The survival outcome in proximal and distal gastric neuroendocrine carcinoma - A SEER-based competing risk nomogram
Research Square
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Objective The occurrence of gastric neuroendocrine carcinoma (GNEC) is on the rise, and its prognosis is extremely poor. We compared survival outcomes between distal and proximal GNEC and developed a nomogram incorporating tumor site to enhance personalized management for patients of GNEC. Methods 1807 patients were divided them into DGNEC and PGNEC groups. We performed analyses by using propensity score matching (PSM) and Fine-Gray competing risk methods. A predictive nomogram about prognosis of GNEC was constructed and validated. Results The cumulative incidence of cancer-specific death (CSD) in DGNEC group was lower than that in PGNEC group. Subgroup analysis showed lower CSD of DGNEC in male, female, tumor size (≤ 2 cm, 2 < tumor size ≤ 5 cm, > 5 cm and unkown), grade stage I-II, and AJCC stage I-, chemotherapy yes or none, surgery yes or none groups (p < 0.05). Multivariate analysis revealed a significant association between PGNEC and CSD (HR, 1.4; 95% CI, 1.13–1.73; P = 0.02). The independent predictors of CSD in patients with GNEC were primary site, gender, age, tumor size, AJCC stage, T stage, N stage, grade stage, and surgery. A predictive model based on multivariate analysis was constructed to estimate the probability of CSD at 1-, 3-, and 5- year. The calibration curves demonstrated excellent consistency between the predicted and observed probabilities of the CSD. Conclusion Patients with DGNEC have a better prognosis than those with PGNEC. The model exhibits strong predictive capability for these patients.
Bibliographic Details
Springer Science and Business Media LLC
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