De-escalating chemotherapy for stage I–II gastric neuroendocrine carcinoma? A real-world competing risk analysis

Abstract

Abstract Background The role of adjuvant chemotherapy in gastric neuroendocrine neoplasms (GNEC) has not been well clarified yet. The study was designed to investigate the potential effect of adjuvant chemotherapy in stage I–II GNEC patients and construct a predictive nomogram. Method Stage I–II GNEC patients were included in the Surveillance, Epidemiology, and End Results (SEER) database and divided into chemotherapy and no-chemotherapy groups. We used Kaplan–Meier survival analyses, propensity score matching (PSM), and competing risk analyses. The predictive nomogram was then built and validated. Results Four hundred four patients with stage I–II GNEC were enrolled from the SEER database while 28 patients from Hangzhou TCM Hospital were identified as the external validation cohort. After PSM, similar 5-year cancer-specific survival was observed in two groups. The outcomes of competing risk analysis indicated a similar 5-year cumulative incidence of cancer-specific death (CSD) between the two cohorts (35.4% vs. 31.4%, p = 0.731). And there was no significant relation between chemotherapy and CSD in the multivariate competing risks regression analysis (HR, 0.79; 95% CI, 0.48–1.31; p = 0.36). Furthermore, based on the variables from the multivariate analysis, a competing event nomogram was created to assess the 1-, 3-, and 5-year risks of CSD. The 1-, 3-, and 5-year area under the receiver operating characteristic curve (AUC) values were 0.770, 0.759, and 0.671 in the training cohort, 0.809, 0.782, and 0.735 in the internal validation cohort, 0.786, 0.856, and 0.770 in the external validation cohort. Furthermore, calibration curves revealed that the expected and actual probabilities of CSD were relatively consistent. Conclusion Stage I–II GNEC patients could not benefit from adjuvant chemotherapy after surgery. De-escalation of chemotherapy should be considered for stage I–II GNEC patients. The proposed nomogram exhibited excellent prediction ability.