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基于 SEER 数据库的近端和远端胃神经内分泌癌的比较。

Comparison of proximal and distal gastric neuroendocrine carcinoma based on SEER database.

机构信息

Disease Control and Prevention Administration of Zhejiang Province, Hangzhou, Zhejiang, China.

Department of General Surgery, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, No.453 Stadium Road, Hangzhou, 310007, Zhejiang, China.

出版信息

Sci Rep. 2024 Oct 29;14(1):25956. doi: 10.1038/s41598-024-76689-z.

Abstract

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 with GNEC. 1807 patients were divided into DGNEC and PGNEC groups. We performed analyses by using propensity score matching (PSM) and Fine-Gray competing risk methods. A predictive nomogram for the prognosis of GNEC was constructed and validated. The cumulative incidence of cancer-specific death (CSD) in the DGNEC group was lower than that in the PGNEC group. Subgroup analysis showed lower CSD of DGNEC in males, females, tumor sizes (≤ 2 cm, 2 < tumor size ≤ 5 cm, > 5 cm, and unknown), grade stage I-II, and AJCC stage I-III, chemotherapy or no chemotherapy, surgery or no surgery 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 CSD. Patients with DGNEC have a better prognosis than those with PGNEC. The model exhibits strong predictive capability for these patients.

摘要

胃神经内分泌癌(GNEC)的发病率呈上升趋势,其预后极差。我们比较了远端和近端 GNEC 的生存结果,并建立了一个纳入肿瘤部位的列线图,以增强 GNEC 患者的个体化管理。将 1807 例患者分为 DGNEC 和 PGNEC 组。我们使用倾向评分匹配(PSM)和 Fine-Gray 竞争风险方法进行分析。构建并验证了预测 GNEC 预后的列线图。DGNEC 组的癌症特异性死亡(CSD)累积发生率低于 PGNEC 组。亚组分析显示,男性、女性、肿瘤大小(≤2cm、2cm<肿瘤大小≤5cm、>5cm 和未知)、分级分期 I-II 期和 AJCC 分期 I-III 期、化疗或无化疗、手术或无手术组的 DGNEC 患者 CSD 较低(P<0.05)。多变量分析显示 PGNEC 与 CSD 显著相关(HR,1.4;95%CI,1.13-1.73;P=0.02)。GNEC 患者 CSD 的独立预测因素为原发部位、性别、年龄、肿瘤大小、AJCC 分期、T 分期、N 分期、分级分期和手术。基于多变量分析构建了预测模型,以估计 1、3 和 5 年 CSD 的概率。校准曲线表明 CSD 的预测概率与观察概率之间具有极好的一致性。DGNEC 患者的预后优于 PGNEC 患者。该模型对这些患者具有很强的预测能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d912/11522417/dc53c9d0e05f/41598_2024_76689_Fig1_HTML.jpg

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