Epidemiological and survival outcomes of neuroendocrine carcinoma of the breast: a SEER data analysis

Primary neuroendocrine tumor of the breast: A case report

Primary neuroendocrine neoplasm of the breast (PNENB) is a rare subtype of breast cancer, accounting for <1% of all breast tumors. The morphological features of PNENB are similar to those of neuroendocrine tumors originating in the lungs or gastrointestinal system, with tumor cells exhibiting the strong expression of neuroendocrine markers, including chromogranin A and synaptophysin. Since this type of cancer was first reported, the definition, classification and diagnostic criteria of PNENB have evolved and changed. However, accurate diagnostic criteria and standard treatment guidelines are lacking. The present report describes a specific case of PNENB, which was consistent with the morphological and molecular features of other cases in most previous studies. In addition, the current body of literature on PNENB, including its development, diagnosis, molecular features, treatment and prognosis is reviewed.

Comparison of clinicopathological features and survival analysis between esophageal neuroendocrine carcinoma and esophageal squamous cell carcinoma based on the SEER database, alongside nomogram analysis for esophageal neuroendocrine carcinoma

Background

Esophageal neuroendocrine carcinoma (ENEC) is a rare subtype of esophageal cancer (EC). It presents distinctive clinical and pathological features in comparison to esophageal squamous cell carcinoma (ESCC). To better elucidate the disparities between the two and establish a prognostic prediction model for ENEC, we conducted this study.

Methods

Data of ENEC and ESCC patients (1975 to 2016) were extracted from the Surveillance, Epidemiology and End Results (SEER) database. Patients with a confirmed pathological diagnosis of ENEC and ESCC were enrolled in the study. The Chi-square test was employed to compare categorical variables, and the median survival time was analyzed using the Kaplan-Meier curve. Training and validation groups were randomly assigned at a ratio of 7:3. Factors with a significance level of <0.05 in the multifactor regression model as well as age were integrated into the nomogram model. Concordance index (C-index), calibration curves, and decision curve analyses (DCA) were generated for model validation.

Results

This study encompassed a total of 737 ENEC patients and 29,420 ESCC. Compared to ESCC, ENEC patients had higher probability of liver metastasis (13.8% vs. 1.9%, P<0.001), poor differentiation (68.0% vs. 37.1%, P<0.001), and late SEER stage (52.8% vs. 26.9%, P<0.001). Patients who received either surgery, radiotherapy (RT), or chemotherapy had a significantly longer disease-specific survival (DSS) and overall survival (OS) (all P<0.001). After propensity score matching (PSM), ENEC patients were associated with shorter DSS (7.0 months vs. not reached, P<0.0001) and OS (7.0 vs. 12.0 months, P<0.0001) compared to ESCC. Race, SEER stage, surgery, RT, and chemotherapy were identified as predictors of DSS and were incorporated into the nomogram model together with age. The validation of the model using C-index (0.751 and 0.706, respectively) and calibration curves reflected the better discrimination power of the model. In addition, DCA supported the favorable potential clinical effect of the predictive model. Lastly, a risk classification based on the nomogram also verified the reliability of the model.

Conclusions

ENEC and ESCC exhibit distinct clinicopathological features. Patients with ENEC experience significantly poorer survival outcomes compared to those with ESCC. Surgical intervention, radiation therapy, and chemotherapy significantly improve OS and DSS for ENEC patients. The nomogram prediction model, constructed based on age, race, stage, and treatment regimen, demonstrates accurate and effective predictive capabilities for prognostic factors in ENEC patients.