Resection of the Primary Tumor Improves the Survival of Patients With Stage IV Gastric Neuroendocrine Carcinoma

Machine Learning-Based Real-Time Survival Prediction for Gastric Neuroendocrine Carcinoma

BACKGROUND

This study aimed to develop a dynamic survival prediction model utilizing conditional survival (CS) analysis and machine learning techniques for gastric neuroendocrine carcinomas (GNECs).

PATIENTS AND METHODS

Data from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2015) were analyzed and split into training and validation groups (7:3 ratio). CS profiles for patients with GNEC were examined in the full cohort. We utilized random survival forests (RSFs) and least absolute shrinkage and selection operator (LASSO) regression, alongside stepwise Cox regression, for variable selection. A CS-based nomogram was developed on the basis of key prognostic factors, followed by risk stratification and model validation.

RESULTS

We included 654 patients with GNEC in our study, with 457 assigned to the training set and 197 to the validation set. The CS analysis demonstrated that the probability of achieving 5-year CS improved from 48% immediately after diagnosis to 68%, 81%, 88%, and 94% after surviving an additional year (i.e., at 1, 2, 3, and 4 years, respectively). Through the use of RSFs and LASSO regression, combined with multivariable regression analysis, we identified the optimal combination of prognostic factors, which included age, tumor grade, tumor stage, surgery, and chemotherapy. Utilizing these prognostic indicators, we successfully developed a nomogram model that incorporated CS and effectively stratified these patients by risk. Subsequent performance analyses further validated the superior efficacy of the nomogram.

CONCLUSIONS

Our study highlights the value of CS in GNEC prognosis. The nomogram offers dynamic, individualized survival predictions, supporting personalized treatment strategies.

Successful conversion surgery after comprehensive therapy in a patient with MSI-H but pMMR metastatic gastric mixed adenoneuroendocrine carcinoma: a case report and literature review

Gastric mixed adenoneuroendocrine carcinoma (MANEC) is a rare and highly aggressive malignancy characterized by both exocrine and neuroendocrine components. Treatment options for metastatic cases are limited, with typical therapeutic approaches involving a combination of chemotherapy and immunotherapy. A 68-year-old male with metastatic gastric MANEC was treated with targeted therapy, immunotherapy, and chemotherapy, including S-1, apatinib, cadonilimab, and paclitaxel. After six cycles, the liver metastases resolved completely, and the primary tumor achieved partial remission, leading to conversion surgery. The patient underwent a radical D2 gastrectomy with R0 resection, including proximal gastrectomy, splenectomy, omentectomy, and esophagogastric anastomosis, along with radiofrequency ablation of liver metastases. Postoperative pathology confirmed the disappearance of liver metastases but revealed residual adenocarcinoma in the primary gastric lesion and neuroendocrine components in the perigastric lymph nodes. The patient was discharged seven days post-surgery. Five months postoperatively, new liver metastases were detected, exhibiting neuroendocrine differentiation. The patient was subsequently treated with a maintenance regimen of S-1 and pembrolizumab. This case highlights the significant heterogeneity of gastric MANEC and the challenges in managing such cases. While conversion surgery can be effective in certain contexts, the high likelihood of postoperative recurrence and metastasis, particularly in neuroendocrine components, necessitates cautious consideration. Further research is needed to evaluate the long-term benefits of conversion surgery in metastatic gastric MANEC and to develop tailored therapeutic strategies.

Synergizing traditional CT imaging with radiomics: a novel model for preoperative diagnosis of gastric neuroendocrine and mixed adenoneuroendocrine carcinoma

Objective

To develop diagnostic models for differentiating gastric neuroendocrine carcinoma (g-NEC) and gastric mixed adeno-neuroendocrine carcinoma (g-MANEC) from gastric adenocarcinoma (g-ADC) based on traditional contrast enhanced CT imaging features and radiomics features.

Methods

We retrospectively analyzed 90 g-(MA)NEC (g-MANEC and g-NEC) patients matched 1:1 by T-stage with 90 g-ADC patients. Traditional CT features were analyzed using univariable and multivariable logistic regression. Tumor segmentation and radiomics features extraction were performed with Slicer and PyRadiomics. Feature selection was conducted through univariable analysis, correlation analysis, LASSO, and multivariable stepwise logistic. The combined model incorporated clinical and radiomics predictors. Diagnostic performance was assessed with ROC curves and DeLong's test. The models' diagnostic efficacy was further validated in subgroup of g-NEC vs. g-ADC and g-MANEC vs. g-ADC cases.

Results

Tumor necrosis and lymph node metastasis were independent predictors for differentiating g-(MA)NEC from g-ADC (P < 0.05). The clinical model's AUC was 0.700 (training) and 0.667(validation). Five radiomics features were retained, with the radiomics model showing AUC of 0.809 (training) and 0.802 (validation). The combined model's AUCs were 0.853 (training) and 0.812 (validation), significantly outperforming the clinical model (P < 0.05). Subgroup analysis revealed that the combined model exhibited acceptable performance in differentiating g-NEC from g-ADC and g-MANEC from g-ADC, with AUC of 0.887 and 0.823 in the training cohort and 0.852 and 0.762 in the validation cohort.

Conclusion

A combined model based on traditional CT imaging and radiomic features provides a non-invasive and effective preoperative diagnostic method for differentiating g-(MA)NEC from g-ADC.

Perioperative chemotherapy improves survival of patients with locally advanced diffuse gastric cancer

BACKGROUND

Whether patients with diffuse gastric cancer, which is insensitive to chemotherapy, can benefit from neoadjuvant or adjuvant chemotherapy has long been controversial.

AIM

To investigate whether perioperative chemotherapy can improve survival of patients with locally advanced diffuse gastric cancer.

METHODS

A total of 2684 patients with locally advanced diffuse gastric cancer from 18 population-based cancer registries in the United States were analyzed.

RESULTS

Compared with surgery alone, perioperative chemotherapy improved the prognosis of patients with locally advanced gastric cancer. Before stabilized inverse probability of treatment weighting (IPTW), the median overall survival (OS) times were 40.0 months and 13.0 months (P < 0.001), respectively. After IPTW, the median OS times were 33.0 months and 17.0 months (P < 0.001), respectively. Neoadjuvant chemotherapy did not improve the prognosis of patients with locally advanced gastric cancer compared with adjuvant chemotherapy after IPTW. After IPTW, the median OS times were 38.0 months in the neoadjuvant chemotherapy group and 42.0 months in the adjuvant chemotherapy group (P = 0.472).

CONCLUSION

Patients with diffuse gastric cancer can benefit from perioperative chemotherapy. There was no significant difference in survival between patients who received neoadjuvant chemotherapy and those who received adjuvant chemotherapy.

Favorable response to PD-1 inhibitor plus chemotherapy as first-line treatment for metastatic gastric mixed neuroendocrine-non-neuroendocrine tumor: a case report

Gastric mixed neuroendocrine-non-neuroendocrine tumor (MiNEN), a rare malignancy, currently has no standard treatment. Here, we report a patient with pathologically confirmed gastric MiNEN following radical surgery with rapid postoperative distant tumor recurrence. Immunofluorescence results suggested intensive lymphocyte infiltration in the tumor. The programmed death receptor ligand 1 (PD-L1) immunohistochemistry 22C3 pharmDx assay showed tumor proportion score was 5% and combined positive score was 10. After 6 cycles of treatment with etoposide and cisplatin in combination with toripalimab, efficacy was assessed as a complete response. Our report shows that for gastric MiNEN patients with high expression of PD-L1, chemotherapy combined with immune checkpoint inhibitors may achieve more significant efficacy.

Resection of the primary tumor improves the prognosis of gastrointestinal neuroendocrine neoplasms with liver metastases: mutual validation based on SEER database and institutional data

BACKGROUND

Gastrointestinal Neuroendocrine Neoplasms (GI-NENs) often result in liver metastases, and the role of Primary Tumor Resection (PTR) in managing GI-NENs with liver metastases (GI-NENLM) is still debated. This study aimed to investigate the potential benefits of PTR in treating GI-NENLM by analyzing data from the Surveillance, Epidemiology, and End Results Program (SEER) and the First Affiliated Hospital of Sun Yat-sen University (FAH).

METHODS

The SEER Registry 17 database and the FAH clinical pathology database were used to collect clinicopathology data for GI-NENLM diagnosed between 2010 and 2019 and between 2011 and 2022, respectively. Propensity score matching (PSM) was used to match the clinicopathological characteristics of patients from both cohorts. Inverse probability weighting (IPTW) was used to weigh the PTR and non-PTR groups. The primary endpoint was overall survival (OS).

RESULTS

After matching, 155 patients from the SEER database were matched to the FAH cohort. PTR was significantly associated with better prognosis in PSM-matched/unmatched SEER cohorts (P < 0.01) and in the FAH cohort even after eliminating selection bias using IPTW (p < 0.01). Subgroup analysis suggests that the cohort consisting of patients aged 55 years or older, individuals with colorectal primary tumors, those at the T1 disease stage, and those without extrahepatic metastasis may potentially benefit from PTR. Interaction analysis showed no significant interaction between PTR and other clinical and pathological factors except for age.

CONCLUSION

The employment of PTR in patients with GI-NENLM is significantly correlated with individual survival benefits. We support performing PTR on carefully evaluated patients.

Surgical treatment of stage IV gastroenteropancreatic neuroendocrine carcinoma: Experience and outcomes in the United States

BACKGROUND AND OBJECTIVES

Surgery for metastatic gastroenteropancreatic neuroendocrine carcinoma (GEP-NEC) has not been well-studied. This retrospective cohort study describes patients in the United States with stage IV GEP-NEC and their survival outcomes segregated by surgery.

METHODS

Patients diagnosed with stage IV GEP-NEC from 2004 to 2017 in the National Cancer Database were categorized into three groups: no surgery, primary site or metastatic site ("single-site") surgery, and primary site and metastatic site ("multisite") surgery. Factors associated with surgical treatment were identified, and risk-adjusted overall survival of each group was compared.

RESULTS

Of 4171 patients included, 958 (23.0%) underwent single-site surgery and 374 (9.0%) underwent multisite surgery. The strongest predictor of surgery was primary tumor type. Compared with no surgery, the risk-adjusted mortality reduction associated with single-site surgery ranged from 63% for small bowel (HR = 0.37, 0.23-0.58, p < 0.001) NEC to 30% for colon and appendix NEC (HR = 0.70, 0.61-0.80, p < 0.001), while the mortality reduction associated with multisite surgery ranged from 77% for pancreas NEC (HR = 0.23, 0.17-0.33, p < 0.001) to 48% for colon and appendix NEC (HR = 0.52, 0.44-0.63, p < 0.001).

CONCLUSIONS

We observed an association between extent of surgical intervention and overall survival for patients with stage IV GEP-NEC. Surgical resection should be further investigated as a treatment option for highly-selected patients with this aggressive disease.

A novel nomogram and risk stratification system predicting the cancer-specific survival of patients with gastric neuroendocrine carcinoma: a study based on SEER database and external validation

BACKGROUND

Gastric neuroendocrine carcinoma (GNEC) is a rare histology of gastric cancer. The retrospective study was designed to construct and validate a nomogram for predicting the cancer-specific survival (CSS) of postoperative GNEC patients.

METHODS

Data for 28 patients from the Hangzhou TCM Hospital were identified as the external validation cohort. A total of 1493 patients were included in the SEER database and randomly assigned to the training group (1045 patients) and internal validation group (448 patients). The nomogram was constructed using the findings of univariate and multivariate Cox regression studies. The model was evaluated by consistency index (C-index), calibration plots, and clinical net benefit. Finally, the effect between the nomogram and AJCC staging system was compared by net reclassification index (NRI) and integrated discrimination improvement (IDI).

RESULTS

Age, gender, grade, T stage, N stage, metastasis, primary site, tumor size, RNE, and chemotherapy were incorporated in the nomogram. The C-indexes were 0.792 and 0.782 in the training and internal verification sets. The 1-, 3-, and 5-year CSS predicted by the nomogram and actual measurements had good agreement in calibration plots. The 1-, 3-, and 5-year NRI were 0.21, 0.29, and 0.37, respectively. The 1-, 3-, and 5-year IDI values were 0.10, 0.12, and 0.13 (P < 0.001), respectively. In 1-, 3-, and 5-year CSS prediction using DCA curves, the nomogram outperformed the AJCC staging system. The nomogram performed well in both the internal and external validation cohorts.

CONCLUSION

We developed and validated a nomogram to predict 1-, 3-, and 5-year CSS for GNEC patients after surgical resection. This well-performing model could help doctors enhance the treatment plan.