Pan-Immune-Inflammation Value as a Prognostic Biomarker for Hepatocellular Carcinoma Patients Undergoing Hepatectomy.

IF 4.2 2区 医学 Q2 IMMUNOLOGY
Journal of Inflammation Research Pub Date : 2025-05-20 eCollection Date: 2025-01-01 DOI:10.2147/JIR.S521603
Hongyuan Fu, Yubo Wang, Bangde Xiang
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引用次数: 0

Abstract

Purpose: Hepatocellular carcinoma (HCC) poses a substantial threat to global health, characterized by its high incidence and mortality rates. This research aims to assess the prognostic value of a systematic serum inflammation index, the pan-immune-inflammation value (PIV), in patients with HCC who have undergone hepatectomy.

Patients and methods: A total of 1764 HCC patients who underwent surgery were included in the study. These patients were divided into two groups based on the median PIV value. The Cox regression model was utilized to ascertain the independent risk factors that influence the prognosis of patients. A PIV-based nomogram was constructed and its performance was evaluated by the C-index, calibration curve, ROC curve, and DCA curve. Finally, a comparison was made between the nomogram and existing staging models.

Results: Patients with elevated PIV exhibited diminished OS and RFS compared to those with lower PIV. Univariate and multivariate Cox analyses revealed that PIV is an independent predictor of prognosis. The PIV-based nomogram demonstrated excellent discrimination, calibration, and clinical net benefit. The proposed nomogram outperformed the other existing staging systems, as evidenced by a higher AUC value.

Conclusion: PIV exhibits potential as a prognostic factor for both OS and RFS in patients with HCC who have undergone hepatectomy. The PIV-based nomogram can serve as an additional tool in conjunction with the existing liver cancer staging system, thereby facilitating more personalized treatment decisions for clinicians.

泛免疫炎症作为肝细胞癌切除术患者预后生物标志物的价值
目的:肝细胞癌(HCC)以其高发病率和高死亡率为特征,对全球健康构成重大威胁。本研究旨在评估系统性血清炎症指数,即泛免疫炎症值(PIV)在行肝切除术的HCC患者中的预后价值。患者和方法:本研究共纳入1764例接受手术治疗的HCC患者。根据PIV中位值将患者分为两组。采用Cox回归模型确定影响患者预后的独立危险因素。构建基于piv的nomogram,并通过C-index、校准曲线、ROC曲线和DCA曲线对其性能进行评价。最后,将nomogram分期模型与现有分期模型进行比较。结果:与PIV较低的患者相比,PIV升高的患者表现出更低的OS和RFS。单因素和多因素Cox分析显示PIV是预后的独立预测因子。基于piv的nomogram显示出优秀的鉴别、校准和临床净效益。所提出的nomogram优于其他现有分期系统,其AUC值更高。结论:PIV可能是肝癌切除术患者OS和RFS的预后因素。基于piv的nomographic可以作为与现有肝癌分期系统相结合的额外工具,从而为临床医生提供更个性化的治疗决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Inflammation Research
Journal of Inflammation Research Immunology and Microbiology-Immunology
CiteScore
6.10
自引率
2.20%
发文量
658
审稿时长
16 weeks
期刊介绍: An international, peer-reviewed, open access, online journal that welcomes laboratory and clinical findings on the molecular basis, cell biology and pharmacology of inflammation.
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