Published online Nov 26, 2019. doi: 10.12998/wjcc.v7.i22.3734
Peer-review started: September 3, 2019
First decision: September 23, 2019
Revised: October 18, 2019
Accepted: October 30, 2019
Article in press: October 29, 2019
Published online: November 26, 2019
Processing time: 83 Days and 23.8 Hours
Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer. HCC predominantly develops in patients with liver cirrhosis. At present, hepatectomy is still the main treatment for HCC. However, post-hepatectomy liver failure (PHLF) is one of the most serious complications following hepatic resection, despite improvements in surgical and post-operative management. Thus, it is of great clinical significance to evaluate the risk of PHLF before operation to reduce its incidence after hepatectomy.
At present, the models of predicting the occurrence of PHLF after hepatectomy do not meet the clinical needs. We need to have new forecasting indicators to further improve the models for predicting the occurrence of PHLF. The purpose of our study was to evaluate the value of model for end-stage liver disease (MELD) score combined with standardized future liver remnant (sFLR) volume in predicting PHLF in patients undergoing hepatectomy for liver cancer.
To study the value of MELD score combined with sFLR volume in predicting PHLF in patients undergoing hepatectomy for HCC, and explore the application of sFLR/MELD score in the hepatectomy and treatment of HCC, so as to provide reference for clinical treatment of this malignancy.
A total of 238 patients with HCC treated at our hospital from January 2015 to January 2018 were selected as a study group. Discrimination of sFLR volume, MELD score, and sFLR/MELD ratio to predict PHLF was evaluated according to the univariable and multivariable analyses, χ2 test, and receiver operating characteristic curve analysis.
The incidence of PHLF increased with the decrease of sFLR volume and the increase of MELD score. Moreover, both sFLR volume and MELD score were independent risk factors for PHLF. The cut-off value of the sFLR/MELD score to predict PHLF was 0.078, with an AUC of 0.845, which was superior to MELD score or sFLR volume alone.
sFLR volume combined with MELD score can effectively guide early treatment after hepatectomy, so as to improve prognosis and reduce mortality. The model also provides a new strategy for preoperative evaluation of hepatectomy.
Future studies are needed to further confirm the relationship between sFLR/MELD score and patient survival rate so that it can be better used in clinical practice. What’s more, to further consummate the follow-up time of patients and improve the accuracy of sFLR/MELD score is the next step for further analysis.