ArticleInternational journal of general medicine2022
Development and Validation of a Prediction Model for Predicting the Prognosis of Postoperative Patients with Hepatocellular Carcinoma.
Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Role of insulin-like growth factor/receptor signaling in hepatocellular carcinoma.Hepatology forum · 2026Review
- A nomogram based on PNI and preoperative TACE can predict overall survival in patients with larger than 2 cm HCC after hepatectomy.Updates in surgery · 2025Article
- Analysis of risk factors of hepatocellular carcinoma and establishment of a clinical prognosis model.Frontiers in oncology · 2023Article
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5 authors.
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Abstract
Purpose: The aims of this study were to identify the prognosis-related risk factors for HCC patients after surgery and to develop a predictive model by analysing the medical records of 152 HCC patients in our hospital. Patients and Methods: Univariate Cox regression analysis was applied to identify potential risk factors for HCC patients after surgery and to determine independent prognosis-related risk factors by multivariate analysis. Subsequently, a nomogram model was developed based on all independent factors and was validated by a validation set. Calibration and receiver operating characteristic curves were employed to evaluate the accuracy of the model. Finally, decision curve analyses were used to assess its clinical utility. Results: The univariate Cox regression analysis indicated that the patient's age, sex, grade, different AJCC TNM stages, vascular invasion, lymphatic infiltration, and tumour size were potential prognostic-related risk factors for HCC patients (p < 0.2), and the findings of multivariate analysis revealed that grade, different AJCC TNM stages, vascular invasion, and lymphatic infiltration were independent prognostic-related risk factors for HCC patients (p < 0.05). Subsequently, we constructed a prognosis-related prediction model based on all independent prognostic predictors and validated it with internal and external validation sets. The validation results indicated that the prediction model showed good accuracy (AUC = 0.81, 0.728) and consistency. More importantly, decision curve analysis illustrated that the nomogram model is a practical tool for predicting prognosis. Conclusion: This study found that grade, different AJCC TNM stages, vascular invasion, and lymphatic infiltration were independent prognosis-related predictors for HCC patients after surgery, and a nomogram model built on these predictors exhibited great accuracy and clinical usefulness.
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