Clinicopathological characteristics and prognosis of 232 patients with poorly differentiated gastric neuroendocrine neoplasms

Deep learning radiomics analysis based on computed tomography for survival prediction in gastric neuroendocrine neoplasm: a multicenter study

Background

Survival prediction is crucial for patients with gastric neuroendocrine neoplasms (gNENs) to assess the treatment programs and may guide personalized medicine. This study aimed to develop and evaluate a deep learning (DL) radiomics model to predict the overall survival (OS) in patients with gNENs.

Methods

The retrospective analysis included 162 consecutive patients with gNENs from two hospitals, who were divided into a training cohort, internal validation cohort (The First Affiliated Hospital of Zhengzhou University; n=108), and an external validation cohort (The Henan Cancer Hospital; n=54). DL radiomics analysis was applied to computed tomography (CT) images of the arterial phase and venous phase, respectively. Based on pretreatment CT images, two DL radiomics signatures were developed to predict OS. The combined model incorporating the radiomics signatures and clinical factors was built through the multivariable Cox proportional hazards (CPH) method. The combined model was visualized into a radiomics nomogram for individualized OS estimation. Prediction performance was assessed with the concordance index (C-index) and the Kaplan-Meier (KM) estimator.

Results

The DL-based radiomics signatures based on two phases were significantly correlated with OS in the training (C-index: 0.79-0.92; P<0.01), internal validation (C-index: 0.61-0.86; P<0.01), and external validation (C-index: 0.56-0.75; P<0.01) cohorts. The combined model integrating radiomics signatures with clinical factors showed a significant improvement in predictive performance compared to the clinical model in the training (C-index: 0.86 vs. 0.80; P<0.01), internal validation (C-index: 0.77 vs. 0.71; P<0.01), and external validation (C-index: 0.71 vs. 0.66; P<0.01) cohorts. Moreover, the combined model classified patients into high-risk and low-risk groups, and the high-risk group had a shorter OS compared to the low-risk group in the training cohort [hazard ratio (HR) 3.12, 95% confidence interval (CI): 2.34-3.93; P<0.01], which was validated in the internal (HR 2.51, 95% CI: 1.57-3.99; P<0.01) and external validation cohort (HR 1.77, 95% CI: 1.21-2.59; P<0.01).

Conclusions

DL radiomics analysis could serve as a potential and noninvasive tool for prognostic prediction and risk stratification in patients with gNENs.

Endoscopic features of gastric neuroendocrine carcinoma

BACKGROUND AND AIM

The endoscopic features of gastric neuroendocrine carcinoma (G-NEC) have not been clarified; therefore, they were investigated in relation to clinicopathological findings.

METHODS

Consecutive patients with G-NECs who had undergone endoscopic or surgical resection at our institution between January 2005 and March 2022 were included in this retrospective study. The endoscopic and clinicopathological findings of the lesions were analyzed to provide information of diagnostic value. In addition, cases of gastric neuroendocrine tumor (G-NET) and common-type gastric adenocarcinoma treated in the same study period were identified to compare the endoscopic findings between each G-NEC versus G-NET, and G-NEC versus common-type gastric adenocarcinoma. Patients with common-type gastric adenocarcinoma were matched for age, sex, tumor size, and depth of tumor invasion in 1:3 ratio.

RESULTS

Among 15 patients with 15 G-NECs, submucosal tumor-like marginal elevation (87%), adherent white coat (67%), and ulceration with a distinct border (60%) were characteristic endoscopic findings in white-light images. Magnifying narrow-band imaging endoscopy revealed an absent microsurface (MS) pattern plus disrupted irregular microvessel (MV) in five (71%) of seven cases with evaluable MS and MV patterns. The area with an absent MS pattern plus disrupted irregular MV corresponded to the histological finding of NEC component in all five cases. These endoscopic features were all significantly more frequent in G-NECs than G-NETs (n = 22) or common-type gastric adenocarcinomas (n = 45).

CONCLUSIONS

These endoscopic features should be taken into consideration to increase the index of suspicion and to improve the accuracy of target biopsies for G-NEC.

Differences in clinicopathology and prognosis between gastroesophageal junctional and gastric non-cardiac neuroendocrine carcinomas: a retrospective comparison study of consecutive 56 cases from a single institution in China

Gastric neuroendocrine carcinoma (NEC), including mixed neuroendocrine-non-neuroendocrine neoplasm (MiNEN), is uncommon and differences in clinicopathological features and outcomes of NEC arising in various gastric regions remain elusive. We investigated 56 consecutive NECs identified among 3961 gastrectomies performed at our center between 2005 and 2021. We then compared clinicopathological characteristics and prognosis between gastroesophageal junctional (GEJ) NECs (N=39) and gastric non-cardiac NECs (N=17). No significant difference was found between the two groups in age, gender, tumor size, mixed non-neuroendocrine carcinoma component, MiNEN, NEC type, metastatic NEC component in lymph nodes, tumor infiltrating lymphocyte, lymph node metastasis, lymphovascular or perineural invasion, intestinal metaplasia in adjacent non-neoplastic mucosa, and expression of P53, PD-L1, TTF-1, HER2, and Ki-67. However, compared to gastric non-cardiac NECs, GEJ NECs displayed a significantly higher frequency of prevalence (2.79% versus 0.66%), pT3-T4 (92.3% versus 64.7%), advanced pathological stage (IIb-IV) (76.9% versus 47.1%), and a significantly lower 5-year overall survival rate (46.1% versus 73.1%) (P<0.05). The GEJ location was the only independent risk factor for overall survival. In stage-stratified comparisons, patients with stage II GEJ NEC demonstrated a significantly lower 5-year survival rate than those with gastric non-cardiac NEC at the same stage. Compared to non-NECs matched for age, gender, tumor location, and pathological summary stage, GEJ NEC was associated with significantly worse prognosis. In conclusion, GEJ NEC showed deeper invasion, more advanced pathological stages, and worse prognosis than gastric non-cardiac NEC. The findings provide pathologic evidence for individualized management strategies for patients with GEJ NEC. Future studies with larger samples are needed.

Prognosis of patients with poorly differentiated gastric neuroendocrine neoplasms: a multi-center study in China

Background: The incidence of poorly differentiated gastric neuroendocrine neoplasms (G-NENs) has been increasing during the past decades. Methods: A total of 183 patients diagnosed with poorly differentiated G-NENs were enrolled from eight hospitals during 2010-2019 in China. All cases included have accepted abdominal surgery in tertiary hospitals. Result: T3 (HR: 2.66, p = 0.019), T4 (HR: 3.62, p = 0.005), stage IV (HR: 5.67, p < 0.001), vascular invasion (HR: 1.59, p = 0.048) were independent risk factors for poor prognosis of poorly differentiated G-NENs. In stratified analysis, for patients with stage III tumors, those treated with chemotherapy had significantly longer survival than those accepting surgery alone. Conclusion: T3/T4 stage, TNM stage IV and vascular invasion were independent negative prognostic factors for patients with poorly differentiated G-NENs. Patients with stage III tumors can benefit from chemotherapy. Highly selected patients with stage IV tumors may also benefit from surgery.

The Clinicopathological Features and Overall Survival of Patients With Gastric Neuroendocrine Carcinoma

OBJECTIVES

Gastric neuroendocrine carcinoma (GNEC) is a class of rare histological subtypes in gastric cancer (GC). This retrospective case-control study aimed to explore the clinicopathological features and overall survival (OS) of patients with GNEC.

METHODS

A large population of GNEC and intestinal-type GC (IGC) patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The 1:1 propensity score matching (PSM) analysis was initiated to adjust the confounders between GNEC and IGC cohorts. Kaplan-Meier (KM) plots with log-rank tests were used to compare the survival differences in GNEC versus IGC. Additionally, Cox proportional hazard regression models were adopted to characterize the prognostic factors relevant to OS of the GNEC patients.

RESULTS

An entity of 4596 patients were collected, including 3943 (85.8%) IGC patients and 653 (14.2%) GNEC patients. The PSM analysis well-balanced all confounders in GNEC versus IGC (all P > .05). The KM plots showed that GNEC had significantly superior OS to IGC both before and after PSM analysis. Before PSM, the median OS was 52 (33.6-70.4) months in GNEC versus 32 (29.3-34.7) months in IGC (P  =  .0015). After PSM, the median OS was 26 (18.3-33.7) months in GNEC versus 21 (17.7-24.3) months in IGC (P  =  .0039). Stratified analysis indicated that GNEC had superior survivals to IGC in early stage patients and those who received surgery. In Cox regression analysis, age ≥ 60, tumor size > 50 mm, stage II-IV, T2, and N3 were independent risk factors for the GNEC patients (hazard ratio [HR]>1, P < .05). By contrast, year 2010 to 2015, female, and surgery were independent protective factors for these patients (HR < 1, P < .05).

CONCLUSIONS

GNEC has unique clinicopathological features quite different from IGC and may have a superior survival to IGC in early stage patients. The prognostic factors identified here may assist the clinicians to more individually treat these patients.