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基于 SEER 的人群分析:建立用于预测肝样腺癌特异性生存的动态列线图。

Development of dynamic nomogram for predicting cancer-specific survival in hepatoid adenocarcinoma: A comprehensive SEER-based population analysis.

机构信息

Department of Targeting Therapy and Immunology, Cancer Centre, West China Hospital, Sichuan University, Chengdu, China.

Division of Abdominal Tumor Multimodality Treatment, Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.

出版信息

Biomol Biomed. 2024 Sep 6;24(5):1350-1360. doi: 10.17305/bb.2024.10445.

Abstract

Hepatoid adenocarcinoma (HAC) is a poorly differentiated extrahepatic tumor that can produce alpha-fetoprotein (AFP). The literature does not provide a comprehensive understanding of the prognostic factors for HAC. Therefore, we present a novel nomogram to predict the cancer-specific survival (CSS) of patients with HAC. We analyzed 265 cases of HAC from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2004 to 2015. Using a Cox proportional hazard regression model, we identified several risk factors and incorporated them into our predictive nomogram. The nomogram's predictive ability was assessed by utilizing the concordance index (C-index), calibration curve, and receiver operating characteristic (ROC). Results from a multivariate Cox regression showed that CSS was independently correlated with liver metastasis, surgery, and chemotherapy. Our nomogram had a C-index of 0.71 (95% CI 0.71-0.96). Furthermore, calibration curves demonstrated concordance between the predicted survival probability from the nomogram and the observed survival probability. The areas under the curve (AUC) for 6-month, 1-, and 3-year survival were 0.80, 0.82, and 0.88, respectively. Our study successfully formulated a prognostic nomogram that offers promising predictions for the 6-month, 1-, and 3-year CSS of patients with HAC. This nomogram holds potential for practical use in guiding treatment decisions and designing clinical trials.

摘要

肝样腺癌(Hepatoid adenocarcinoma,HAC)是一种低分化的肝外肿瘤,可产生甲胎蛋白(alpha-fetoprotein,AFP)。文献中对于 HAC 的预后因素尚无全面了解。因此,我们提出了一种新的列线图来预测 HAC 患者的癌症特异性生存(cancer-specific survival,CSS)。我们分析了 2004 年至 2015 年期间来自监测、流行病学和最终结果(Surveillance, Epidemiology, and End Results,SEER)数据库的 265 例 HAC 病例。使用 Cox 比例风险回归模型,我们确定了几个风险因素,并将其纳入我们的预测列线图中。通过一致性指数(concordance index,C-index)、校准曲线和受试者工作特征(receiver operating characteristic,ROC)评估了列线图的预测能力。多变量 Cox 回归的结果表明,CSS 与肝转移、手术和化疗独立相关。我们的列线图的 C-index 为 0.71(95%置信区间 0.71-0.96)。此外,校准曲线表明列线图预测的生存概率与观察到的生存概率之间存在一致性。6 个月、1 年和 3 年生存率的曲线下面积(area under the curve,AUC)分别为 0.80、0.82 和 0.88。我们的研究成功制定了一个预后列线图,为 HAC 患者的 6 个月、1 年和 3 年 CSS 提供了有前途的预测。该列线图具有在指导治疗决策和设计临床试验方面实际应用的潜力。

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