Enhanced prediction of 5-year postoperative recurrence in hepatocellular carcinoma by incorporating LASSO regression and random forest models
- 03.03.2025
Erschienen in:
- Verfasst von
- Bing-Bing Su
- Chao-Jie Zhu
- Jun Cao
- Rui Peng
- Dao-Yuan Tu
- Guo-Qing Jiang
- Sheng-Jie Jin
- Qian Wang
- Chi Zhang
- Dou-Sheng Bai
- Erschienen in
- Surgical Endoscopy | Ausgabe 4/2025
Abstract
Background
Tumor recurrence post-operation of hepatocellular carcinoma (HCC) impacts patient prognosis. Identifying and predicting 5-year HCC recurrence following surgery remains a substantial challenge.
Methods
We included 338 patients diagnosed with HCC who underwent surgery from January 2013 to December 2018. Traditional logistic regression, random forest (RF), and LASSO regression methods were used to develop a predictive model for 5-year recurrence. The findings were presented visually using nomogram. The accuracy and sensitivity of the predictive model were evaluated by receiver operating curves (ROC) and decision curve analysis (DCA).
Results
Of the 338 patients, 172 (50.9%) experienced 5 years recurrence, with a gender distribution of 79.7% males. Univariate and multivariate logistic regression analysis identified that three independent predictors of 5-year HCC recurrence (all P < 0.001). The area under the curve (AUC) value of the model (Model-1) constructed was 0.678. Then we combined LASSO regression and RF construct a predictive model including six factors: age, transarterial chemoembolization (TACE), microvascular invasion (MVI), alcohol, size, and number. The AUC of the model (Model-2) constructed was 0.733. DeLong’s test results showed that Model-2 had significantly better prediction ability compared with Model-1 (P = 0.004). DCA also demonstrated that Model-2 had better predictive accuracy (P < 0.05). Then we constructed a nomogram, and Kaplan–Meier analysis showed that patients in the low-risk group had significantly better prognosis than the high (P < 0.001).
Conclusion
The predictive accuracy of our model, incorporating factors, such as age, alcohol, size, number, MVI, and TACE, significantly enhances clinical practice management by accurately forecasting 5 years HCC recurrence.
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- Titel
- Enhanced prediction of 5-year postoperative recurrence in hepatocellular carcinoma by incorporating LASSO regression and random forest models
- Verfasst von
-
Bing-Bing Su
Chao-Jie Zhu
Jun Cao
Rui Peng
Dao-Yuan Tu
Guo-Qing Jiang
Sheng-Jie Jin
Qian Wang
Chi Zhang
Dou-Sheng Bai
- Publikationsdatum
- 03.03.2025
- Verlag
- Springer US
- Erschienen in
-
Surgical Endoscopy / Ausgabe 4/2025
Print ISSN: 0930-2794
Elektronische ISSN: 1432-2218 - DOI
- https://doi.org/10.1007/s00464-025-11631-6
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