Determining the optimal number of examined lymph nodes for accurate staging of pancreatic cancer: An analysis using the nodal staging score model

Defining Optimal Lymph Node Yield in Gastrectomy: A Real-World Cohort Analysis

BACKGROUND

Gastric cancer (GC) has a high global mortality and incidence rate. Lymph node (LN) invasion is crucial in TNM staging, and an accurate LN staging system is vital for treatment decisions. However, the appropriate number of examined LNs remains uncertain.

METHODS

We retrospectively analyzed consecutive GC patients who underwent gastrectomy at the First Medical Center of the Chinese PLA General Hospital from January 2010 to December 2023. A new statistical model based on the β-binomial distribution and maximum likelihood method in R software was employed to calculate false-negative probabilities.

RESULTS

A total of 6463 GC patients were included. For cT1 patients, even with only five LNs excised, the likelihood of encountering occult positive LNs remained below 5%. For cT2 patients, 17 nodes were needed to rule out occult nodal disease with 90% confidence. While for cT3 and cT4 patients, even after the removal of 35 LNs, the likelihood of overlooking a positive node was still above 20%. Considering surgical extent, 25 nodes were required for patients who underwent proximal gastrectomy or distal gastrectomy to rule out occult nodal disease with 90% confidence, whereas those who received entire gastrectomy needed 59 nodes to achieve the same level of confidence.

CONCLUSION

Our study establishes a novel quantitative framework linking LN harvest thresholds to false-negative metastasis risk in GC, derived from real-world clinicopathological data.

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.

Prognostic nomogram for estimating survival in patients with resected muscle-invasive bladder cancer receiving chemotherapy

Background

Chemotherapy has been proven to bring survival benefit in patients with resected muscle-invasive bladder cancer (MIBC), which is increasingly recommended. Our objective was to establish an effective model for estimating the overall survival (OS) and cancer-specific survival (CSS) in these patients.

Methods

2,030 patients diagnosed with resected MIBC receiving chemotherapy were acquired from the Surveillance, Epidemiology, and End Result (SEER) database, which were randomized 7:3 into a primary set (1,421 patients) and an internal validation set (609 patients). Significant predictors for OS and CSS were identified by Cox regression models, which were then utilized to develop prognostic nomogram. The performance of the model was assessed by utilizing calibration, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).

Results

Six independent prognostic factors, including age, race, histology, T stage, N stage and regional nodes examined, made up the nomogram. The AUCs of the primary cohort was 0.751 and 0.753 for 3- and 5- year OS and 0.751 and 0.754 for 3-and 5- year CSS, respectively. The calibration plots proved the nomograms' satisfactory discrimination. The results of DCA manifested that our models had an excellent clinical applicability. In addition, a risk stratification system was established according to the nomogram' risk score. Obvious difference was found in different groups (P < 0.001).

Conclusion

The established prediction nomogram provides a simple-to-use tool for estimating the survival probability of resected MIBC patients treated with chemotherapy, which can assist clinicians make individualized treatment plans.

Pathologic node-negative lung cancer: Adequacy of lymph node yield and a tool to assess the risk of occult nodal disease

INTRODUCTION

Accurate lymph node (LN) staging is crucial for prognostication in NSCLC. Diagnosis of pN0 disease is based on the absence of positive LNs, irrespective of the number of LNs excised, and is thus susceptible to sampling error. Tumors that are assumed to be pN0 may in fact be understaged. We developed a tool to quantify the risk of occult nodal disease (OND) among patients with pN0 NSCLC in terms of the number of LNs examined.

METHODS

Patients treated surgically for stage I-III primary NSCLC between 2004 and 2014 (n = 49,356) were extracted from the Surveillance, Epidemiology, and End Results database. The probability of missing a positive node in terms of the number of LNs examined was modeled using a beta-binomial model. A mathematical tool was then used to calculate the negative predictive value (NPV) corresponding to the number of LNs examined. Ranging from 0 to 100%, higher NPV reflects greater confidence in the pN0 diagnosis and a lower probability of OND.

RESULTS

The median number of LNs examined was 7 for N0, 10 for N1/N2, and 8 for N3 disease. The probability of missing a positive node decreased as LNs examined increased. Additionally, higher T stage required more LNs to confirm an N0 diagnosis. After accounting for false-negative diagnoses, the prevalence of node-positive disease was readjusted from 16% to 22% among patients with T1 disease. According to our tool, with 10 LNs examined, the NPV was 85% (15% probability of OND) for a patient with T3 disease, compared with 95% (5% probability of OND) for a patient with T1 disease.

CONCLUSIONS

Accurate pN0 diagnosis depends on the number of LNs examined. The proposed tool offers the ability to quantify, in a patient-specific manner, the confidence in a diagnosis of node-negative disease on the basis of the number of LNs examined.

Reassessment of the Optimal Number of Examined Lymph Nodes in Pancreatoduodenectomy for Pancreatic Ductal Adenocarcinoma

OBJECTIVE

The aim of this study was to reappraise the optimal number of examined lymph nodes (ELNs) in pancreatoduodenectomy (PD) for pancreatic ductal adenocarcinoma (PDAC).

SUMMARY BACKGROUND DATA

The well-established threshold of 15 ELNs in PD for PDAC is optimized for detecting 1 positive node (PLN) per the previous 7th edition of the American Joint Committee on Cancer (AJCC) staging manual. In the framework of the 8th edition, where at least 4 PLN are needed for an N2 diagnosis, this threshold may be inadequate for accurate staging.

METHODS

Patients who underwent upfront PD at 2 academic institutions between 2000 and 2016 were analyzed. The optimal ELN threshold was defined as the cut-point associated with a 95% probability of identifying at least 4 PLNs in N2 patients. The results were validated addressing the N-status distribution and stage migration.

RESULTS

Overall, 1218 patients were included. The median number of ELN was 26 (IQR 17-37). ELN was independently associated with N2-status (OR 1.27, P < 0.001). The estimated optimal threshold of ELN was 28. This cut-point enabled improved detection of N2 patients and stage III disease (58% vs 37%, P = 0.001). The median survival was 28.6 months. There was an improved survival in N0/N1 patients when ELN exceeded 28, suggesting a stage migration effect (47 vs 29 months, adjusted HR 0.649, P < 0.001). In N2 patients, this threshold was not associated with survival on multivariable analysis.

CONCLUSION

Examining at least 28 LN in PD for PDAC ensures optimal staging through improved detection of N2/stage III disease. This may have relevant implications for benchmarking processes and quality implementation.

Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort

Objective

This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC).

Methods

For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves.

Results

A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718–0.735) and 0.721 (95% CI, 0.709–0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691–0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system.

Conclusion

We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10067-8.

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.

Surgery for pancreatic cancer: current controversies and challenges

Two areas that remain the focus of improvement in pancreatic cancer include high post-operative morbidity and inability to uniformly translate surgical success into long-term survival. This narrative review addresses specific aspects of pancreatic cancer surgery, including neoadjuvant therapy, vascular resections, extended pancreatectomy, extent of lymphadenectomy and current status of minimally invasive surgery. R0 resection confers longer disease-free survival and overall survival. Vascular and adjacent organ resections should be undertaken after neoadjuvant therapy, only if R0 resection can be ensured based on high-quality preoperative imaging, and that too, with acceptable post-operative morbidity. Extended lymphadenectomy does not offer any advantage over standard lymphadenectomy. Although minimally invasive distal pancreatectomies offers some short-term benefits over open distal pancreatectomy, safety remains a concern with minimally invasive pancreatoduodenectomy. Strict adherence to principles and judicious utilization of surgery within a multimodality framework is the way forward.

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.

Stage migration resulting from inadequate number of examined lymph nodes impacts prognosis in stage II colon cancer after radical surgery

PURPOSE

We evaluated the impact of examined lymph node (ELN) number on the prognosis of stage II colon cancer after radical surgery and developed a novel prognostic scoring system by combining primary tumor extension (pT) and ELN number for reclassification of stage II colon cancer.

METHODS

Three cohorts of patients diagnosed with colon cancer between 2004 and 2010 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analyses were performed to evaluate the relationship between factors and patients' survival including cause-specific survival (CSS) and overall survival (OS). Survival curves from subgroups were plotted by the Kaplan-Meier method and compared by the log-rank test.

RESULTS

Cohort 1 and cohort 2 consisted of 13,960 and 5312 stage II colon cancer patients, respectively. Cohort 3 consisted of 4713 stage III patients. Factors including ELN, age, and pT were found to be associated with patients' survival in cohorts 1 and 2. Patients who were older or with smaller tumors were more likely to experience inadequate ELN. Patients with a higher score, as calculated by the novel scoring system, showed worse survival. Compared with stage III colon cancer patients, stage II patients with high scores had a comparable or even worse survival than stage IIIA and IIIB patients.

CONCLUSION

Inadequate ELN leads to understaging in stage II colon cancer and predicts inferior prognosis. Our analyses show that the novel prognostic scoring system, consisting of combined pT and ELN, quantified stage migration effect and can be applied to the reclassification of stage II colon cancer.

Pathologic upstaging in resected pancreatic adenocarcinoma: Risk factors and impact on survival

BACKGROUND

Clinical and pathologic staging determine treatment of pancreatic cancer. Clinical stage has been shown to underestimate final pathologic stage in pancreatic cancer, resulting in upstaging.

METHODS

National Cancer Database was used to identify clinical stage I pancreatic adenocarcinoma. Univariate, multivariable logistic regression, and Cox proportional hazard ratio were used to determine differences between upstaged and stage concordant patients.

RESULTS

Upstaging was seen in 80.2% of patients. Factors found to be significantly associated with upstaging included pancreatic head tumors (OR 2.56), high-grade histology (OR 1.74), elevated Ca 19-9 (OR 2.09), and clinical stage T2 (OR 1.99). Upstaging was associated with a 45% increased risk of mortality compared to stage concordant disease (HR 1.44, p < .001).

CONCLUSION

A majority of clinical stage I pancreatic cancer is upstaged after resection. Factors including tumor location, grade, Ca 19-9, and tumor size can help identify those at high risk for upstaging.

A nomogram for predicting overall survival in patients with resected non-small cell lung cancer treated with chemotherapy

Background

Chemotherapy is a common treatment for patients with resected non-small cell lung cancer (NSCLC). However, there are few models for predicting the survival outcomes of these patients. Here, we developed a clinical nomogram for predicting overall survival (OS) in this cohort.

Methods

A total of 16,661 patients with resected NSCLC treated with chemotherapy were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified prognostic factors and integrated them into a nomogram. The model was subjected to bootstrap internal validation using the SEER database and external validation using a database in China and the National Cancer Database (NCDB). The model’s predictive accuracy and discriminative ability were tested by calibration and concordance index (C-index).

Results

Age, sex, number of dissected lymph nodes, extent of surgery, N stage, T stage, and grade were independent factors for OS and were integrated into the model. The calibration curves for probability of 1-, 3-, and 5-year OS showed excellent agreement between the predicted and actual survivals. The C-index of the nomogram was higher than that of the Tumor-Node-Metastasis staging system for predicting OS (training cohort, 0.62 vs. 0.58; China cohort, 0.68 vs. 0.63; NCDB cohort, 0.59 vs. 0.57).

Conclusions

We developed a nomogram that can present individual prediction of OS for patients with resected NSCLC who are undergoing chemotherapy. This practical prognostic tool may help clinicians in treatment planning.

Analysis of the Trends in Publications on Clinical Cancer Research in Mainland China from the Surveillance, Epidemiology, and End Results (SEER) Database: Bibliometric Study

BACKGROUND

The application of China's big data sector in cancer research is just the beginning. In recent decades, more and more Chinese scholars have used the Surveillance, Epidemiology, and End Results (SEER) database for clinical cancer research. A comprehensive bibliometric study is required to analyze the tendency of Chinese scholars to utilize the SEER database for clinical cancer research and provide a reference for the future of big data analytics.

OBJECTIVE

Our study aimed to assess the trend of publications on clinical cancer research in mainland China from the SEER database.

METHODS

We performed a PubMed search to identify papers published with data from the SEER database in mainland China until August 31, 2020.

RESULTS

A total of 1566 papers utilizing the SEER database that were authored by investigators in mainland China were identified. Over the past years, significant growth in studies based on the SEER database was observed (P<.001). The top 5 research topics were breast cancer (213/1566, 13.6%), followed by colorectal cancer (185/1566, 11.8%), lung cancer (179/1566, 11.4%), gastrointestinal cancer (excluding colorectal cancer; 149/1566, 9.5%), and genital system cancer (93/1566, 5.9%). Approximately 75.2% (1178/1566) of papers were published from the eastern coastal region of China, and Fudan University Shanghai Cancer Center (Shanghai, China) was the most active organization. Overall, 267 journals were analyzed in this study, of which Oncotarget was the most contributing journal (136/267, 50.9%). Of the 1566 papers studied, 585 (37.4%) were published in the second quartile, 489 (31.2%) in the third quartile, 312 (19.9%) in the first quartile, and 80 (5.1%) in the fourth quartile, with 100 (6.4%) having an unknown Journal Citation Reports ranking.

CONCLUSIONS

Clinical cancer research based on the SEER database in mainland China underwent constant and rapid growth during recent years. High-quality and comprehensive cancer databases based on Chinese demographic data are urgently needed.

The influence of cervical lymph node number of neck dissection on the prognosis of the early oral cancer patients

Background/purpose

The status of neck lymph nodes (LNs) plays an important role in survival of oral cavity cancer. Early stage oral cancer patients are still at a risk for locoregional metastasis. We aimed to determine the number of LNs that needs to be retrieved for adequate diagnosis and treatment of the neck tumor.

Materials and methods

We conducted a retrospective study of 126 oral cavity cancer patients who underwent wide excision and 3 types of neck dissection at MacKay Memorial Hospital, Taiwan. Data from the operative and pathology reports were collected and analyzed. The significant difference was defined as p < 0.05 by SPSS 21.0 and Prizm 5 software.

Results

There was a significant difference between the total retrieved LNs and tumor differentiation and nerve invasion on multivariate analysis. Receiveroperating characteristic (ROC) curve showed significant difference in the total number of neck LNs between the survival and expired groups. The cut-off point was 36.5 nodes. However, there was no difference in survival between supraomohyoid and modified radical neck dissection.

Conclusion

Retrieval of adequate LNs can improve oral cancer survival rates. If total number of neck nodes examined is <37 with poor differentiation and/or nerve invasion, early oral cancer patients with neck dissection have a lower survival rate and are candidates for adjuvant therapy.

Prognostic impact of lymph node status in patients after total pancreatectomy for pancreatic ductal adenocarcinoma: A strobe-compliant study

The optimal number of examined lymph nodes (ELN) for staging and impact of nodal status on survival following total pancreatectomy (TP) for pancreatic ductal adenocarcinoma (PDAC) is unclear. The aim of this study was to evaluate the prognostic impact of different lymph node status after TP for PDAC.The Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients who underwent TP for PDAC from 2004 to 2015. We calculated overall survival (OS) of these patients using Kaplan-Meier analysis and Cox proportional hazards model.Overall, 1291 patients were included in the study, with 869 node-positive patients (49.5%). A cut-off points analysis revealed that 19, 19, and 13 lymph nodes best discriminated OS for all patients, node-negative patients, and node-positive patients, respectively. Higher number of ELN than the corresponding cut-off points was an independent predictor for better prognosis [all patients: hazard ratios (HR) 0.786, P = .002; node-negative patients: HR 0.714, P = .043; node-positive patients: HR 0.678, P < .001]. For node-positive patients, 1 to 3 positive lymph nodes (PLN) correlated independently with better survival compared with those with 4 or more PLN (HR 1.433, P = .002). Moreover, when analyzed in node-positive patients with less than 13 ELN, neither the number of PLN nor lymph node ratio (LNR) was associated with survival. However, when limited node-positive patients with at least 13 ELN, univariate analyses showed that both the number of PLN and LNR were associated with survival, whereas multivariate analyses demonstrated that only number of PLN was consistently associated with survival (HR 1.556, P = .004).Evaluation at least 19 lymph nodes should be considered as quality metric of surgery in patients who underwent TP for PDAC. For node-negative patients, a minimal number of 19 lymph nodes is adequate to avoid stage migration. For node-positive patients, PLN is superior to LNR in predicting survival after TP, predominantly for those with high number of ELN.