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Prognostic nomogram of overall survival for radiation therapy in hepatocellular carcinoma: a population study based on the SEER database and an external cohort

列线图 医学 危险系数 比例危险模型 肝细胞癌 内科学 监测、流行病学和最终结果 队列 肿瘤科 接收机工作特性 阶段(地层学) 人口 流行病学 数据库 泌尿科 置信区间 癌症登记处 环境卫生 古生物学 生物 计算机科学
作者
Lijun Chen,Qiaoyuan Wu,Fu Jia,Mengjie Jiang,Jialin Qiu,Jiaomei Tao,L. Lin,Shenshen Chen,Yi Wu,Zhengqiang Yang,Jian-Xu Li,Shi‐Xiong Liang
出处
期刊:Frontiers in Oncology [Frontiers Media]
卷期号:14 被引量:1
标识
DOI:10.3389/fonc.2024.1371409
摘要

Purpose Radiotherapy (RT) plays an important role in the treatment of hepatocellular carcinoma (HCC). To screen patients who benefit most from RT, a nomogram for survival prediction of RT based on a large sample of patients with HCC was created and validated. Methods A total of 2,252 cases collected from the Surveillance, Epidemiology, and End Results (SEER) database were separated into a training or an internal validation cohort in a 7:3 ratio ( n = 1,565:650). An external validation cohort of cases from our institute was obtained ( n = 403). LASSO regression and Cox analyses were adopted to develop a nomogram for survival prediction. The decision curve analysis (DCA), calibration curve, and time-dependent receiver operating characteristic curves (TROCs) demonstrated the reliability of the predictive model. Results For patients with HCC who received RT, the analyses revealed that the independent survival prediction factors were T stage {T2 vs. T1, hazard ratio (HR) =1.452 [95% CI, 1.195–1.765], p < 0.001; T3 vs. T1, HR = 1.469 [95% CI, 1.168–1.846], p < 0.001; T4 vs. T1, HR = 1.291 [95% CI, 0.951–1.754], p = 0.101}, N stage (HR = 1.555 [95% CI, 1.338–1.805], p < 0.001), M stage (HR = 3.007 [95% CI, 2.645–3.418], p < 0.001), max tumor size (>2 and ≤5 vs. ≤2 cm, HR = 1.273 [95% CI, 0.992–1.633], p = 0.057; >5 and ≤10 vs. ≤2 cm, HR = 1.625 [95% CI, 1.246–2.118], p < 0.001; >10 vs. ≤2 cm, HR = 1.784 [95% CI, 1.335–2.385], p < 0.001), major vascular invasion (MVI) (HR = 1.454 [95% CI, 1.028–2.057], p = 0.034), alpha fetoprotein (AFP) (HR = 1.573 [95% CI, 1.315–1.882], p < 0.001), and chemotherapy (HR = 0.511 [95% CI, 0.454–0.576], p < 0.001). A nomogram constructed with these prognostic factors demonstrated outstanding predictive accuracy. The area under the curve (AUC) in the training cohort for predicting overall survival (OS) at 6, 12, 18, and 24 months was 0.824 (95% CI, 0.803–0.846), 0.824 (95% CI, 0.802–0.845), 0.816 (95% CI, 0.792–0.840), and 0.820 (95% CI, 0.794–0.846), respectively. The AUCs were similar in the other two cohorts. The DCA and calibration curve demonstrated the reliability of the predictive model. Conclusion For patients who have been treated with RT, a nomogram constructed with T stage, N stage, M stage, tumor size, MVI, AFP, and chemotherapy has good survival prediction ability.
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