A Lymph Node Ratio-Based Staging Model Is Superior to the Current Staging System for Pancreatic Neuroendocrine Tumors

A Lymph Node Ratio Model for Prognosis of Patients with Pancreatic Neuroendocrine Tumors

The objective of this study was to determine the prognostic value of lymph node (LN) involvement and the LN ratio (LNR) and their effect on recurrence rates and survival in patients with pancreatic neuroendocrine tumors (PNETs) undergoing surgery. This single-center retrospective study reviewed the medical records of 95 consecutive patients diagnosed with PNETs who underwent surgery at our medical center between 1997 and 2017. The retrieved information included patient demographics, pathology reports, treatments, and oncological outcomes. Results: 95 consecutive potentially suitable patients were identified. The 78 patients with PNETs who underwent surgery and for whom there was adequate data were included in the analysis. Their mean ± standard deviation age at diagnosis was 57.4 ± 13.4 years (range 20-82), and there were 50 males (64%) and 28 females (36%). 23 patients (30%) had LN metastases (N1). The 2.5- and 5-year disease-free survival (DFS) rates for the entire cohort were 79.5% and 71.8%, respectively, and their 2- and 5-year overall survival (OS) rates were 85.9% and 82.1%, respectively. The optimal value of the LNR was 0.1603, which correlated with the outcome (2-year OS p = 0.002 HR = 13.4 and 5-year DFS p = 0.016 HR = 7.2, respectively, and 5-year OS and 5-year DFS p = 0.004 HR = 9 and p = 0.001 HR = 10.6, respectively). However, the multivariate analysis failed to show that the LNR was an independent prognostic factor in PNETs. Patients with PNETs grade and stage are known key prognostic factors influencing OS and DFS. According to our results, LNR failed to be an independent prognostic factor.

Risk Stratification of Pancreatic Neuroendocrine Neoplasms Based on Clinical, Pathological, and Molecular Characteristics

Pancreatic neuroendocrine neoplasms consist of heterogeneous diseases. Depending on the novel features detected by various modern technologies, their classification and related prognosis predictions continue to change and develop. The role of traditional clinicopathological prognostic factors, including classification systems, is also being refined, and several attempts have been made to predict a more accurate prognosis through novel serum biomarkers, genetic factors, and epigenetic factors that have been identified through various state-of-the-art molecular techniques with multiomics sequencing. In this review article, the latest research results including the traditional approach to prognostic factors and recent advanced strategies for risk stratification of pancreatic neuroendocrine neoplasms based on clinical, pathological, and molecular characteristics are summarized. Predicting prognosis through multi-factorial assessments seems to be more efficacious, and prognostic factors through noninvasive methods are expected to develop further advances in liquid biopsy in the future.

A modified mTNM staging system based on lymph node ratio for colon neuroendocrine tumors: A recursive partitioning analysis

BACKGROUND

In the current tumor-lymph node-metastasis (TNM) staging system for colon neuroendocrine tumors, lymph node status is divided into N1 and N0. An assessment of the lymph node ratio (LNR) and a proposal for a modified mTNM staging system were the objectives of this study.

METHODS

Selecting the optimal cut-off value of LNR was done using X-tile. A Cox regression model and the Kaplan-Meier method were performed to calculate patient cancer-specific survival in the Surveillance, Epidemiology and End Results cohort. Recursive partitioning analysis was used to improve TNM staging.

RESULTS

The study included 674 patients. The current TNM staging system showed inadequate discriminatory power between stage I and stage II patients (p = 0.088). The optimal cut-off value was determined as 0.6 for LNR. Based on multivariate Cox regression analysis, the modified mN classification could be classified into mN 0 (LNR = 0.00), mN 1 (LNR = 0.01-0.60), and mN 2 (LNR > 0.60), and was found to be an independent factor affecting prognosis (p < 0.001). Using the American Joint Committee on Cancer T and modified mN classifications, the modified mTNM system was constructed, and it exhibited better prognostic discriminatory power ability than the traditional TNM system (C-index: 0.587 vs. 0.665).

CONCLUSIONS

Our study determined that LNR is a prognostic factor in colon NET patients. In addition, to more accurately assess the prognosis of colon NET patients, we proposed a modified mTNM staging system.

Prognostic nomograms for lung neuroendocrine carcinomas based on lymph node ratio: a SEER database analysis

Objective

The current study aimed to explore the prognostic value of the lymph node ratio (LNR) in patients with lung neuroendocrine carcinomas (LNECs).

Methods

Data for 1564 elderly patients with LNECs between 1998 and 2016 were obtained from the Surveillance, Epidemiology, and End Results database. The cases were assigned randomly to training (n = 1086) and internal validation (n = 478) sets. The association between LNR and survival was investigated by Cox regression.

Results

Multivariate analyses identified age, tumor grade, summary stage, M stage, surgery, and LNR as independent prognostic factors for both overall survival (OS) and lung cancer-specific survival (LCSS). Tumor size was also a prognostic determinant for LCSS. Prognostic nomograms combining LNR with other informative variables showed good discrimination and calibration abilities in both the training and validation sets. In addition, the C-index of the nomograms was statistically superior to the American Joint Committee on Cancer (AJCC) staging system in both the training and validation cohorts.

Conclusions

These nomograms, based on LNR, showed superior prognostic predictive accuracy compared with the AJCC staging system for predicting OS and LCSS in patients with LNECs.

Prognostic Nomogram Based on the Metastatic Lymph Node Ratio for T1-4N0-1M0 Pancreatic Neuroendocrine Tumors After Surgery

Purpose

This study aimed to investigate the prognostic significance of the metastatic lymph node ratio (LNR) in patients with pancreatic neuroendocrine tumors (pNETs) and to develop and validate nomograms to predict 5-, 7-, and 10-year overall survival (OS) and cancer-specific survival (CSS) rates for pNETs after surgical resection.

Methods

The demographics and clinicopathological information of T_1-4N_0-1M₀ pNET patients between 2004 and 2018 were extracted from the Surveillance, Epidemiology and End Results database. X-tile software was used to determine the best cutoff value for the LNR. Patients were randomly divided into the training and the validation groups. A Cox regression model was used in the training group to obtain independent prognostic factors to develop nomograms for predicting OS and CSS. The concordance index (C-index), calibration curves, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the nomograms. Patients were divided into four groups according to the model scores, and their survival curves were generated by the Kaplan–Meier method.

Results

A total of 806 patients were included in this study. The best cutoff value for the LNR was 0.16. The LNR was negatively correlated with both OS and CSS. Age, sex, marital status, primary site, grade, the LNR and radiotherapy were used to construct OS and CSS nomograms. In the training group, the C-index was 0.771 for OS and 0.778 for CSS. In the validation group, the C-index was 0.737 for OS and 0.727 for CSS. The calibration curves and AUC also indicated their good predictability. DCA demonstrated that the nomograms displayed better performance than the American Joint Committee on Cancer (AJCC) TNM staging system (8th edition). Risk stratification indicated that patients with higher risk had a worse prognosis.

Conclusions

The LNR is an independent negative prognostic factor for pNETs. The nomograms we built can accurately predict long-term survival for pNETs after surgery.

Surgical Principles in the Management of Lung Neuroendocrine Tumors: Open Questions and Controversial Technical Issues

OPINION STATEMENT

Primary neuroendocrine tumors (NETs) of the lung represent a heterogeneous group of malignancies arising from the endocrine cells, involving different entities, from well differentiated to highly undifferentiated neoplasms. Because of the predominance of poorly differentiated tumors, advanced disease is observed at diagnosis in more than one third of patients making chemo- or chemoradiotherapy the only possible treatment. Complete surgical resection, as defined as anatomical resection plus systematic lymphadenectomy, becomes a reliable curative option only for that little percentage of patients presenting with stage I (N0) high-grade NETs. On the other hand, complete surgical resection is considered the mainstay treatment for localized low- and intermediate-grade NETs. Therefore, in the era of the mini-invasive surgery, their indolent behavior has suggested that parenchyma-sparing resections could be as adequate as the anatomical ones in terms of oncological outcomes, leading to discuss about the correct extent of resection and about the role of lymphadenectomy when dealing with highly differentiated NETs.

Plasma Hemoglobin and Red Blood Cell Mass Levels as Dynamic Prognostic Markers for Progression and Survival in Pancreatic Neuroendocrine Tumors

There are scarce data on readily available markers enabling immediate risk stratification and personalized management in patients with advanced pancreatic neuroendocrine tumors. This study explores the association of red blood cells-related parameters as prognostic markers in patients harboring pancreatic neuroendocrine tumors. Retrospective analysis of a tertiary medical center database, acquiring data of patients with pancreatic neuroendocrine tumors including demographics, tumor-related parameters and consecutive imaging results, vital status at last follow-up, and red blood cells parameters at baseline, last follow-up, and dynamics (last/baseline ratio). Univariate and multivariable analyses were performed. Sixty-seven patients were identified (mean age at diagnosis of 63±11 years, 56.7% males). Patients with disease progression had lower hemoglobin, red blood cells mass values and hematocrit at the last evaluation (p<0.001 for all comparisons), with red blood cells mass level<3.9 m/μl and a 6% and 9% relative reduction in hemoglobin and hematocrit levels, respectively, associated with an increased risk for disease progression. Similarly, patients deceased during the study period had lower hemoglobin, red blood cells mass values and hematocrit (p<0.03 for all) than those alive, at last follow-up. Eleven percent reduction in hemoglobin level was noted indicating a higher mortality risk (p=0.04). Negative hemoglobin and hematocrit dynamics were independently associated with increased risk for disease progression (p=0.03 and 0.049, respectively). In conclusion, decrease in red blood cells mass, hemoglobin and/or hematocrit levels are all associated with poor prognosis in patients with pancreatic neuroendocrine tumors. We suggest utilizing these parameters as complementary follow-up prognostic markers to radiologic imaging in this patients population.

Patterns and predictors of pancreatic neuroendocrine tumor prognosis: Are no two leaves alike?

Pancreatic neuroendocrine tumors (PanNETs) are heterogeneous; thus, individual prognostic prediction is important. Clinicopathological features, like TNM stage, grade, and differentiation, are independent clinical predictors. However, single predictors are insufficient, as patients sharing similar clinicopathological features usually show distinct prognoses. Accordingly, novel nomograms and risk stratifications have been developed for more accurate PanNET prognostic prediction. Moreover, the exploration of molecular mechanisms has identified novel prognostic predictors for PanNET. Multi-analyte assays of molecular biomarkers provide a deeper understanding of PanNET features; however, the priority, and the optimal combination of classic and novel predictors for PanNET prognosis prediction remain unclear. In this review, we summarized the patterns and predictors of PanNET prognosis and discussed their clinical utility; we emphasized that PanNET at different stages have different superior predictor, and that multi-analyte assays are more sensitive than mono-analyte biomarkers. Therefore, combined biomarkers improve the accuracy of surveillance and optimize decision-making in clinical practice.

Optimal Cut-Off Values of the Positive Lymph Node Ratio and the Number of Removed Nodes for Patients Receiving Resection of Bronchopulmonary Carcinoids: A Propensity Score-Weighted Analysis of the SEER Database

Background

Although lymph node dissection (LND) has been commonly used for patients with bronchopulmonary carcinoids (PCs), the prognostic values of the positive lymph node ratio (PLNR) and the number of removed nodes (NRN) remain unclear.

Methods

Patients with resected PCs were identified in the Surveillance, Epidemiology, and End Results (SEER) database (2010–2015). The optimal cut-off values of the PLNR and NRN were determined by X-tile. The inverse probability of treatment weighting (IPTW) method was used to reduce the selection bias. IPTW-adjusted Kaplan-Meier curves and Cox proportional hazards models were used to compare the overall survival (OS) and cancer-specific survival (CSS) of patients in different PLNR and NRN groups.

Results

The study included 1622 patients. The optimal cut-off values of the PLNR and NRN for survival were 13% and 13, respectively. In both Kaplan-Meier analysis and univariable Cox proportional hazards regression analysis before IPTW, a PLNR ≥13% was significantly associated with worse OS (HR = 3.364, P<0.001) and worse CSS (HR = 7.874, P<0.001). These findings were corroborated by the IPTW-adjusted Cox analysis OS (HR = 2.358, P = 0.0275) and CSS (HR = 8.190, P<0.001) results. An NRN ≥13 was not significantly associated with worse OS in either the Kaplan-Meier or Cox analysis before or after IPTW adjustment. In the Cox proportional hazards analysis before and after IPTW adjustment, an NRN ≥13 was significantly associated with worse CSS (non-IPTW: HR = 2.216, P=0.013; IPTW-adjusted: HR = 2.162, P=0.024).

Conclusion

A PLNR ≥13% could predict worse OS and CSS in patients with PCs and might be an important complement to the present PC staging system. Extensive LND with an NRN ≥13 might have no therapeutic value for OS and may even have an adverse influence on CSS. Its application should be considered on an individual basis.

New Nodal Staging for Primary Pancreatic Neuroendocrine Tumors: A Multi-institutional and National Data Analysis

OBJECTIVE

To determine the prognostic role of metastatic lymph node (LN) number and the minimal number of LNs for optimal staging of patients with pancreatic neuroendocrine tumors (pNETs).

BACKGROUND

Prognosis relative to number of LN metastasis (LNM), and minimal number of LNs needed to evaluate for accurate staging, have been poorly defined for pNETs.

METHODS

Number of LNM and total number of LN evaluated (TNLE) were assessed relative to recurrence-free survival (RFS) and overall survival (OS) in a multi-institutional database. External validation was performed using Surveillance, Epidemiology and End Results (SEER) registry.

RESULTS

Among 854 patients who underwent resection, 233 (27.3%) had at least 1 LNM. Patients with 1, 2, or 3 LNM had a comparable worse RFS versus patients with no nodal metastasis (5-year RFS, 1 LNM 65.6%, 2 LNM 68.2%, 3 LNM 63.2% vs 0 LNM 82.6%; all P < 0.001). In contrast, patients with ≥4 LNM (proposed N2) had a worse RFS versus patients who either had 1 to 3 LNM (proposed N1) or node-negative disease (5-year RFS, ≥4 LNM 43.5% vs 1-3 LNM 66.3%, 0 LNM 82.6%; all P < 0.05) [C-statistics area under the curve (AUC) 0.650]. TNLE ≥8 had the highest discriminatory power relative to RFS (AUC 0.713) and OS (AUC 0.726) among patients who had 1 to 3 LNM, and patients who had ≥4 LNM in the multi-institutional and SEER database (n = 2764).

CONCLUSIONS

Regional lymphadenectomy of at least 8 lymph nodes was necessary to stage patients accurately. The proposed nodal staging of N0, N1, and N2 optimally staged patients.

Role of Lymph Node Resection and Histopathological Evaluation in Accurate Staging of Nonfunctional Pancreatic Neuroendocrine Tumors: How Many Are Enough?

BACKGROUND

Nodal involvement has been identified as one of the strongest prognostic factors in patients with nonfunctional pancreatic neuroendocrine tumors (NF-PanNETs). Sufficient lymphadenectomy and evaluation is vital for accurate staging. The purpose of this study was to identify the optimal number of examined lymph nodes (ELN) required for accurate staging.

METHODS

The SEER database was used to identify patients with resected NF-PanNETs between 2004 and 2014. The distributions of positive lymph nodes (PLN) ratio and total lymph nodes were used to develop a mathematical model. The sensitivity of detecting nodal disease at each cutoff of ELN was estimated and used to identify the optimal cutoff for ELN.

RESULTS

A total of 1098 patients were included in the study of which 391 patients (35.6%) had nodal disease. The median ELN was 12 (interquartile range [IQR]: 7-19.5), and the median PLN was 2 (IQR: 1-4) for patients with nodal disease. With an increase in ELN, the sensitivity of detecting nodal disease increased from 12.0% (ELN: 1) to 92.2% (ELN: 20), plateauing at 20 ELN (< 1% increase in sensitivity with an additional ELN). This sensitivity increase pattern was similar in subgroup analyses with different T stages.

CONCLUSIONS

The sensitivity of detecting nodal disease in patients with NF-PanNETs increases with an increase in the number of ELN. Cutoffs for adequate nodal assessment were defined for all T stages. Utilization of these cutoffs in clinical settings will help with patient prognostication and management.

Prognosis analysis of patients with pancreatic neuroendocrine tumors after surgical resection and the application of enucleation

Objective

To investigate the prognostic factors of patients with pancreatic neuroendocrine tumor (pNETs) after surgical resection, and to analyze the value of enucleation for pNETs without distant metastasis that are well-differentiated (G1) and have a diameter ≤ 4 cm.

Methods

Data from pNET patients undergoing surgical resection between 2004 and 2017 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan–Meier analysis and log-rank testing were used for the survival comparisons. Adjusted HRs with 95% CIs were calculated using univariate and multivariate Cox regression models to estimate the prognostic factors. P < 0.05 was regarded as statistically significant.

Results

This study found that female, cases diagnosed after 2010, and pancreatic body/tail tumors were protective factors for good survival, while histological grade G3, a larger tumor size, distant metastasis, AJCC 8th stage III-IV and age over 60 were independent prognostic factors for a worse OS/CSS. For the pNETs that were well-differentiated (G1) and had a tumor diameter ≤ 4 cm, the type of surgery was an independent factor for the long-term prognosis of this group. Compared with pancreaticoduodenectomy and total pancreatectomy, patients who were accepted enucleation had better OS/CSS.

Conclusion

For pNETs patients undergoing surgical resection, sex, year of diagnosis, tumor location, pathological grade, tumor size, distant metastasis, race, and age were independent prognostic factors associated with the OS/CSS of patients. For pNETs patients with G1 and a tumor diameter less than 4 cm, if the tumor was located over 3 mm from the pancreatic duct, enucleation may be a wise choice.

Number of Positive Lymph Nodes Is Superior to LNR and LODDS for Predicting the Prognosis of Pancreatic Neuroendocrine Neoplasms

BACKGROUND

The American Joint Committee on Cancer (AJCC) staging for pancreatic neuroendocrine neoplasms (PanNENs) based on the number of positive lymph nodes (PLNs) is the most widely accepted nodal staging system. New nodal staging schemes that take both the number of PLNs and the number of examined lymph nodes into consideration have emerged as useful prognostic tools. The aim of the current study was to determine the most effective nodal staging system, among the 8th edition AJCC N staging (or PLN staging), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS), for predicting the cause-specific survival of patients with PanNENs.

METHODS

The clinicopathological and prognostic data of 2,295 patients from the Surveillance, Epidemiology, and End Results (SEER) database, diagnosed with PanNENs between 1988 and 2015, were reviewed retrospectively.

RESULTS

A multivariate analysis identified PLN and LNR staging as independent prognostic factors, but not LODDS. The PLN staging exhibited higher C-index and area under the curve values than those of the LNR and LODDS, indicating better predictive discriminatory capacity. No significant difference in the survival of patients was observed within the same PLN staging subgroup according to the number (high or low) of examined lymph nodes. In contrast, intra-group heterogeneity was seen with use of LNR and LODDS staging, due to overestimation of the risk of insufficient examined lymph nodes, and LODDS failed to stratify patients without lymph nodes metastasis into different risk groups.

CONCLUSIONS

The PLN staging is more reliable than LNR and LODDS staging for predicting the cause-specific survival of PanNENs.

M6A Regulatory Genes Play an Important Role in the Prognosis, Progression and Immune Microenvironment of Pancreatic Adenocarcinoma

The specific roles of N6-methyladenosine (m6A) regulatory genes in pancreatic adenocarcinoma (PAAD) have not been fully elucidated. In present study, a novel risk signature was constructed by five m6A-related genes (including METTL3, METTL14, KIAA1429, ALKBH5 and YTHDF1) and was identified as an independent prognostic factor (HR = 13.192) via TCGA (185 samples) databases. The immune abundances of 22 leukocyte subtypes in each PAAD sample were exhibited via the CIBERSORT algorithm. High risk group promoted infiltration levels of Macrophages M0 and M2 cells and decreased that of B cells naive, T cells CD8 and T regulatory cells.

The eighth version of American Joint Committee on Cancer nodal classification for high grade pancreatic neuroendocrine tumor should be generalized for the whole population with this disease

Several indexes evaluating the lymph node metastasis of pancreatic neuroendocrine tumor (pNET) have been raised. We aimed to compare the prognostic value of the indexes via the analysis of Surveillance, Epidemiology, and End Results (SEER) database.We identified pNETs patients from SEER database (2004-2015). The prognostic value of N classification which adopted the 8th American Joint Committee on Cancer (AJCC) N classification for well differentiated pNET, revised N classification (rN) which adopted the AJCC 8th N classification for exocrine pancreatic cancer (EPC) and high grade pNET, lymph node ratio and log odds of positive nodes were analyzed.A total of 1791 eligible patients in the SEER cohort were included in this study. The indexes N, rN, lymph node ratio, and log odds of positive nodes were all significant independent prognostic factors for the overall survival. Specifically, the rN had the lowest akaike information criterion of 4050.19, the highest likelihood ratio test (χ) of 48.87, and the highest C-index of 0.6094. The rN was significantly associated with age, tumor location, tumor differentiation, T classification and M classification (P < .05 for all).The 8th version of AJCC N classification for high grade pNET could be generalized for the pNET population.

Prognostic and predictive factors on overall survival and surgical outcomes in pancreatic neuroendocrine tumors: recent advances and controversies

Introduction: Recent advances in diagnostic modalities and therapeutic agents have raised the importance of prognostic factors in predicting overall survival, as well as predictive factors for surgical outcomes, in tailoring therapeutic strategies of patients with pancreatic neuroendocrine neoplasms (panNENs).Areas covered: Numerous recent studies of panNEN patients report the prognostic values of a number of clinically related factors (clinical, laboratory, imaging, treatment-related factors), pathological factors (histological, classification, grading) and molecular factors on long-term survival. In addition, an increasing number of studies showed the usefulness of various factors, specifically biomarkers and molecular makers, in predicting recurrence and mortality related to surgical treatment. Recent findings (from the last 3 years) in each of these areas, as well as recent controversies, are reviewed.Expert commentary: The clinical importance of prognostic and predictive factors for panNENs is markedly increased for both overall outcome and post resection, as a result of recent advances in all aspects of the diagnosis, management and treatment of panNENs. Despite the proven prognostic utility of routinely used tumor grading/classification and staging systems, further studies are required to establish these novel prognostic factors to support their routine clinical use.

Competing risks and cause-specific mortality in patients with pancreatic neuroendocrine tumors

BACKGROUND AND OBJECTIVE

Currently, there are no competing risk analyses of cause-specific mortality in patients with pancreatic neuroendocrine tumors.

MATERIALS AND METHODS

We estimated a cumulative incidence function for cause-specific mortality. The first nomogram for predicting cause-specific mortality was constructed using a proportional subdistribution hazard model, validated using bootstrap cross-validation, and evaluated with decision curve analysis.

RESULTS

Sex, age, positive lymph node status, metastasis, surveillance, epidemiology, and end results historic stage, grade, and surgery strongly predicted cause-specific mortality. The discrimination performance of Fine-Gray models was evaluated using the c-index, which was 0.864. In addition, the calibration plot of the developed nomogram demonstrated good concordance between the predicted and actual outcomes. Decision curve analysis yielded a range of threshold probabilities (0.014-0.779) at which the clinical net benefit of the risk model was greater than that in hypothetical all-screening or no-screening scenarios.

CONCLUSION

Our nomogram allows selection of a patient population at high risk for cancer-specific mortality and thus facilitates the design of prevention trials for the affected population.