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已发表论文
一种用于预测肝细胞癌根治性切除术后炎症相关预后的模型
Authors Zhai Y, Gan B, Guan R , Lin Y, Lu Y
Received 5 October 2025
Accepted for publication 25 December 2025
Published 8 January 2026 Volume 2026:13 567300
DOI https://doi.org/10.2147/JHC.S567300
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Ahmed Kaseb
Yanyun Zhai,1,* Biling Gan,1,* Renguo Guan,1 Ye Lin,1 Yanxia Lu2
1Department of Hepatobiliary Surgery, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People’s Republic of China; 2Department of Operating Room, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Ye Lin; Yanxia Lu, Email linye@gdph.org.cn; 929885825@qq.com
Background: Hepatocellular carcinoma (HCC) remains poor, and inflammatory markers have emerged as potential predictors. This study aimed to develop and validate a nomogram for predicting overall survival (OS) in patients with HCC after radical hepatectomy by integrating inflammatory markers with clinicopathological factors.
Methods: We retrospectively analyzed patients with HCC who underwent radical hepatectomy at the Guangdong Provincial People’s Hospital between 2014 and 2018. The patients were randomly assigned (2:1 ratio) to the training and validation cohorts. Independent prognostic factors were identified using univariate and multivariate Cox regression analyses to construct a nomogram. The performance of the model was assessed using ROC, calibration, and decision curve analysis (DCA) and compared with established staging systems (AJCC 8th edition TNM, BCLC, and CNLC).
Results: The training and validation cohorts included 242 and 121 patients, respectively. Aspartate aminotransferase-to-platelet ratio index (APRI), systemic inflammation response index (SIRI), and microvascular invasion (MVI) were identified as independent prognostic factors (P < 0.05). In the training cohort, the nomogram achieved AUCs of 0.837, 0.778, and 0.793 for the 1-, 3-, and 5-year OS, respectively. The corresponding AUCs in the validation cohort were 0.712, 0.746, and 0.746, respectively. The calibration curves and DCA confirmed the robust predictive ability of the model. The nomogram AUCs were significantly higher than those of all staging systems (P < 0.05).
Conclusion: The proposed nomogram, incorporating APRI, SIRI, and MVI, effectively predicts OS in patients with HCC following radical resection and outperforms conventional staging systems.
Keywords: hepatocellular carcinoma, inflammatory markers, microvascular invasion, nomogram, prognosis
1Department of Hepatobiliary Surgery, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People’s Republic of China; 2Department of Operating Room, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Ye Lin; Yanxia Lu, Email linye@gdph.org.cn; 929885825@qq.com
Background: Hepatocellular carcinoma (HCC) remains poor, and inflammatory markers have emerged as potential predictors. This study aimed to develop and validate a nomogram for predicting overall survival (OS) in patients with HCC after radical hepatectomy by integrating inflammatory markers with clinicopathological factors.
Methods: We retrospectively analyzed patients with HCC who underwent radical hepatectomy at the Guangdong Provincial People’s Hospital between 2014 and 2018. The patients were randomly assigned (2:1 ratio) to the training and validation cohorts. Independent prognostic factors were identified using univariate and multivariate Cox regression analyses to construct a nomogram. The performance of the model was assessed using ROC, calibration, and decision curve analysis (DCA) and compared with established staging systems (AJCC 8th edition TNM, BCLC, and CNLC).
Results: The training and validation cohorts included 242 and 121 patients, respectively. Aspartate aminotransferase-to-platelet ratio index (APRI), systemic inflammation response index (SIRI), and microvascular invasion (MVI) were identified as independent prognostic factors (P < 0.05). In the training cohort, the nomogram achieved AUCs of 0.837, 0.778, and 0.793 for the 1-, 3-, and 5-year OS, respectively. The corresponding AUCs in the validation cohort were 0.712, 0.746, and 0.746, respectively. The calibration curves and DCA confirmed the robust predictive ability of the model. The nomogram AUCs were significantly higher than those of all staging systems (P < 0.05).
Conclusion: The proposed nomogram, incorporating APRI, SIRI, and MVI, effectively predicts OS in patients with HCC following radical resection and outperforms conventional staging systems.
Keywords: hepatocellular carcinoma, inflammatory markers, microvascular invasion, nomogram, prognosis