PDF(Pubmed)
Abstract：
UNASSIGNED: Intestinal-type gastric adenocarcinoma, representing 95 % of gastric malignancies, originates from the malignant transformation of gastric gland cells. Despite its prevalence, existing methods for prognosis evaluation of this cancer subtype are inadequate. This study aims to enhance patient-specific prognosis evaluation by analyzing the clinicopathological characteristics and prognostic risk factors of intestinal-type gastric adenocarcinoma patients using data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute (NCI).
UNASSIGNED: We extracted clinical data for patients diagnosed with intestinal-type gastric adenocarcinoma between 2010 and 2015 from the SEER database, selecting 257 cases based on predefined inclusion and exclusion criteria. Independent risk factors for overall survival (OS) and cancer-specific survival (CSS) were identified using a Cox regression model. A nomogram model for predicting OS or CSS was developed from the Cox risk regression analysis and validated through the consistency index (C-index), ROC curve, and calibration curve.
UNASSIGNED: Age, primary tumor resection, chemotherapy, lymph node metastasis, and tumor size were identified as independent prognostic factors for OS and CSS (P < 0.05). The nomogram model, constructed from these indicators, demonstrated superior predictive consistency for OS and CSS compared to the AJCC-TNM staging system. ROC curve analysis confirmed the model\'s higher accuracy, and calibration curve analysis indicated good agreement between the nomogram\'s predictions and actual observed outcomes.
UNASSIGNED: The nomogram model derived from SEER database analyses accurately predicts OS and CSS for patients with intestinal-type gastric adenocarcinoma. This model promises to facilitate more tailored treatments in clinical practice.
UNASSIGNED: We extracted clinical data for patients diagnosed with intestinal-type gastric adenocarcinoma between 2010 and 2015 from the SEER database, selecting 257 cases based on predefined inclusion and exclusion criteria. Independent risk factors for overall survival (OS) and cancer-specific survival (CSS) were identified using a Cox regression model. A nomogram model for predicting OS or CSS was developed from the Cox risk regression analysis and validated through the consistency index (C-index), ROC curve, and calibration curve.
UNASSIGNED: Age, primary tumor resection, chemotherapy, lymph node metastasis, and tumor size were identified as independent prognostic factors for OS and CSS (P < 0.05). The nomogram model, constructed from these indicators, demonstrated superior predictive consistency for OS and CSS compared to the AJCC-TNM staging system. ROC curve analysis confirmed the model\'s higher accuracy, and calibration curve analysis indicated good agreement between the nomogram\'s predictions and actual observed outcomes.
UNASSIGNED: The nomogram model derived from SEER database analyses accurately predicts OS and CSS for patients with intestinal-type gastric adenocarcinoma. This model promises to facilitate more tailored treatments in clinical practice.
摘要：
■肠型胃腺癌，占胃恶性肿瘤的95%，起源于胃腺细胞的恶性转化。尽管流行,这种癌症亚型的现有预后评估方法不足.本研究旨在通过使用监测数据分析肠型胃腺癌患者的临床病理特征和预后危险因素，提高患者特异性预后评估。流行病学,和国家癌症研究所（NCI）的最终结果（SEER）计划。
■我们从SEER数据库中提取了2010年至2015年间诊断为肠型胃腺癌的患者的临床数据，根据预定义的纳入和排除标准选择257例。使用Cox回归模型确定总生存期（OS）和癌症特异性生存期（CSS）的独立危险因素。从Cox风险回归分析中建立了预测OS或CSS的列线图模型，并通过一致性指数（C指数）进行了验证，ROC曲线,和校准曲线。
■年龄，原发肿瘤切除,化疗,淋巴结转移,肿瘤大小是OS和CSS的独立预后因素(P<0.05)。列线图模型，根据这些指标构建，与AJCC-TNM分期系统相比，OS和CSS具有更好的预测一致性。ROC曲线分析证实了模型的较高准确性,和校准曲线分析表明，列线图的预测和实际观察到的结果之间有很好的一致性。
■来自SEER数据库分析的列线图模型可以准确预测肠型胃腺癌患者的OS和CSS。该模型有望在临床实践中促进更多定制的治疗。
■我们从SEER数据库中提取了2010年至2015年间诊断为肠型胃腺癌的患者的临床数据，根据预定义的纳入和排除标准选择257例。使用Cox回归模型确定总生存期（OS）和癌症特异性生存期（CSS）的独立危险因素。从Cox风险回归分析中建立了预测OS或CSS的列线图模型，并通过一致性指数（C指数）进行了验证，ROC曲线,和校准曲线。
■年龄，原发肿瘤切除,化疗,淋巴结转移,肿瘤大小是OS和CSS的独立预后因素(P<0.05)。列线图模型，根据这些指标构建，与AJCC-TNM分期系统相比，OS和CSS具有更好的预测一致性。ROC曲线分析证实了模型的较高准确性,和校准曲线分析表明，列线图的预测和实际观察到的结果之间有很好的一致性。
■来自SEER数据库分析的列线图模型可以准确预测肠型胃腺癌患者的OS和CSS。该模型有望在临床实践中促进更多定制的治疗。
