Analysis of factors influencing early recurrence for patients with initially unresectable hepa-tocellular carcinoma who underwent liver resection following downstaging treatment and construction of a predictive model: a multicenter study
10.3760/cma.j.cn115610-20250106-00011
- VernacularTitle:初始不可切除肝细胞癌降期后行肝切除术患者早期复发影响因素分析及预测模型构建的多中心研究
- Author:
Yun YANG
1
;
Peng LU
;
Kongying LIN
;
Zheng DANG
;
Wei GUO
;
Zeya PAN
;
Weiping ZHOU
Author Information
1. 海军军医大学第三附属医院(上海东方肝胆外科医院）肝外三科，上海 200438
- Publication Type:Journal Article
- Keywords:
Liver neoplasms;
Nomogram;
Downstaging treatment;
Salvage liver resec-tion;
Early recurrence
- From:
Chinese Journal of Digestive Surgery
2025;24(2):223-235
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the factors influencing early recurrence for patients with initially unresectable hepatocellular carcinoma (HCC) who underwent salvage liver resection (SLR) following transcatheter arterial chemoembolization-based downstaging treatment, and construct a predictive model to evaluate its predicting performance.Methods:The retrospective cohort study was constructed. The clinicopathological data of 305 patients with initially unresectable HCC who were admitted to 4 medical centers in China, including the Third Affiliated Hospital of Naval Medical University (Shanghai Eastern Hepatobiliary Surgery Hospital) et al, from January 2019 to December 2021 were collected. There were 286 males and 19 females, aged (48.7±10.4)years. A total of 133 patients who were admitted from January 2019 to December 2020 were set as the training cohort, and the other 172 patients who were admitted from January to December 2021 were set as the validation cohort. Observation indicators: (1) postoperative recurrence-free survival in HCC patients; (2) analysis of factors influencing postoperative early recurrence in HCC patients; (3) construction and validation of the predictive model. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data was conducted using the rank sum test. Univariate and multivariate analyses were conducted using the Cox regre-ssion model. The Kaplan-Meier method was used to calculate survival. The Log-rank test was used for survival analysis. The predicting performance of the model was evaluated using the concordance index (C-index) and the area under curve (AUC) of time-dependent receiver operating characteristic (ROC) curve, and the accuracy of the model was validated using the calibration curve. The total net gain of the model was evaluated using the decision curve. Results:(1) Postoperative recurrence-free survival in HCC patients. The recurrence-free survival time of 133 HCC patients in the training cohort was 10.0(range, 1.5-24.0)months, with 1-, 2-year recurrence-free survival rate of 47.3% and 36.8%. The recurrence-free survival time of 172 HCC patients in the validation cohort was 11.0(range, 1.0-24.0)months, with 1-, 2-year recurrence-free survival rate of 51.7% and 37.2%. There was no significant difference in recurrence-free survival between patients in the training cohort and the validation cohort ( χ2=0.075, P>0.05). (2) Analysis of factors influencing postoperative early recur-rence in HCC patients. Results of multivariate analysis showed that tumor burden prior to down-staging treatment, grade of albumin-bilirubin (ALBI) score prior to SLR, alpha-fetoprotein (AFP) half-life prior to SLR, and tumor response prior to SLR were independent factors influencing early recurrence in HCC patients after surgery [ hazard ratio=3.212, 2.526, 2.304, 1.575, 95% confidence interal ( CI) as 1.262-8.175, 1.324-4.818, 1.477-3.595, 1.138-2.180, P<0.05]. (3) Construction and validation of the predictive model. A nomogram predictive model for postoperative early recurrence was constructed base on the results of multivariate analysis. The C-index of predictive model was 0.786 for the training cohort and 0.734 for the validation cohort. The AUC of ROC curve of nomogram predictive model for 12-, 18-, and 24-month recurrence-free survival rate in the training cohort were 0.890 (95% CI as 0.836-0.944), 0.895 (95% CI as 0.842-0.947), and 0.887 (95% CI as 0.831-0.942), respectively. The AUC of ROC curve of nomogram predictive model for 12-, 18-, and 24-month recurrence-free survival rate in the validation cohort were 0.845 (95% CI as 0.781-0.909], 0.888 (95% CI as 0.826-0.950), and 0.919 (95% CI as 0.870-0.968), respectively. Results of calibration curve showed high consistency between the predicted results of nomogram predictive model and actual outcomes. Results of decision curve showed the nomogram predictive model with a good total net gain at a threshold of 0.10-0.50. Conclusions:Tumor burden prior to downstaging treatment, grade of ALBI score prior to SLR, AFP half-life prior to SLR, and tumor response prior to SLR are independent factors influencing early recurrence in initially unresectable HCC patients undergoing SLR following downstaging treatment. The nomogram predictive model based on these factors can effectively evaluate the prognosis of this patient population.
