肝细胞癌伴大血管侵犯的预后图:来自SEER数据库和中国队列的基于人群的研究。

IF 3.4 3区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Jia Fu, Min Liu, Sirong Chen, LiJun Chen, Shixiong Liang
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引用次数: 0

摘要

背景:肝细胞癌伴大血管侵犯(MaVI)患者预后较差。在本研究中,我们旨在建立一种用MaVI预测HCC预后的nomogram模型。方法:从2024年9月25日的监测、流行病学和最终结果(SEER)数据库中提取2211例患者的数据。我们以7:3的比例将患者随机分配到训练组和验证组。此外,采用了一个外部验证集,包括广西医科大学肿瘤医院的359例患者。通过训练队列的Cox回归分析确定影响总生存期(OS)的独立变量。采用Kaplan-Meier曲线和log-rank检验比较各组间OS的差异。基于所识别的因素,建立了nomogram模型。采用随时间变化的受试者工作特征曲线、c指数值、决策曲线分析和校准曲线评价模型的预测效果。结果:肝癌合并MaVI患者的独立生存指标包括N期、肺和骨转移、肿瘤大小、化疗、甲胎蛋白(AFP)水平、放疗和手术。利用这些因素构建了nomogram模型。训练组c指数为0.73,内部验证组为0.72,中文验证组为0.72。在训练集中,6个月、12个月和18个月的曲线下面积(AUC)分别为0.81(95%可信区间[CI] 0.79-0.83)、0.80 (95% CI 0.77-0.83)和0.79 (95% CI 0.76-0.82)。同样,内部验证集的AUC分别为0.83 (95% CI 0.80-0.86)、0.80 (95% CI 0.76-0.84)和0.78 (95% CI 0.74-0.83),中文验证集在6、12和18个月时的AUC分别为0.85 (95% CI 0.78-0.92)、0.82 (95% CI 0.77-0.87)和0.79 (95% CI 0.74-0.84)。结论:基于N分期、肿瘤大小、甲胎蛋白水平、肺转移、骨转移、化疗、放疗、手术的nomogram模型具有较高的预测准确率和临床应用价值。为肝细胞癌伴MaVI患者的临床实践提供有益的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Prognostic nomogram for hepatocellular carcinoma with major vascular invasion: a population-based study from the SEER database and a Chinese cohort.

Prognostic nomogram for hepatocellular carcinoma with major vascular invasion: a population-based study from the SEER database and a Chinese cohort.

Prognostic nomogram for hepatocellular carcinoma with major vascular invasion: a population-based study from the SEER database and a Chinese cohort.

Prognostic nomogram for hepatocellular carcinoma with major vascular invasion: a population-based study from the SEER database and a Chinese cohort.

Background: Patients with hepatocellular carcinoma (HCC) with major vascular invasion (MaVI) have a poor prognosis. In this study, we aimed to develop a nomogram model for predicting the prognosis of HCC with MaVI.

Methods: Data of 2211 patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database on September 25, 2024. We randomly allocated the patients into training and validation cohorts using a 7:3 ratio. Furthermore, an external validation set, comprising 359 patients from Guangxi Medical University Cancer Hospital, was used. Independent variables impacting overall survival (OS) were identified using Cox regression analyses of the training cohort. The variations in OS across groups were compared using Kaplan-Meier curves and log-rank testing. A nomogram model was developed based on the identified factors. Time-dependent receiver operating characteristic curves, C-index values, decision curve analysis, and calibration curves were used to evaluate the model's predictive efficacy.

Results: Independent indicators of survival for patients with HCC with MaVI included N stage, lung and bone metastases, tumor size, chemotherapy, alpha-fetoprotein (AFP) levels, radiotherapy, and surgery. A nomogram model was constructed using these factors. The C-index values were 0.73 for the training cohort, 0.72 for the internal validation cohort, and 0.72 for Chinese validation set. In training set, the area under the curve (AUC) was 0.81 (95% confidence interval [CI] 0.79-0.83), 0.80 (95% CI 0.77-0.83), and 0.79 (95% CI 0.76-0.82) at 6, 12, and 18 months, respectively. Similarly, the internal validation set had AUC of 0.83 (95% CI 0.80-0.86), 0.80 (95% CI 0.76-0.84), and 0.78 (95% CI 0.74-0.83) and the Chinese validation set had AUC of 0.85 (95% CI 0.78-0.92), 0.82 (95% CI 0.77-0.87), and 0.79 (95% CI 0.74-0.84) at 6, 12, and 18 months, respectively.

Conclusions: A nomogram model based on N stage, tumor size, AFP levels, lung metastasis, bone metastasis, chemotherapy, radiotherapy, and surgery demonstrated high prediction accuracy and clinical value. Thus, it can serve as a useful reference in clinical practice for patients with HCC having MaVI.

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来源期刊
European Journal of Medical Research
European Journal of Medical Research 医学-医学:研究与实验
CiteScore
3.20
自引率
0.00%
发文量
247
审稿时长
>12 weeks
期刊介绍: European Journal of Medical Research publishes translational and clinical research of international interest across all medical disciplines, enabling clinicians and other researchers to learn about developments and innovations within these disciplines and across the boundaries between disciplines. The journal publishes high quality research and reviews and aims to ensure that the results of all well-conducted research are published, regardless of their outcome.
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