Construction and validation of a novel prognostic nomogram for patients with poorly differentiated gastric neuroendocrine neoplasms.

IF 2.6 Q3 ONCOLOGY
Ben-Long Zhang, Fei Peng, Li Li, Yun-He Gao, Zi-Jian Wang, Yi-Xun Lu, Lin Chen, Ke-Cheng Zhang
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引用次数: 0

Abstract

Background: The prognosis of patients with poorly differentiated gastric neuroendocrine neoplasms (PDGNENs) is dismal and related research is limited.

Aim: To investigate the prognostic factors, and validate a novel prognostic nomogram for PDGNEN patients.

Methods: We conducted a retrospective study using clinical and pathological data from PDGNEN patients treated at the First Medical Center of the Chinese PLA General Hospital from January 2000 to June 2023. Overall survival (OS) differences were assessed with the Log-rank test and Kaplan-Meier survival curves. Cox regression analysis identified independent risk factors for prognosis. Model performance was evaluated using Harrell's concordance index, receiver operating characteristic analysis, area under the curve, calibration curves, and decision curve analysis (UDC), including the area under the UDC.

Results: The study included 336 patients (227 with neuroendocrine carcinoma and 109 with mixed adenoneuroendocrine carcinoma). The average age was 62.7 years. The cohort comprised 80 (24.7%) patients in stage I, 146 (42.9%) in stage II, 62 (18.1%) in stage III, and 48 (14.3%) in stage IV. Significant differences in OS were observed across tumor-node-metastasis stages (P < 0.001). Multivariate analysis showed age, Ki-67 index, invasion depth, lymph node metastasis, distant metastasis, and platelet-to-lymphocyte ratio as independent risk factors. We developed a nomogram with a concordance index of 0.779 (95% confidence interval: 0.743-0.858). Receiver operating characteristic analysis showed area under the curves for 1-year, 3-year, and 5-year OS predictions of 0.865, 0.850, and 0.890, respectively. The calibration curve demonstrated good agreement with actual outcomes. The area under the UDC for the nomogram vs the 8th American Joint Committee on Cancer tumor-node-metastasis staging system were 0.047 vs 0.027, 0.291 vs 0.179, and 0.376 vs 0.216 for 1-year, 3-year, and 5-year OS, respectively.

Conclusion: PDGNENs are predominantly found in older men, often in advanced stages at diagnosis, resulting in poor prognosis. The established nomogram demonstrates strong predictive capability and clinical utility.

低分化胃神经内分泌肿瘤新型预后图的构建与验证。
背景:低分化胃神经内分泌肿瘤(PDGNENs)患者预后不佳,相关研究有限。目的:探讨PDGNEN患者的预后因素,并验证一种新的预后图。方法:回顾性分析解放军总医院第一医疗中心2000年1月至2023年6月收治的PDGNEN患者的临床和病理资料。采用Log-rank检验和Kaplan-Meier生存曲线评估总生存期(OS)差异。Cox回归分析确定了影响预后的独立危险因素。采用Harrell’s concordance index、受试者工作特征分析、曲线下面积、校准曲线和决策曲线分析(decision curve analysis, UDC)(包括UDC下面积)对模型性能进行评价。结果:共纳入336例患者,其中神经内分泌癌227例,混合性腺神经内分泌癌109例。平均年龄为62.7岁。该队列包括80例(24.7%)I期患者,146例(42.9%)II期患者,62例(18.1%)III期患者和48例(14.3%)IV期患者。不同肿瘤-淋巴结-转移期的OS差异显著(P < 0.001)。多因素分析显示,年龄、Ki-67指数、浸润深度、淋巴结转移、远处转移、血小板/淋巴细胞比是独立的危险因素。我们建立了一个一致性指数为0.779(95%置信区间:0.743-0.858)的nomogram。受试者工作特征分析显示,1年、3年和5年OS预测曲线下面积分别为0.865、0.850和0.890。标定曲线与实际结果吻合较好。在1年、3年和5年的OS中,nomogram与第八届美国癌症联合委员会肿瘤-淋巴结-转移分期系统的UDC下面积分别为0.047 vs 0.027、0.291 vs 0.179、0.376 vs 0.216。结论:PDGNENs主要见于老年男性,诊断时多为晚期,预后较差。所建立的图具有较强的预测能力和临床应用价值。
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来源期刊
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585
期刊介绍: The WJCO is a high-quality, peer reviewed, open-access journal. The primary task of WJCO is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of oncology. In order to promote productive academic communication, the peer review process for the WJCO is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJCO are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in oncology. Scope: Art of Oncology, Biology of Neoplasia, Breast Cancer, Cancer Prevention and Control, Cancer-Related Complications, Diagnosis in Oncology, Gastrointestinal Cancer, Genetic Testing For Cancer, Gynecologic Cancer, Head and Neck Cancer, Hematologic Malignancy, Lung Cancer, Melanoma, Molecular Oncology, Neurooncology, Palliative and Supportive Care, Pediatric Oncology, Surgical Oncology, Translational Oncology, and Urologic Oncology.
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