A novel preoperative predictive model of 90-day mortality after liver resection for huge hepatocellular carcinoma.

Abstract

BACKGROUND:

Hepatectomy for huge hepatocellular carcinoma (HCC) (diameter ≥10 cm) is characterized by high mortality. This study aimed to establish a preoperative model to evaluate the risk of postoperative 90-day mortality for huge HCC patients.

METHODS:

We retrospectively enrolled 1,127 consecutive patients and prospectively enrolled 93 patients with huge HCC who underwent hepatectomy (training cohort, n=798; validation cohort, n=329; prospective cohort, n=93) in our institute. Based on independent preoperative predictors of 90-day mortality, we established a logistic regression model and visualized the model by nomogram.

RESULTS:

The 90-day mortality rates were 9.6%, 9.2%, and 10.9% in the training, validation, and prospective cohort. The α-fetoprotein (AFP) level, the prealbumin levels, and the presence of portal vein tumor thrombosis (PVTT) were preoperative independent predictors of 90-day mortality. A logistic regression model, AFP-prealbumin-PVTT score (APP score), was subsequently established and showed good performance in predicting 90-day mortality (training cohort, AUC =0.87; validation cohort, AUC =0.91; prospective cohort, AUC =0.93). Using a cut-off of -1.96, the model could stratify patients into low risk (≤-1.96) and high risk (>-1.96) with different 90-day mortality rates (~30% vs. ~2%). Furthermore, the predictive performance for 90-day mortality and overall survival was significantly superior to the Child-Pugh score, the model of end-stage liver disease (MELD) score, and the albumin-bilirubin (ALBI) score.

CONCLUSIONS:

The APP score can precisely predict postoperative 90-day mortality as well as long-term survival for patients with huge HCC, assisting physician selection of suitable candidates for liver resection and improving the safety and efficacy of surgical treatment.

• Authors: Yue Yin, Jian-Wen Cheng, Fei-Yu Chen, Xu-Xiao Chen, Xin Zhang, Ao Huang, De-Zhen Guo, Yu-Peng Wang, Ya Cao, Jia Fan, Jian Zhou, Xin-Rong Yang
• Journal: Annals of translational medicine (Ann Transl Med) Vol. 9 Issue 9 Pg. 774 (May 2021) ISSN: 2305-5839 [Print] China
• PMID: 34268387 (Publication Type: Journal Article)
• Copyright: 2021 Annals of Translational Medicine. All rights reserved.