Second Clinical Medical College, Binzhou Medical University, Yantai, China.
Department of General Surgery Center, Linyi People's Hospital, Shandong University, Linyi, China.
Medicine (Baltimore). 2023 Jun 9;102(23):e33902. doi: 10.1097/MD.0000000000033902.
This study aimed to establish a validated prognostic survival column line chart by analyzing data from patients with colon cancer (CC) in the SEER database. The nomogram proposed in this study was based on the retrospective data of patients diagnosed with CC in the SEER database from 1975 to 2015. Randomly divided into training and validation sets, the nomogram was constructed using the Cox model, and the discriminatory power of the nomogram and its predictive accuracy were determined using the consistency index and associated calibration curves. In a multifactorial analysis of the main cohort, the independent factors for survival were age, sex, race, tumor stage, and tumor grade, all of which were included in the nomogram and were prognostic factors for patients with CC (P < .05). The calibration curve of the survival probability showed good agreement between the prediction of the nomogram and the actual observation. The validation calibration curve showed good correlation and agreement between predicted and observed values. Multifactorial analysis showed that the factors affecting the prognosis of patients with CC included age, sex, race, tumor-node-metastasis stage, and tumor pathological stage. The nomogram prediction model proposed in this study has high accuracy and can provide more accurate prognostic prediction and relevant reference values for assessing the postoperative survival of CC patients and guiding clinical decision-making.
本研究旨在通过分析 SEER 数据库中结肠癌（CC）患者的数据，建立一个经过验证的预后生存列线图。本研究提出的列线图基于 1975 年至 2015 年 SEER 数据库中诊断为 CC 的患者的回顾性数据。通过 Cox 模型构建列线图，并使用一致性指数和相关校准曲线确定列线图的判别能力及其预测准确性。在对主要队列进行的多因素分析中，生存的独立因素为年龄、性别、种族、肿瘤分期和肿瘤分级，这些因素均被纳入列线图，是 CC 患者的预后因素（P<0.05）。生存概率的校准曲线显示，列线图的预测与实际观察之间具有良好的一致性。验证校准曲线显示预测值与观察值之间具有良好的相关性和一致性。多因素分析显示，影响 CC 患者预后的因素包括年龄、性别、种族、肿瘤-淋巴结-转移分期和肿瘤病理分期。本研究提出的列线图预测模型具有较高的准确性，可为 CC 患者术后生存提供更准确的预后预测和相关参考值，指导临床决策。
