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Objective <p>To identify prognostic factors and develop a predictive tool for patients with hilar cholangiocarcinoma (HCCA) undergoing R1 or R2 resection, thereby informing patient selection and individualized treatment decisions.</p> Methods <p>A retrospective analysis was conducted of HCCA patients who underwent R1 or R2 resection at a single center. Independent prognostic factors were identified using Cox regression analysis, and a predictive nomogram was constructed using R software.</p> Results <p>Multivariate analysis identified four independent prognostic factors: surgical margin status (<i>P</i> = 0.002), tumor differentiation grade (<i>P</i> = 0.030), vascular invasion (<i>P</i> &lt; 0.001), and adjuvant therapy (<i>P</i> = 0.023). The nomogram based on these factors demonstrated favorable discriminatory ability, with a C-index of 0.780. Time-dependent receiver operating characteristic (ROC) analysis yielded areas under the curve (AUC) of 0.904 (95% confidence interval [CI]: 0.831–0.966) and 0.822 (95% CI: 0.736–0.897) for predicting 1-year and 2-year survival, respectively. Patients stratified into high-risk and low-risk groups by the nomogram showed significantly different survival outcomes (1-year survival: 44% vs. 92.5%; 2-year survival: 20% vs. 52.8%).</p> Conclusion <p>The developed nomogram effectively predicts prognosis following R1 or R2 resection for HCCA, demonstrating good discrimination and short-term predictive accuracy. It serves as a useful tool for postoperative risk stratification and personalized management planning.</p>

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Analysis of prognostic factors for R1/R2 resection in patients with hilar cholangiocarcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月6日

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  • Zepu Wang,
  • Chuncheng Wang,
  • Meijian Yang,
  • Dan Lv,
  • Yanhui Peng

摘要

Objective

To identify prognostic factors and develop a predictive tool for patients with hilar cholangiocarcinoma (HCCA) undergoing R1 or R2 resection, thereby informing patient selection and individualized treatment decisions.

Methods

A retrospective analysis was conducted of HCCA patients who underwent R1 or R2 resection at a single center. Independent prognostic factors were identified using Cox regression analysis, and a predictive nomogram was constructed using R software.

Results

Multivariate analysis identified four independent prognostic factors: surgical margin status (P = 0.002), tumor differentiation grade (P = 0.030), vascular invasion (P < 0.001), and adjuvant therapy (P = 0.023). The nomogram based on these factors demonstrated favorable discriminatory ability, with a C-index of 0.780. Time-dependent receiver operating characteristic (ROC) analysis yielded areas under the curve (AUC) of 0.904 (95% confidence interval [CI]: 0.831–0.966) and 0.822 (95% CI: 0.736–0.897) for predicting 1-year and 2-year survival, respectively. Patients stratified into high-risk and low-risk groups by the nomogram showed significantly different survival outcomes (1-year survival: 44% vs. 92.5%; 2-year survival: 20% vs. 52.8%).

Conclusion

The developed nomogram effectively predicts prognosis following R1 or R2 resection for HCCA, demonstrating good discrimination and short-term predictive accuracy. It serves as a useful tool for postoperative risk stratification and personalized management planning.