Background: Post-hepatectomy liver failure (PHLF) is a dreaded complication following liver resection for hepatocellular carcinoma (HCC) with a high mortality rate. We sought to develop a score based on preoperative factors to predict PHLF.
Methods: Patients who underwent resection for HCC between 2000 and 2020 were identified from an international multi-institutional database. Factors associated with PHLF were identified and used to develop a preoperative comorbidity-tumor burden-liver function (CTF) predictive score.
Results: Among 1785 patients, 106 (5.9%) experienced PHLF. On multivariate analysis, several factors were associated with PHLF including high Charlson comorbidity index (CCI ≥ 5) (OR 2.80, 95%CI, 1.08-7.26), albumin-bilirubin (ALBI) (OR 1.99, 95%CI, 1.10-3.56), and tumor burden score (TBS) (OR 1.06, 95%CI, 1.02-1.11) (all p < 0.05). Using the beta-coefficients of these variables, a weighted predictive score was developed and made available online ( https://alaimolaura.shinyapps.io/PHLFriskCalculator/ ). The CTF score (c-index = 0.67) performed better than Child-Pugh score (CPS) (c-index = 0.53) or Barcelona clinic liver cancer system (BCLC) (c-index = 0.57) to predict PHLF. A high CTF score was also an independent adverse prognostic factor for survival (HR 1.61, 95%CI, 1.12-2.30) and recurrence (HR 1.36, 95%CI, 1.08-1.71) (both p = 0.01).
Conclusion: Roughly 1 in 20 patients experienced PHLF following resection of HCC. Patient (i.e., CCI), tumor (i.e., TBS), and liver function (i.e., ALBI) factors were associated with risk of PHLF. These preoperative factors were incorporated into a novel CTF tool that was made available online, which outperformed other previously proposed tools.
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http://dx.doi.org/10.1007/s11605-022-05451-5 | DOI Listing |
HPB (Oxford)
December 2024
Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA. Electronic address:
Background: We sought to define textbook outcome in liver surgery (TOLS) for intrahepatic cholangiocarcinoma (ICC) by considering the implications of perioperative outcomes on overall survival (OS).
Methods: Using a multi-institutional database, TOLS for ICC was defined by employing novel machine learning (ML) models to identify perioperative factors most strongly predictive of OS ≥ 12 months. Subsequently, clinicopathologic factors associated with achieving TOLS were investigated.
HPB (Oxford)
December 2024
Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, United States. Electronic address:
Objective: We sought to develop a machine learning (ML) preoperative model to predict bile leak following hepatectomy for primary and secondary liver cancer.
Methods: An eXtreme Gradient Boosting (XGBoost) model was developed to predict post-hepatectomy bile leak using data from the ACS-NSQIP database. The model was externally validated using data from hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) multi-institutional databases.
Sci Rep
January 2025
Department of Gastroenterological Surgery I, Hokkaido University Graduate School of Medicine, N15 W7 Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
Diacylglycerol kinases (DGKs) phosphorylate diacylglycerol to generate phosphatidic acid, which plays important roles in intracellular signal transduction. DGKα is reportedly associated with progression of tumors, including hepatocellular carcinomas, but its relationship with liver regeneration has not been examined. The purpose of this research is to elucidate the role of DGKα in liver regeneration.
View Article and Find Full Text PDFSci Adv
January 2025
School of Basic Medicine, Qingdao University, 308 Ningxia Road, Qingdao 266071, China.
Acta Radiol
December 2024
Department of Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea.
Background: Liver dysfunction has been reported as a risk factor for predicting complications after hepatectomy. In patients with liver cirrhosis (LC) who underwent hepatectomy, a Functional Liver Imaging Score (FLIS), derived from gadoxetic acid-enhanced magnetic resonance imaging (MRI), has never been investigated as a predictor of clinically significant post-hepatectomy complications.
Purpose: To evaluate whether FLIS can predict post-hepatectomy complications in patients with LC.
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