International Journal of Hyperthermia (Dec 2024)

Prognostic significance of pan-immune-inflammation value in hepatocellular carcinoma treated by curative radiofrequency ablation: potential role for individualized adjuvant systemic treatment

  • Xuexia Liang,
  • Juyuan Bu,
  • Yanhui Jiang,
  • Shuqin Zhu,
  • Qing Ye,
  • Yun Deng,
  • Wuzhu Lu,
  • Qiaodan Liu

DOI
https://doi.org/10.1080/02656736.2024.2355279
Journal volume & issue
Vol. 41, no. 1

Abstract

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AbstractBackground This study aimed to explore the prognostic role of pan-immune-inflammation value (PIV) and develop a new risk model to guide individualized adjuvant systemic treatment following radiofrequency ablation (RFA) for early-stage hepatocellular carcinoma (HCC).Materials and methods Patients with early-stage HCC treated by RFA were randomly divided into training cohort A (n = 65) and testing cohort B (n = 68). Another 265 counterparts were enrolled into external validating cohort C. Various immune-inflammatory biomarkers (IIBs) were screened in cohort A. Prognostic role of PIV was evaluated and validated in cohort B and C, respectively. A nomogram risk model was built in cohort C and validated in pooled cohort D. Clinical benefits of adjuvant anti-angiogenesis therapy plus immune checkpoint inhibitor (AA-ICI) following RFA was assessed in low- and high-risk groups.Results The cutoff point of PIV was 120. High PIV was an independent predictor of unfavorable recurrence-free survival (RFS) and overall survival (OS). RFS and OS rates of patients with high PIV were significantly lower than those with low PIV both in cohort B (PRFS=0.016, POS=0.011) and C (PRFS<0.001, POS<0.001). The nomogram model based on PIV, tumor number and BCLC staging performed well in risk stratification in external validating cohort C. Adjuvant AA-ICI treatment showed an added benefit in OS (p = 0.011) for high-risk patients.Conclusions PIV is a feasible independent prognostic factor for RFS and OS in early-stage HCC patients who received curative RFA. The proposed PIV-based nomogram risk model could help clinicians identify high-risk patients and tailor adjuvant systemic treatment and disease follow-up scheme.

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