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Development and Validation of a Nomogram-Based Prognostic Evaluation Model for Sarcomatoid Hepatocellular Carcinoma
Dazhuang Ge1, Zhiwen Luo1, Rui Mao1
1Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
This study developed a prognostic evaluation model (PEM) to predict survival in sarcomatoid hepatocellular carcinoma (SHC), a rare liver cancer. The new nomogram accurately identifies survival factors for SHC patients, improving prognosis prediction.
Area of Science:
- Hepatobiliary Malignancies
- Oncology Research
- Cancer Prognostics
Background:
- Sarcomatoid hepatocellular carcinoma (SHC) is a rare liver cancer subtype with a poor prognosis.
- Accurate prediction of cancer-specific survival (CSS) is crucial for managing SHC patients.
Purpose of the Study:
- To identify independent prognostic factors for CSS in SHC.
- To develop and validate an efficient nomogram for predicting CSS in SHC.
Main Methods:
- Retrieved data from the SEER database for 116 SHC patients (training cohort).
- Utilized LASSO and Cox regression to identify prognostic factors and construct a nomogram (PEM).
- Assessed nomogram accuracy using C-index, calibration curves, ROC curves, and DCA, with external validation.
Main Results:
- Multivariate analysis identified M stage, primary tumor surgery, and chemotherapy as CSS predictors, along with tumor size.
- The developed PEM demonstrated a high C-index (0.853) for CSS prediction.
- PEM showed superior discrimination compared to BCLC, CLIP, and Okuda systems in validation.
Conclusions:
- The four-factor PEM nomogram accurately predicts prognosis for SHC.
- This model offers a valuable tool for clinical practice in managing SHC.
