Modified AJCC staging of gastric neuroendocrine carcinoma based on T staging can improve the capacity of prognosis assessment

Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients

BACKGROUND

Lymph node ratio (LNR) was demonstrated to play a crucial role in the prognosis of many tumors. However, research concerning the prognostic value of LNR in postoperative gastric neuroendocrine neoplasm (NEN) patients was limited.

AIM

To explore the prognostic value of LNR in postoperative gastric NEN patients and to combine LNR to develop prognostic models.

METHODS

A total of 286 patients from the Surveillance, Epidemiology, and End Results database were divided into the training set and validation set at a ratio of 8:2. 92 patients from the First Affiliated Hospital of Soochow University in China were designated as a test set. Cox regression analysis was used to explore the relationship between LNR and disease-specific survival (DSS) of gastric NEN patients. Random survival forest (RSF) algorithm and Cox proportional hazards (CoxPH) analysis were applied to develop models to predict DSS respectively, and compared with the 8th edition American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging.

RESULTS

Multivariate analyses indicated that LNR was an independent prognostic factor for postoperative gastric NEN patients and a higher LNR was accompanied by a higher risk of death. The RSF model exhibited the best performance in predicting DSS, with the C-index in the test set being 0.769 [95% confidence interval (CI): 0.691-0.846] outperforming the CoxPH model (0.744, 95%CI: 0.665-0.822) and the 8th edition AJCC TNM staging (0.723, 95%CI: 0.613-0.833). The calibration curves and decision curve analysis (DCA) demonstrated the RSF model had good calibration and clinical benefits. Furthermore, the RSF model could perform risk stratification and individual prognosis prediction effectively.

CONCLUSION

A higher LNR indicated a lower DSS in postoperative gastric NEN patients. The RSF model outperformed the CoxPH model and the 8th edition AJCC TNM staging in the test set, showing potential in clinical practice.

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.

Trends of incidence and prognosis of gastric neuroendocrine neoplasms: a study based on SEER and our multicenter research

BACKGROUND

To investigate the recent epidemiological trends of gastric neuroendocrine neoplasms (GNENs) and establish a new tool to estimate the prognosis of gastric neuroendocrine carcinoma (GNEC) and gastric neuroendocrine tumor (GNET).

METHODS

Nomograms were established based on a retrospective study on patients diagnosed with GNENs from 1975 to 2016 in Surveillance, Epidemiology and End Results database. External validation was performed among 246 GNENs patients in Jiangsu province to verify the discrimination and calibration of the nomograms.

RESULTS

The age-adjusted incidence of GNENs has increased from 0.309 to 6.149 per 1,000,000 persons in the past 4 decades. Multivariate analysis indicated independent prognostic factors for both GNEC and GNET including age, distant metastasis and surgical intervention (P < 0.05). In addition, T, N staging and grade were significantly associated with survival of GNEC, while size was a predictor for GNET (P < 0.05). The C-indexes of the nomograms were 0.840 for GNEC and 0.718 for GNET, which were higher than those of the 8th AJCC staging system (0.773 and 0.599). Excellent discrimination was observed in the validation cohorts (C-index of nomogram vs AJCC staging for GNEC: 0.743 vs 0.714; GNET: 0.945 vs 0.927). Survival rates predicted by nomograms were close to the actual survival rates in the calibration plots in both training and validation sets.

CONCLUSIONS

The incidence of the GNENs is increasing steadily in the past 40 years. We established more excellent nomograms to predict the prognosis of GNENs than traditional staging system, helping clinicians to make tailored decisions.