Prognostic Performance of Different Lymph Node Staging Systems in Patients With Small Bowel Neuroendocrine Tumors

Different lymph node staging systems for predicting the prognosis of colorectal neuroendocrine neoplasms

BACKGROUND

Colorectal neuroendocrine neoplasms (NENs) are a rare malignancy that primarily arises from the diffuse distribution of neuroendocrine cells in the colon and rectum. Previous studies have pointed out that the status of lymph node may be used to predict the prognosis.

AIM

To investigate the predictive values of lymph node ratio (LNR), positive lymph node (PLN), and log odds of PLNs (LODDS) staging systems on the prognosis of colorectal NENs treated surgically, and compare their predictive values.

METHODS

This cohort study included 895 patients with colorectal NENs treated surgically from the Surveillance, Epidemiology, and End Results database. The endpoint was mortality of patients with colorectal NENs treated surgically. X-tile software was utilized to identify most suitable thresholds for categorizing the LNR, PLN, and LODDS. Participants were selected in a random manner to form training and testing sets. The prognosis of surgically treating colorectal NENs was examined using multivariate cox analysis to assess the associations of LNR, PLN, and LODDS with the prognosis of colorectal NENs. C-index was used for assessing the predictive effectiveness. We conducted a subgroup analysis to explore the different lymph node staging systems' predictive values.

RESULTS

After adjusting all confounding factors, PLN, LNR and LODDS staging systems were linked with mortality in patients with colorectal NENs treated surgically (P < 0.05). We found that LODDS staging had a higher prognostic value for patients with colorectal NENs treated surgically than PLN and LNR staging systems. Similar results were obtained in the different G staging subgroup analyses. Furthermore, the area under the receiver operating characteristic curve values for LODDS staging system remained consistently higher than those of PLN or LNR, even at the 1-, 2-, 3-, 4-, 5- and 6-year follow-up periods.

CONCLUSION

LNR, PLN, and LODDS were found to significantly predict the prognosis of patients with colorectal NENs treated surgically.

The prognostic ability of radiotherapy of different colorectal cancer histological subtypes and tumor sites

The prognostic significance of radiotherapy (RT) for colorectal cancer (CRC) has shown conflicting results, particularly among different pathological subtypes, including adenocarcinoma (AC), mucinous adenocarcinoma (MC), and signet-ring cell carcinoma (SR). This study analyzed the prognosis of three pathological CRC types and focused on the prognostic significance of RT on three CRC histological subtypes. Patients diagnosed with AC (n = 54,174), MC (n = 3813), and SR (n = 664) in the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database (2010-2017) were evaluated. Cox regression models and competitive risk models were built to assess the effect of RT on the risk of CRC-associated death. Potential interactions between RT and stratified variables including age, sex, and tumor location were examined by multiplicative models. Compared with AC patients, SR patients had the worst overall survival (OS) among 3 subtypes of CRC (log-rank test, p < 0.001). Compared with patients who did not receive radiotherapy, RT was associated with a 1.09-fold (HR = 1.09, 95%[CI]: 1.03, 1.15) elevated risk of death among AC patients. In the SR group, RT significantly reduced the risk of death by 39% (HR = 0.61, 95%[CI]: 0.39-0.95). However, RT did not appear to independently influence survival in the MC group (HR = 0.96, 95%[CI]: 0.77, 1.21). In the subgroup analysis, tumor location (colon and rectum) significantly modified the association between RT and the risk of death among the AC and SR patients (p for interaction < 0.05). SR patients exhibited a worse OS (overall survival) than AC patients, and the effect of RT varied according to CRC histological subtypes. This can ultimately lead to more personalized and effective treatment strategies for CRC patients.

Prognostic differences in grading and metastatic lymph node pattern in patients with small bowel neuroendocrine tumors

PURPOSE

Neuroendocrine tumors of the small intestine (si-NET) describe a heterogenous group of neoplasms. Based on the Ki67 proliferation index si-NET are divided into G1 (Ki67 < 2%), G2 (Ki67 3-20%) and rarely G3 (Ki67 > 20%) tumors. However, few studies evaluate the impact of tumor grading on prognosis in si-NET. Moreover, si-NET can form distinct lymphatic spread patterns to the mesenteric root, aortocaval lymph nodes, and distant organs. This study aims to identify prognostic factors within the lymphatic spread patterns and grading.

METHODS

Demographic, pathological, and surgical data of 208 (90 male, 118 female) individuals with si-NETs treated at Charité University Medicine Berlin between 2010 and 2020 were analyzed retrospectively.

RESULTS

A total of 113 (54.5%) specimens were defined as G1 and 93 (44.7%) as G2 tumors. Interestingly, splitting the G2 group in two subgroups: G2 low (Ki67 3-9%) and G2 high (Ki67 10-20%), displayed significant differences in overall survival (OS) (p = 0.008) and progression free survival (PFS) (p = 0.004) between these subgroups. Remission after surgery was less often achieved in patients with higher Ki67 index (> 10%). Lymph node metastases (N +) were present in 174 (83.6%) patients. Patients with isolated locoregional disease showed better PFS and OS in comparison to patients with additional aortocaval and distant lymph node metastases.

CONCLUSION

Lymphatic spread pattern influences patient outcome. In G2 tumors, low and high grading shows heterogenous outcome in OS and PFS. Differentiation within this group might impact follow-up, adjuvant treatment, and surgical strategy.

Development of a Deep Learning Model for Malignant Small Bowel Tumors Survival: A SEER-Based Study

Background This study aims to explore a deep learning (DL) algorithm for developing a prognostic model and perform survival analyses in SBT patients. Methods The demographic and clinical features of patients with SBTs were extracted from the Surveillance, Epidemiology and End Results (SEER) database. We randomly split the samples into the training set and the validation set at 7:3. Cox proportional hazards (Cox-PH) analysis and the DeepSurv algorithm were used to develop models. The performance of the Cox-PH and DeepSurv models was evaluated using receiver operating characteristic curves, calibration curves, C-statistics and decision-curve analysis (DCA). A Kaplan−Meier (K−M) survival analysis was performed for further explanation on prognostic effect of the Cox-PH model. Results The multivariate analysis demonstrated that seven variables were associated with cancer-specific survival (CSS) (all p < 0.05). The DeepSurv model showed better performance than the Cox-PH model (C-index: 0.871 vs. 0.866). The calibration curves and DCA revealed that the two models had good discrimination and calibration. Moreover, patients with ileac malignancy and N2 stage disease were not responding to surgery according to the K−M analysis. Conclusions This study reported a DeepSurv model that performed well in CSS in SBT patients. It might offer insights into future research to explore more DL algorithms in cohort studies.

Comparison of 4 lymph node staging systems for the prognostic prediction of esophagogastric junction adenocarcinoma with ≤15 retrieved lymph nodes

BACKGROUND

Directly applying the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) staging system to evaluate the prognosis of patients with esophagogastric junction adenocarcinoma (AEG) might lead to under-staging, when insufficient lymph nodes were retrieved during surgery. The prognostic value of 4 lymph nodes staging systems, 8th AJCC TNM N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and negative lymph nodes (NLN), in AEG patients having ≤15 retrieved lymph nodes were compared.

METHODS

869 AEG patients diagnosed between 2004 and 2012 with ≤15 retrieved lymph nodes were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were conducted to assess the association of cancer-specific survival (CSS) and overall survival (OS) with 8th AJCC TNM N stage, LNR, LODDS, and NLN respectively. Predictive survival ability was assessed and compared using linear trend χ2 score, likelihood ratio (LR) test, Akaike information criterion (AIC), Harrell concordance index (C-index), and Receiver Operative Curve (ROC).

RESULTS

The N stage, LNR, LODDS, and NLN were all independent prognostic predictors for CSS and OS in multivariate Cox models. Comparatively, LODDS demonstrated higher linear trend χ2 score, LR test score, C-index and integrated area under the curve (iAUC) value, and lower AIC in CSS compared to the other three systems. Moreover, for patients without regional lymph node metastasis, NLN showed higher C-index and lower AIC.

CONCLUSIONS

LODDS showed better predictive performance than N, LNR, and NLN among patients with node-positive patients while NLN performed better in node-negative patients. A combination of LODDS and NLN has the potential to provide more prognostic information than the current AJCC TNM classification.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

How to Manage Small Intestine (Jejunal and Ileal) Neuroendocrine Neoplasms Presenting with Liver Metastases?

PURPOSE OF REVIEW

Small intestinal neuroendocrine neoplasms (siNENs) are slowly growing tumours with a low malignant potential. However, more than half of the patients present with distant metastases (stage IV) and nearly all with locoregional lymph node (LN) metastases at the time of surgery. The value of locoregional treatment is discussed controversially.

RECENT FINDINGS

In stage I to III disease, locoregional surgery was currently shown to be curative prolonging survival. In stage IV disease, surgery may prolong survival in selected patients with the chance to cure locoregional disease besides radical/debulking liver surgery. It may improve the quality of life and may prevent severe local complications resulting in a state of chronic malnutrition and severe intestinal ischaemia or bowel obstruction. Locoregional tumour resection offers the opportunity to be curative or to focus therapeutically on liver metastasis, facilitating various other therapeutic modalities. Risks and benefits of the surgical intervention need to be balanced individually.

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.

Role of Removed Lymph Nodes on the Prognosis of M0 Small-Bowel Neuroendocrine Tumors: a Propensity Score Matching Analysis from SEER Database

BACKGROUND

Current studies on the number of removed lymph nodes (LNs) and their prognostic value in small-bowel neuroendocrine tumors (SBNETs) are limited. This study aimed to clarify the prognostic value of removed LNs for SBNETs.

METHODS

SBNET patients without distant metastasis from 2004 to 2017 in the SEER database were included. The optimal cutoff values of examined LNs (ELNs) and negative LNs (NLNs) were calculated by the X-tile software. Propensity score matching (PSM) was done to match patients 1:1 on clinicopathological characteristics between the two groups. The Kaplan-Meier method with log-rank test and multivariable Cox proportional-hazards regression model were used to evaluate the prognostic effect of removed LNs.

RESULTS

The cutoff values of 14 for ELNs and 9 for NLNs could well distinguish patients with different prognoses. After 1:1 PSM, the differences in clinicopathological characteristics between the two groups were significantly reduced (all P > 0.05). Removal of more than one LN significantly improved the prognosis of the patients (P < 0.001). The number of lymphatic metastasis in the sufficiently radical resection group (SRR, 3.74 ± 3.278, ELN > 14 and NLN > 9) was significantly more than that in the insufficiently radical resection group (ISRR, 2.72 ± 3.19, ELN < 14 or NLN < 9). The 10-year overall survival (OS) of the SRR was significantly better than that of the ISRR (HR = 1.65, P = 0.001, 95% CI: 1.24-2.19).

CONCLUSION

Both ELNs and NLNs can well predict the OS of patients. Systematic removal of more than 14 LNs and more than 9 NLNs can increase the OS of SBNET patients.