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Background <p>Postoperative late recurrence (POLAR) after 2 years from the date of surgical resection of hepatocellular carcinoma (HCC) represents a unique surveillance and management challenge. Despite identified risk factors, individualized prediction tools to guide personalized surveillance strategies for recurrence remain scarce. The current study sought to develop a predictive model for late recurrence among patients undergoing HCC resection.</p> Methods <p>This multicenter study analyzed HCC patients who underwent resection across 10 Chinese hepatobiliary centers and remained recurrence-free at 2 years after hepatectomy. Patients were randomly assigned to development and validation cohorts (2:1 ratio). Independent predictors identified through multivariate Cox regression analysis were integrated into a nomogram and web-based calculator.</p> Results <p>Among 849 recurrence-free patients at 2 years after hepatectomy for HCC, seven independent predictors of POLAR were identified: male (hazard ratio [HR] 1.37, <i>p</i>&#xa0;=&#xa0;0.04), cirrhosis (HR 1.42, <i>p&#xa0;</i>=&#xa0;0.008), multiple tumors (HR 1.56, <i>p&#xa0;</i>=&#xa0;0.006), satellite nodules (HR 1.59, <i>p&#xa0;</i>=&#xa0;0.004), large tumor size (HR 1.49, <i>p&#xa0;</i>=&#xa0;0.009), macrovascular invasion (HR 4.63, <i>p&#xa0;</i>&lt;&#xa0;0.001), and microvascular invasion (HR 1.69, <i>p&#xa0;</i>=&#xa0;0.001). The POLAR-HCC nomogram-based calculator demonstrated robust performance in both the development (area under the curve [AUC] 0.660) and validation (AUC 0.626) cohorts. Using the optimal cut-off value of 1.93, patients were accurately stratified into high- and low-risk groups with different risks of POLAR (<i>p&#xa0;</i>&lt;&#xa0;0.001).</p> Conclusions <p>The POLAR-HCC online calculator enables risk stratification for POLAR after HCC resection. By integrating tumor characteristics and host factors, this prediction tool identified high-risk patients who may benefit from intensified recurrence surveillance, potentially improving long-term survival through earlier detection of POLAR. The model represents an important step toward personalized surveillance strategies among patients undergoing HCC resection.</p>

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Development and Validation of an Individualized Prediction Model for Postoperative Late Recurrence After Hepatectomy for Hepatocellular Carcinoma (POLAR-HCC): A Multicenter Study

  • 期刊论文

  • 发表日期：

    2025年9月10日

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  • Xin-Fei Xu,
  • Han Wu,
  • Li-Hui Gu,
  • Yu-Ze Zhao,
  • Ya-Hao Zhou,
  • Ting-Hao Chen,
  • Hong-Wei Guo,
  • Zhong Chen,
  • Kong-Ying Lin,
  • Wei-Min Gu,
  • Zi-Xuan Wang,
  • Hong Wang,
  • Xian-Ming Wang,
  • Yong-Kang Diao,
  • Chao Li,
  • Lan-Qing Yao,
  • Ming-Da Wang,
  • Timothy M. Pawlik,
  • Feng Shen,
  • Tian Yang

摘要

Background

Postoperative late recurrence (POLAR) after 2 years from the date of surgical resection of hepatocellular carcinoma (HCC) represents a unique surveillance and management challenge. Despite identified risk factors, individualized prediction tools to guide personalized surveillance strategies for recurrence remain scarce. The current study sought to develop a predictive model for late recurrence among patients undergoing HCC resection.

Methods

This multicenter study analyzed HCC patients who underwent resection across 10 Chinese hepatobiliary centers and remained recurrence-free at 2 years after hepatectomy. Patients were randomly assigned to development and validation cohorts (2:1 ratio). Independent predictors identified through multivariate Cox regression analysis were integrated into a nomogram and web-based calculator.

Results

Among 849 recurrence-free patients at 2 years after hepatectomy for HCC, seven independent predictors of POLAR were identified: male (hazard ratio [HR] 1.37, p = 0.04), cirrhosis (HR 1.42, p = 0.008), multiple tumors (HR 1.56, p = 0.006), satellite nodules (HR 1.59, p = 0.004), large tumor size (HR 1.49, p = 0.009), macrovascular invasion (HR 4.63, p < 0.001), and microvascular invasion (HR 1.69, p = 0.001). The POLAR-HCC nomogram-based calculator demonstrated robust performance in both the development (area under the curve [AUC] 0.660) and validation (AUC 0.626) cohorts. Using the optimal cut-off value of 1.93, patients were accurately stratified into high- and low-risk groups with different risks of POLAR (p < 0.001).

Conclusions

The POLAR-HCC online calculator enables risk stratification for POLAR after HCC resection. By integrating tumor characteristics and host factors, this prediction tool identified high-risk patients who may benefit from intensified recurrence surveillance, potentially improving long-term survival through earlier detection of POLAR. The model represents an important step toward personalized surveillance strategies among patients undergoing HCC resection.