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Analysis of Risk Factors and Construction of Risk Prediction Model for Patients With First Recurrence After Initial
1Department of General Surgery, Dongyang People's Hospital, Jinhua, Zhejiang Province, China.
Summary
This study identifies key indicators like alpha-fetoprotein (AFP) levels and tumor characteristics that predict survival and disease progression in hepatocellular carcinoma (HCC) patients after initial treatment. Nomogram models were developed to forecast risks for these patients.
Area of Science:
- Hepatobiliary Surgery
- Oncology
- Medical Imaging
Background:
- Hepatocellular carcinoma (HCC) recurrence after curative resection poses a significant clinical challenge.
- Identifying prognostic factors and developing predictive models are crucial for managing post-resection HCC recurrence.
Purpose of the Study:
- To identify clinical indicators for patients experiencing first recurrence after HCC resection.
- To develop and validate nomogram models for predicting overall survival (OS) and progression-free survival (PFS).
Main Methods:
- Retrospective analysis of 200 patients with first HCC recurrence post-resection.
- Cox regression analysis to determine independent prognostic factors for OS and PFS.
- Development and validation of nomogram models using training and validation cohorts.
Main Results:
- Alpha-fetoprotein (AFP) level, tumor size, lymph node metastasis, histologic grade, and microvascular invasion (MVI) independently predicted OS.
- Age, AFP level, and histologic grade independently predicted PFS.
- Nomogram models demonstrated strong predictive accuracy for 1-, 2-, and 3-year OS and PFS.
Conclusions:
- Key prognostic factors for HCC recurrence include AFP, tumor characteristics, and initial resection details.
- Developed nomogram models offer reliable risk prediction for OS and PFS in recurrent HCC.
- These models provide valuable clinical insights for managing patients with first recurrence after HCC resection.
