A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients With Early Hepatocellular Carcinoma: A Study Based on SEER Database.
A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients With Early Hepatocellular Carcinoma: A Study Based on SEER Database.
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DOI：
10.3389/fpubh.2021.789026
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发表时间：
2021
影响因子：
5.2
通讯作者：
Zhang G
中科院分区：
文献类型：
--
作者：
He T;Chen T;Liu X;Zhang B;Yue S;Cao J;Zhang G
背景：原发性肝癌是一种以肝细胞癌（HCC）为主要表现的常见恶性肿瘤。老年早期HCC患者越来越多，年龄越大预后越差。然而，对于这些患者的预后，仍然缺乏准确的预测模型。方法：下载2010 - 2016年符合条件的老年早期HCC监测、流行病学和最终结果数据库的数据。2010 - 2015年患者随机分为训练组（n = 1093）和验证组（n = 461）。采用2016年患者数据（n = 431）进行外部验证。通过单因素和多因素分析获得独立的预后因素。基于这些因素，构建癌症特异性生存（CSS） nomogram。本方法的预测性能和临床实用性得到了验证。根据nomogram风险评分，将患者分为低、中、高风险组。采用Kaplan-Meier曲线和log-rank检验进行生存分析。结果：年龄、种族、T分期、组织学分级、手术、放疗和化疗是CSS的独立预测因素，因此纳入了我们的nomogram。在训练组和验证组中，我们的nomogram一致性指数（c - index）分别为0.739 （95% CI: 0.714-0.764）和0.756 （95% CI: 0.719-0.793）。受试者工作特征曲线（auc）下的1、3和5年区域显示了类似的结果。校正曲线显示观测值与预测值高度一致。在外部验证队列中，c -指数（0.802,95%CI: 0.778 ~ 0.826）和校准曲线也显示了观测值与预测值的高度一致性。与TNM分期相比，nomogram相关决策曲线分析（DCA）曲线表现出更好的临床实用性。Kaplan-Meier曲线显示，CSS在三个不同风险组之间存在显著差异。此外，还开发了一个CSS在线预测工具。结论：构建并验证了基于web的老年早期HCC患者CSS预测模型，该模型可为老年早期HCC患者的预后评估、治疗策略选择及随访管理提供参考。
Background: Primary liver cancer is a common malignant tumor primarily represented by hepatocellular carcinoma (HCC). The number of elderly patients with early HCC is increasing, and older age is related to a worse prognosis. However, an accurate predictive model for the prognosis of these patients is still lacking. Methods: Data of eligible elderly patients with early HCC in Surveillance, Epidemiology, and End Results database from 2010 to 2016 were downloaded. Patients from 2010 to 2015 were randomly assigned to the training cohort (n = 1093) and validation cohort (n = 461). Patients' data in 2016 (n = 431) was used for external validation. Independent prognostic factors were obtained using univariate and multivariate analyses. Based on these factors, a cancer-specific survival (CSS) nomogram was constructed. The predictive performance and clinical practicability of our nomogram were validated. According to the risk scores of our nomogram, patients were divided into low-, intermediate-, and high-risk groups. A survival analysis was performed using Kaplan–Meier curves and log-rank tests. Results: Age, race, T stage, histological grade, surgery, radiotherapy, and chemotherapy were independent predictors for CSS and thus were included in our nomogram. In the training cohort and validation cohort, the concordance indices (C-indices) of our nomogram were 0.739 (95% CI: 0.714–0.764) and 0.756 (95% CI: 0.719–0.793), respectively. The 1-, 3-, and 5-year areas under receiver operating characteristic curves (AUCs) showed similar results. Calibration curves revealed high consistency between observations and predictions. In external validation cohort, C-index (0.802, 95%CI: 0.778–0.826) and calibration curves also revealed high consistency between observations and predictions. Compared with the TNM stage, nomogram-related decision curve analysis (DCA) curves indicated better clinical practicability. Kaplan–Meier curves revealed that CSS significantly differed among the three different risk groups. In addition, an online prediction tool for CSS was developed. Conclusions: A web-based prediction model for CSS of elderly patients with early HCC was constructed and validated, and it may be helpful for the prognostic evaluation, therapeutic strategy selection, and follow-up management of these patients.
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影响因子：
3.7
作者：
Guo, Hui;Wu, Tao;Zhang, Xu-Feng
通讯作者：
Zhang, Xu-Feng
影响因子：
2.7
作者：
Wan, Sizhe;Nie, Yuan;Zhu, Xuan
通讯作者：
Zhu, Xuan
影响因子：
3.8
作者：
Cheng, Zhangjun;Yang, Pinghua;Shen, Feng
通讯作者：
Shen, Feng
影响因子：
3.8
作者：
Nakano, Ryosuke;Ohira, Masahiro;Ohdan, Hideki
通讯作者：
Ohdan, Hideki
影响因子：
3.3
作者：
Mills, Abigail;Thayer, David;Akinwande, Olaguoke
通讯作者：
Akinwande, Olaguoke