Model to predict major complications following liver resection for HCC in patients with metabolic syndrome
Giammauro Berardi 1 2 , Francesca Ratti 3 , Carlo Sposito 4 , Martina Nebbia 5 , Daniel M D'Souza 6 , Franco Pascual 7 , Epameinondas Dogeas 8 , Samer Tohme 8 , Francesco E D'Amico 9 , Remo Alessandris 9 , Ilaria Simonelli 10 , Celeste Del Basso 2 , Nadia Russolillo 11 , Amika Moro 12 , Guido Fiorentini 3 13 , Matteo Serenari 14 , Fernando Rotellar 15 , Giuseppe Zimmitti 16 , Simone Famularo 17 , Tommy Ivanics 18 , Daniel Hoffman 19 , Edwin Onkendi 20 , Yasmin Essaji 21 , Santiago Lopez Ben 22 , Celia Caula 22 , Gianluca Rompianesi 23 , Asmita Chopra 24 , Mohammed Abu Hilal 16 , Guido Torzilli 17 , Gonzalo Sapisochin 18 , Carlos Corvera 19 , Adnan Alseidi 19 , Scott Helton 21 , Roberto I Troisi 23 , Kerri Simo 24 , Claudius Conrad 25 , Matteo Cescon 14 , Sean Cleary 13 , Choon H D Kwon 12 , Alessandro Ferrero 11 , Giuseppe M Ettorre 2 , Umberto Cillo 9 , David Geller 8 , Daniel Cherqui 7 , Pablo E Serrano 6 , Cristina Ferrone 5 , Vincenzo Mazzaferro 4 , Luca Aldrighetti 3 , T Peter Kingham 1
Background: Metabolic syndrome (MS) is rapidly growing as risk factor for HCC. Liver resection for HCC in patients with MS is associated with increased postoperative risks. There are no data on factors associated with postoperative complications.
Aims: The aim was to identify risk factors and develop and validate a model for postoperative major morbidity after liver resection for HCC in patients with MS, using a large multicentric Western cohort.
Materials and methods: The univariable logistic regression analysis was applied to select predictive factors for 90 days major morbidity. The model was built on the multivariable regression and presented as a nomogram. Performance was evaluated by internal validation through the bootstrap method. The predictive discrimination was assessed through the concordance index.
Results: A total of 1087 patients were gathered from 24 centers between 2001 and 2021. Four hundred and eighty-four patients (45.2%) were obese. Most liver resections were performed using an open approach (59.1%), and 743 (68.3%) underwent minor hepatectomies. Three hundred and seventy-six patients (34.6%) developed postoperative complications, with 13.8% major morbidity and 2.9% mortality rates. Seven hundred and thirteen patients had complete data and were included in the prediction model. The model identified obesity, diabetes, ischemic heart disease, portal hypertension, open approach, major hepatectomy, and changes in the nontumoral parenchyma as risk factors for major morbidity. The model demonstrated an AUC of 72.8% (95% CI: 67.2%-78.2%) (https://childb.shinyapps.io/NomogramMajorMorbidity90days/).
Conclusions: Patients undergoing liver resection for HCC and MS are at high risk of postoperative major complications and death. Careful patient selection, considering baseline characteristics, liver function, and type of surgery, is key to achieving optimal outcomes.