Distinguishing second primary tumors from local recurrence in type 1 gastric neuroendocrine tumors: a risk-stratified management strategy

Q: Why is it challenging to distinguish local recurrence from second primary tumors in type 1 gastric gNETs?

Post-resection lesions in type 1 gNETs are often multifocal and small, making it difficult to separate de novo/synchronously overlooked lesions from lesions arising at the original resection scar.

Q: Which factors independently predicted SPT-related risk and disease progression?

Lymphovascular invasion (LVI) and submucosal invasion were identified as independent predictors, and they formed the basis of the risk-stratification nomogram.

Sep 22, 2026

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Type 1 gastric neuroendocrine tumors (gNETs) show high recurrence rates, yet separating true local recurrence from second primary tumors (SPTs) remains difficult. A retrospective analysis of 70 patients evaluated endoscopic features of SPTs, derived independent risk factors, and built a risk-stratification model. Post-resection lesions were mainly SPTs (54.3% vs 8.6%). Smaller size and flat morphology characterized SPTs. Lymphovascular invasion and submucosal invasion predicted progression, enabling tailored surveillance and intensified monitoring for high-risk patients.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages13

Reading Time33 min

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Abstract

Background

Objectives

Methods

Results

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Keywords

Surgical Endoscopy (2026) 40:5207–5219 [https://doi.org/10.1007/s00464-026-12749-x](https://doi.org/10.1007/s00464-026-12749-x) and Other Interventional Techniques Distinguishing second primary tumors from local recurrence in type 1 gastric neuroendocrine tumors: a risk‑stratified management strategy Jing Jin1,2 · Hejun Zhang1,2 · Shigang Ding1,2 · Jing Zhang1,2 Received: 17 January 2026 / Accepted: 8 March 2026 / Published online: 23 March 2026 © The Author(s) 2026 Abstract Background Type 1 gastric neuroendocrine tumors (gNETs) exhibit high recurrence rates. However, distinguishing true local recurrence from second primary tumors (SPTs) remains challenging. Objectives To characterize the endoscopic features of SPTs, identify independent risk factors, and develop a risk-stratification model to guide personalized surveillance. Methods We retrospectively analyzed 70 patients with type 1 gNETs at Peking University Third Hospital between May 2015 and February 2025. SPTs were strictly defined as lesions detected outside the initial resection scar during follow-up, whereas local recurrence was defined as lesions within the scar. Logistic regression was used to identify independent risk factors. A nomogram was constructed, and disease-free survival (DFS) was analyzed. Results During a median follow-up of 17 months, SPTs were identified in 38 patients (54.3%), whereas local recurrence occurred in only 6 (8.6%), confirming that post-resection lesions are predominantly SPTs. Morphologically, SPTs were significantly smaller than primary tumors (0.4 cm vs. 0.5 cm, P < 0.001) and more frequently exhibited flat morphology (36.3% vs. 17.6%, P = 0.007). Lymphovascular invasion (LVI) (OR = 10.61, P = 0.035) and submucosal invasion (OR = 4.69, P = 0.006) were identified as independent predictors. A risk-stratification nomogram based on these factors showed good discriminatory power (AUC = 0.758) . Based on these factors, patients were stratified into low- , medium- , and high-risk groups. The high-risk group (with LVI and submucosal invasion) demonstrated a rapid disease progression, with no patients remaining disease-free at 3 years (P = 0.015) . Conclusions Surveillance lesions in type 1 gNETs are primarily SPTs characterized by subtle, flat morphology, necessitating high-quality endoscopic observation. The proposed risk-stratification model based on LVI and invasion depth effectively identifies high-risk patients, justifying intensified monitoring for this subgroup while reducing the burden for low-risk individuals. Keywords Type 1 gNETs · Second primary tumors · Recurrence · Risk stratification · Surveillance strategy Gastric neuroendocrine neoplasms (gNENs), are rare epithelial malignancies characterized by endocrine or neuronal differentiation [1, 2]. According to the World Health Organization (WHO) classification [3], they are categorized into well-differentiated gastric neuroendocrine tumors (gNETs) and poorly differentiated gastric neuroendocrine carcinomas (gNECs) based on their molecular and histological * Jing Zhang [sihuizhang@sina.com](sihuizhang@sina.com) 1 Department of Gastroenterology, Peking University Third Hospital, Beijing 100191, China 2 Beijing Key Laboratory for Helicobacter Pylori Infection and Upper Gastrointestinal Diseases (BZ0371), Beijing 100191, China characteristics [4] . Type 1 gNETs, accounting for approximately 75%-80% of all gNET cases, are typically associated with chronic atrophic gastritis and autoimmune gastritis [5] . Type 1 gNETs are usually asymptomatic, and thus are most often detected during routine endoscopic evaluations or screening for anemia or autoimmune disorders [6, 7] . The biologically indolent nature of type 1 gNETs confersan excellent 5-year survival rate, estimated at 90-100%[5, 8], these tumors present a unique clinical challenge due to multifocal, small and tendency to reoccur over time. The pathogenesis of type 1 gNETs is driven by sustained hyperg

FAQs

Why is it challenging to distinguish local recurrence from second primary tumors in type 1 gastric gNETs?

Post-resection lesions in type 1 gNETs are often multifocal and small, making it difficult to separate de novo/synchronously overlooked lesions from lesions arising at the original resection scar.

How were SPTs and local recurrence defined in the study?

SPTs were strictly defined as lesions detected outside the initial resection scar during follow-up, while local recurrence was defined as lesions within the scar.

Which factors independently predicted SPT-related risk and disease progression?

Lymphovascular invasion (LVI) and submucosal invasion were identified as independent predictors, and they formed the basis of the risk-stratification nomogram.

Sep 22, 2026

Upload by Miles