommended for prognostication in these patients (especially those aged 65-75 years, with tumour size 1.1-3.0 cm).

Value of number of negative lymph nodes in predicting the prognosis of patients with esophageal cancer after neoadjuvant therapy and the construction of nomogram prodiction model / 中华消化外科杂志

Objective:To investigate the value of number of negative lymph nodes (NLNs) in predicting the prognosis of patients with esophageal cancer after neoadjuvant therapy and the construction of nomogram prodiction model.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 924 patients with esophageal cancer after neoadjuvant therapy uploaded to the Surveillance, Epidemiology, and End Results Database of the National Cancer Institute from 2004 to 2015 were collected. There were 1 624 males and 300 females, aged 63 (range, 23?85)years. All 1 924 patients were randomly divided into the training dataset of 1 348 cases and the validation dataset of 576 cases with a ratio of 7:3 based on random number method in the R software (3.6.2 version). The training dataset was used to constructed the nomogram predic-tion model, and the validation dataset was used to validate the performance of the nomogrram prediction model. The optimal cutoff values of number of NLNs and number of examined lymph nodes (ELNs) were 8, 14 and 10, 14, respectively, determined by the X-tile software (3.6.1 version), and then data of NLNs and ELNs were converted into classification variables. Observation indicators: (1) clinicopathological characteristics of patients in the training dataset and the validation dataset; (2) survival of patients in the training dataset and the validation dataset; (3) prognostic factors analysis of patients in the training dataset; (4) survival of patients in subgroup of the training dataset; (5) prognostic factors analysis in subgroup of the training dataset; (6) construction of nomogram prediction model and calibration curve. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to draw survival curve and Log-Rank test was used for survival analysis. The COX proportional hazard model was used for univariate and multivariate analyses. Based on the results of multivariate analysis, the nomogram prediction model was constructed. The prediction efficacy of nomogram prediction model was evaluated using the area under curve (AUC) of the receiver operating characteristic curve and the Harrell′s c index. Errors of the nomogram prediction model in predicting survival of patients for the training dataset and the validation dataset were evaluated using the calibration curve. Results:(1) Clinicopathological characteristics of patients in the training dataset and the validation dataset. There was no significant difference in clinicopatholo-gical characteristics between the 1 348 patients of the training dataset and the 576 patients of the validation dataset ( P>0.05). (2) Survival of patients in the training dataset and the validation dataset. All 1 924 patients were followed up for 50(range, 3?140)months, with 3-year and 5-year cumulative survival rate as 59.4% and 49.5%, respectively. The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the training dataset was 46.7%, 62.0% and 66.0%, respectively, and the 5-year cumulative survival rate was 38.1%, 52.1% and 59.7%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=33.70, P<0.05). The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the validation dataset was 51.1%, 54.9% and 71.2%, respectively, and the 5-year cumulative survival rate was 39.3%, 42.5% and 55.7%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=14.49, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the training dataset was 53.9%, 60.0% and 62.7%, respectively, and the 5-year cumulative survival rate was 44.7%, 49.1% and 56.9%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=9.88, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the validation dataset was 56.2%, 47.9% and 69.3%, respectively, and the 5-year cumula-tive survival rate was 44.9%, 38.4% and 51.9%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=9.30, P<0.05). (3) Prognostic factors analysis of patients in the training dataset. Results of multivariate analysis showed that gender, neoadjuvant pathological (yp) T staging, ypN staging (stage N1, stage N2, stage N3) and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=0.65, 1.44, 1.96, 2.41, 4.12, 0.69, 0.56, 95% confidence interval as 0.49?0.87, 1.17?1.78, 1.59?2.42, 1.84?3.14, 2.89?5.88, 0.56?0.86, 0.45?0.70, P<0.05). (4) Survival of patients in subgroup of the training dataset. Of the patients with NLNs in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 61.1%, 71.6% and 76.8%, respectively, and the 5-year cumulative survival rate was 50.7%, 59.9% and 70.1%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=12.66, P<0.05). Of the patients with positive lymph nodes in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 26.1%, 42.9% and 44.7%, respectively, and the 5-year cumulative survival rate was 20.0%, 36.5% and 39.3%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=20.39, P<0.05). (5) Prognostic factors analysis in subgroup of the training dataset. Results of multivariate analysis in patients with NLNs in the training dataset showed that gender, ypT staging and number of NLNs (>14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadju-vant therapy ( hazard ratio=0.67, 1.44, 0.56, 95% confidence interval as 0.47?0.96, 1.09?1.90, 0.41?0.77, P<0.05). Results of multi-variate analysis in patients with positive lymph nodes in the training dataset showed that race as others, histological grade as G2, ypN staging as stage N3 and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=2.73, 0.70, 2.08, 0.63, 0.59, 95% confidence interval as 1.43?5.21, 0.54?0.91, 1.44?3.02, 0.46?0.87, 0.44?0.78, P<0.05). (6) Construction of nomogram prediction model and calibration curve. Based on the multivariate analysis of prognosis in patients of the training dataset ,the nomogram prediction model for the prognosis of patients with esophageal cancer after neoadju-vant treatment was constructed based on the indicators of gender, ypT staging, ypN staging and number of NLNs. The AUC of nomogram prediction model in predicting the 3-, 5-year cumulative survival rate of patients in the training dataset and the validation dataset was 0.70, 0. 70 and 0.71, 0.71, respectively. The Harrell′s c index of nomogram prediction model of patients in the training dataset and the validation dataset was 0.66 and 0.63, respectively. Results of calibration curve showed that the predicted value of the nomogram prediction model of patients in the training dataset and the validation dataset was in good agreement with the actual observed value. Conclusion:The number of NLNs is an independent influencing factor for the prognosis of esophageal cancer patients after neoadjuvant therapy, and the nomogram prediction model based on number of NLNs can predict the prognosis of esophageal cancer patients after neoadjuvant therapy.

Lymph node ratio is a superior predictor in surgically treated early-onset pancreatic cancer.

Background: The prognostic performance of four lymph node classifications, the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and examined lymph nodes (ELN) in early-onset pancreatic cancer (EOPC) remains unclear. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was searched for patients with EOPC from 2004 to 2016. 1048 patients were randomly divided into training (n = 733) and validation sets (n = 315). The predictive abilities of the four lymph node staging systems were compared using the Akaike information criteria (AIC), receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was performed to identify independent risk factors. A nomogram based on lymph node classification with the strongest predictive ability was established. The nomogram's precision was verified by the C-index, calibration curves, and AUC. Kaplan-Meier analysis and log-rank tests were used to compare differences in survival at each stage of the nomogram. Results: Compared with the 8th N stage, LODDS, and ELN, LNR had the highest C-index and AUC and the lowest AIC. Multivariate analysis showed that N stage, LODDS, LNR were independent risk factors associated with cancer specific survival (CSS), but not ELN. In the training set, the AUC values for the 1-, 3-, and 5-year CSS of the nomogram were 0.663, 0.728, and 0.760, respectively and similar results were observed in the validation set. In addition, Kaplan-Meier survival analysis showed that the nomogram was also an important factor in the risk stratification of EOPC. Conclusion: We analyzed the predictive power of the four lymph node staging systems and found that LNR had the strongest predictive ability. Furthermore, the novel nomogram prognostic staging mode based on LNR was also an important factor in the risk stratification of EOPC.

A modified survival model for patients with esophageal squamous cell carcinoma based on lymph nodes: A study based on SEER database and external validation.

Background: The counts of examined lymph nodes (ELNs) in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) is a controversial issue. We conducted a retrospective study to develop an ELNs-based model to individualize ESCC prognosis. Methods: Patients with ESCC from the SEER database and our center were strictly screened. The optimal threshold value was determine by the X-tile software. A prognostic model for ESCC patients was developed and validated with R. The model's efficacy was evaluated by C-index, ROC curve, and decision curve analysis (DCA). Results: 3,629 cases and 286 cases were screened from the SEER database and our center, respectively. The optimal cut-off value of ELNs was 10. Based on this, we constructed a model with a favorable C-index (training group: 0.708; external group 1: 0.687; external group 2: 0.652). The model performance evaluated with ROC curve is still reliable among the groups. 1-year AUC for nomogram in three groups (i.e., 0.753, 0.761, and 0.686) were superior to that of the TNM stage (P < 0.05). Similarly, the 3-year AUC and the 5-year AUC results for the model were also higher than that of the 8th TNM stage. By contrast, DCA showed the benefit of this model was better in the same follow-up period. Conclusion: More than 10 ELNs are helpful to evaluate the survival of ESCC patients. Based on this, an improved model for predicting the prognosis of ESCC patients was proposed.

Number of Examined Lymph Nodes as a Risk Factor for Recurrence in pT1N+ or pT2-3N0 Gastric Cancer.

BACKGROUND/AIM: Japanese Gastric Cancer Treatment Guidelines do not recommend adjuvant chemotherapy after radical gastrectomy for pathological stage (p) T1N+ or pT2~3N0 gastric cancer. However, some patients experience disease recurrence. This study aimed to identify the risk factors for recurrence in pT1N+ or pT2-3N0 gastric cancer. PATIENTS AND METHODS: The study included 157 patients with diagnosed pT1N+ or pT2-3N0 gastric cancer who underwent radical gastrectomy at our institution between January 2001 and December 2020. Clinicopathological data and surgical data were obtained. Independent prognostic factors were analyzed using a Cox proportional hazards regression model. RESULTS: Thirteen patients (8.3%) experienced disease recurrence. Multivariate analysis revealed that the number of examined lymph nodes was an independent prognostic factor for recurrence-free survival (hazard ratio=10.90; 95% confidence interval=1.39-85.86; p=0.023). The group with ≤35 examined lymph nodes had significantly worse recurrence-free survival compared with the group with ≥36 examined lymph nodes (80.7% versus 98.7%; p=0.0005). CONCLUSION: The number of examined lymph nodes (≤35) was an independent risk factor for recurrence after radical gastrectomy with pT1N+ or pT2-3N0 gastric cancer.

The minimum number of examined lymph nodes for accurate nodal staging and optimal survival of stage T1-2 esophageal squamous cell carcinoma: A retrospective multicenter cohort with SEER database validation.

BACKGROUND: The extent of lymphadenectomy during esophagectomy remains controversial for patients with T1-2 ESCC. The aim of this study was to identify the minimum number of examined lymph node (ELN) for accurate nodal staging and overall survival (OS) of patients with T1-2 esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS: Patients with T1-2 ESCC from three institutes between January 2011 and December 2020 were retrospectively reviewed. The associations of ELN count with nodal migration and OS were evaluated using multivariable models, and visualized by using locally weighted scatterplot smoothing (LOWESS). Chow test was used to determine the structural breakpoints of ELN count. External validation in the SEER database was performed. RESULTS: In total, 1537 patients were included. Increased ELNs was associated with an increased likelihood of having positive nodal disease and incremental OS. The minimum numbers of ELNs for accurate nodal staging and optimal survival were 14 and 18 with validation in the SEER database (n = 519), respectively. The prognostic prediction ability of N stage was improved in the group with ≥14 ELNs compared with those with fewer ELNs (iAUC, 0.70 (95%CI 0.66-0.74) versus 0.61(95%CI 0.57-0.65)). The higher prognostic value was found for patients with ≥18 ELNs than those with <18 ELNs (iAUC, 0.78 (95%CI 0.74-0.82) versus 0.73 (95%CI 0.7-0.77)). CONCLUSION: The minimum numbers of ELNs for accurate nodal staging and optimal survival of stage T1-2 ESCC patients were 14 and 18, respectively.

Analysis of the risk factor of insufficient examined lymph nodes in stage II colon cancer from the perspective of stage migration: A retrospective study combined with external validation.

BACKGROUND: An insufficient examined lymph node (ELN) count is a high risk factor for recurrence in patients with stage II colon cancer (CC). This study aimed to explore this risk factor in relation to stage migration. METHODS: We screened 18,544 patients with stage II (pT3/4N0M0) and IIIB (pT3/4N1M0) CC diagnosed after radical resection from 2010 to 2015, using the National Cancer Institute Surveillance, Epidemiology, and End Results database. Propensity score matching was used to balance confounding factors for short-term and long-term survival, and survival analysis was carried out using the Kaplan-Meier method and log-rank test. The optimal cutoff for the number of ELNs in patients with stage II CC was determined using X-tile software. Independent prognostic factors were screened using Cox proportional hazards regression analysis. Finally, the results were externally validated in 318 patients with stage Ⅱ and ⅢB CC in our hospital from 2013 to 2015. RESULTS: The best cutoff value for the number of ELNs in patients with stage II CC was 14. Multivariate analysis identified age, grade, histology, tumor size, T stage, N stage, ELN count, and chemotherapy as independent prognostic factors, and the Akaike and Bayesian information criteria values for the prognostic value of ELN count were relatively small. Patients with stage II CC with <15 ELNs had similar prognoses to patients with stage ⅢB CC (P = 0.939). Subgroup analysis and external validation yielded similar results. CONCLUSION: Patients with stage II CC should be considered as stage ⅢB if the ELN count is insufficient.

Exceeding 30 ELNs is strongly recommended for pT3-4N0 patients with gastric cancer: A multicenter study of survival, recurrence, and prediction model.

The argument concerning the exact minimum number of examined lymph nodes (ELNs) has continued for a long time among various regions, and no consensus has been reached for stratified pathological T stages for data to date. Data from 4607 pN0 patients with gastric cancer were analyzed. Kaplan-Meier analysis showed the similar overall survival (OS) outcomes among the 3 groups (ELNs ≤ 15, 16 ≤ ELNs ≤ 29 and ELNs ≥ 30, P = .171). However, the ELNs ≥ 30 group had a better disease-free survival (DFS) outcome compared with the others (all P < .05). An increased ELN group (ELNs ≥ 30) showed an improved OS only for pT3 patients (hazard ratio [HR] = 0.397, 95% confidence interval (CI): 0.182-0.866, P = .020), while an improved DFS for pT3 patients (HR = 0.362, 95%CI: 0.152-0.860, P = .021) and pT4 patients (HR = 0.484, 95%CI: 0.277-0.844, P = .011) in the multivariate analysis. A well discriminated and calibrated nomogram was constructed to predict the probability of the OS and DFS, with the C-index for OS and DFS prediction of 0.782 (95%CI: 0.735 to 0.829) and 0.738 (95%CI: 0.685 to 0.791), respectively. This study provides new and useful insights into the impact of ELN count on reducing stage migration and postoperative recurrence of pN0 patients with gastric cancer in 2000-2017. In conclusion, a larger number of ELNs is suggested for surgeons to prolong the prognosis of pN0 gastric cancer, especially for pT3 patients.

Original study: The rescue staging for pancreatic ductal adenocarcinoma with inadequate examined lymph nodes.

BACKGROUND: In previous studies, it's recommended that the lymph node involvement should be evaluated with enough examined lymph nodes (eLNs) in the 8th American Joint Committee on Cancer (AJCC) staging system for pancreatic cancer. This study aims to put forward a rescue staging system for pancreatic ductal adenocarcinoma (PDAC) patients with inadequate eLNs after pancreatoduodenectomy (PD). METHOD: 11,224 PDAC patients undergoing PD in The Surveillance, Epidemiology, and End Results (SEER) database were included. Another Ruijin Pancreatic Disease Center (RJPDC) database consisted of 821 patients was utilized for external validation. RESULTS: The proportions of patients with eLNs≥15 were 44.7% and 32.8% in SEER and RJPDC database separately. The rescue staging system was put forward relying on LNR (HR = 1.83, 95% CI 1.74-1.92, P < 0.001) for N staging of eLNs<15 population and pLNs for the rest. The TNM modalities were also rearranged in the rescue system for better survival coordination. The C-index of rescue staging system was 0.638 while that of AJCC 8th staging system was 0.613 in SEER database. Similar phenomena were observed in RJPDC database. Kaplan-Meier analyses revealed reliable internal coherences (SEER: Ib: P = 0.26; IIa: P = 0.063; IIb: P = 0.53; IIIa: P = 0.11. RJPDC: Ib: P = 0.32; IIa: P = 0.66; IIb: P = 0.76; IIIa: P = 0.66) and significant staging efficiency (SEER: P < 0.001; RJPDC: P = 0.002). CONCLUSION: A rescue staging system was put forward regardless of the eLNs number. And the novel system manifested better predictive capacity than 8th AJCC staging system.