An Inflammation-Associated Prognostic Model for Hepatocellular Carcinoma Following Radical Resection

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 workCorrespondence: Ye Lin; Yanxia Lu, Email [email protected]; [email protected]: 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

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SHILAP Revista de lepidopterología
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2026-01-01
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
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article

An Inflammation-Associated Prognostic Model for Hepatocellular Carcinoma Following Radical Resection

Gan B, Lu Y, Lin Y, Zhai Y et al.
SHILAP Revista de lepidopterología
Inflammatory Biomarkers in Disease Prognosis
article

An Inflammation-Associated Prognostic Model for Hepatocellular Carcinoma Following Radical Resection

Gan B, Lu Y, Lin Y, Zhai Y, Guan R
article en

Abstract

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 workCorrespondence: Ye Lin; Yanxia Lu, Email [email protected]; [email protected]: 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

SHILAP Revista de lepidopterología
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Inflammatory Biomarkers in Disease Prognosis
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