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Updated: May 22, 2025
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Prognostic nomogram based on coagulation for individualized prediction after radical resection of hepatocellular
Ming Lu1,2,3, Haibo Yuan1, Mengjie Wu4
1Department of General Surgery, Fuyang Hospital of Anhui Medical University, No. 99 Huangshan Road, Hefei Modern Industrial Park, Yingzhou District, Fuyang, 236000, Anhui, China.
Background:
The prognosis of patients with hepatocellular carcinoma (HCC) following radical resection remains suboptimal. This study aimed to create a nomogram integrating clinicopathological parameters and coagulation indices to predict the recurrence-free survival (RFS) of these individuals.
Methods:
A total of 863 patients with hepatocellular carcinoma after radical resection were included (504 patients in the training cohort, 216 patients in the internal verification cohort and 142 patients in the external verification cohort). Cox regression analysis was used to determine the independent risk factors in the training cohort, and it was used to construct a prognostic nomogram. Calibration curves, decision curve analysis (DCA), the C index and the time-dependent area under the curve (td-AUC) were used to evaluate the performance of the nomogram, and the internal and external validation cohorts were used for verification. We also calculated total risk points to divide patients into high-, medium- and low-risk groups. The Kaplan-Meier methodology was used to analyze RFS, and differences were compared using the log-rank test.
Results:
Age, tumor size, tumor differentiation, microvascular invasion, INR and FIB for RFS were integrated into the nomogram. The calibration curves revealed a strong correlation between the predicted and actual results, and the nomogram's C-index and DCA demonstrated superior predictive performance compared with TNM, BCLC, CNLC, and CLIP. Additionally, the td-AUC revealed that the nomogram effectively predicted recurrence-free survival (RFS) at 1, 3, and 5 years. Moreover, significant differences in RFS were observed between the high-, medium-, and low-risk groups (P < 0.0001) after the effective cutoff values of the risk points were identified using the nomogram.
Conclusions:
A nomogram model that is based on coagulation indices has high predictive efficacy for the recurrence of hepatocellular carcinoma in patients and significant clinical application value.
