Nomogram predicting survival in patients with lymph node-negative hepatocellular carcinoma based on the SEER database...

Area of Science:

• Oncology
• Hepatobiliary Surgery
• Cancer Prognostics

Background:

• Lymph node metastasis (LNM) status is controversial in predicting hepatocellular carcinoma (HCC) survival.
• Identifying prognostic factors in HCC patients without LNM is crucial for accurate survival prediction.

Purpose of the Study:

• To investigate independent prognostic factors in HCC patients without LNM.
• To develop and validate a nomogram for predicting cancer-specific survival (CSS) in this patient group.

Main Methods:

• Utilized the SEER database (2010-2019) for training and internal validation, with external validation from Zhongnan Hospital.
• Employed univariate and multivariate analyses to identify prognostic factors.
• Constructed a nomogram and assessed its predictive performance using C-index, AUC, calibration plots, and decision curve analysis (DCA).

Main Results:

• Age, gender, bone/lung metastasis, AFP, T stage, surgery, and chemotherapy were identified as independent prognostic factors.
• The nomogram achieved high predictive accuracy with C-indices of 0.746 (training), 0.740 (internal validation), and 0.777 (external validation).
• Calibration curves and DCA indicated excellent predictive performance and clinical applicability.

Conclusions:

• A validated nomogram was developed to predict CSS in HCC patients without LNM.
• The nomogram offers a valuable tool for clinicians to determine prognosis and guide treatment strategies.
• The model demonstrates robust predictive performance and clinical utility.