Prognostic nomogram based on coagulation for individualized prediction after radical resection of hepatocellular carcinoma
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View abstract on PubMed
Summary
This summary is machine-generated.A new nomogram integrating clinicopathological factors and coagulation indices accurately predicts recurrence-free survival in hepatocellular carcinoma patients post-resection. This tool aids in stratifying patients into risk groups for better management.
Area Of Science
- Hepatobiliary Surgery
- Oncology
- Biostatistics
Background
- Hepatocellular carcinoma (HCC) prognosis after radical resection is often suboptimal.
- Predictive models are needed to improve patient outcomes and guide treatment strategies.
Purpose Of The Study
- To develop and validate a nomogram for predicting recurrence-free survival (RFS) in HCC patients.
- To integrate clinicopathological parameters and coagulation indices into a predictive model.
Main Methods
- A cohort of 863 HCC patients undergoing radical resection was analyzed.
- Cox regression identified independent risk factors for constructing the nomogram.
- Model performance was validated using calibration curves, decision curve analysis (DCA), C-index, and time-dependent area under the curve (td-AUC) in internal and external cohorts.
Main Results
- The nomogram incorporated age, tumor size, differentiation, microvascular invasion, INR, and FIB.
- The nomogram demonstrated superior predictive performance over existing staging systems (TNM, BCLC, CNLC, CLIP).
- Significant differences in RFS were observed among high-, medium-, and low-risk groups stratified by the nomogram.
Conclusions
- A nomogram integrating coagulation indices offers high predictive efficacy for HCC recurrence.
- This model has significant clinical application value for personalized patient management.
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