Machine Learning Predictive Model to Guide Treatment Allocation for Recurrent Hepatocellular Carcinoma After Surgery.

Autor:	Famularo S; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.; Department of Hepatobiliary and General Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy., Donadon M; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.; Department of Hepatobiliary and General Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy., Cipriani F; Hepatobiliary Surgery Division, 'Vita e Salute' University, Ospedale San Raffaele IRCCS, Milano, Italy., Fazio F; Department of General and Oncological Surgery, Mauriziano Hospital 'Umberto I', Turin, Italy., Ardito F; Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy., Iaria M; Department of Medicine and Surgery, University of Parma, Parma, Italy., Perri P; Division of Hepatobiliarypancreatic Unit, IRCCS - Regina Elena National Cancer Institute, Rome, Italy., Conci S; Division of General and Hepatobiliary Surgery, Department of Surgical Sciences, Dentistry, Gynecology and Pediatrics, University of Verona, Verona, Italy., Dominioni T; Unit of General Surgery 1, University of Pavia and Foundation IRCCS Policlinico San Matteo, Pavia, Italy., Lai Q; General Surgery and Organ Transplantation Unit, Sapienza University of Rome, Umberto I Polyclinic of Rome, Rome, Italy., La Barba G; General and Oncologic Surgery, Morgagni-Pierantoni Hospital, Department of Medical and Surgical Sciences - University of Bologna, Forlì, Italy., Patauner S; Department of General and Pediatric Surgery, Bolzano Central Hospital, Bolzano, Italy., Molfino S; Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy., Germani P; Division of General Surgery, Department of Medical and Surgical Sciences, ASUGI, Trieste, Italy., Zimmitti G; Department of General Surgery, Poliambulanza Foundation Hospital, Brescia, Italy., Pinotti E; Department of Surgery, Ponte San Pietro Hospital, Bergamo, Italy., Zanello M; Alma Mater Studiorum, University of Bologna, AOU Sant'Orsola Malpighi, IRCCS at Maggiore Hospital, Bologna, Italy., Fumagalli L; Department of Emergency and Robotic Surgery, ASST Lecco, Lecco, Italy., Ferrari C; HPB Surgical Unit, San Paolo Hospital, Savona, Italy., Romano M; Department of Surgical, Oncological and Gastroenterological Science (DISCOG), University of Padua, Padua, Italy.; Hepatobiliary and Pancreatic Surgery Unit-Treviso Hospital, Treviso, Italy., Delvecchio A; Department of Hepato-Pancreatic-Biliary Surgery, Miulli Hospital, Bari, Italy., Valsecchi MG; Bicocca Bioinformatics Biostatistics and Bioimaging Centre-B4, School of Medicine and Surgery, University of Milan - Bicocca, Monza, Italy., Antonucci A; Department of Surgery, Monza Policlinic, Monza, Italy., Piscaglia F; Division of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy., Farinati F; Gastroenterology Unit, Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy., Kawaguchi Y; Hepato-Biliary-Pancreatic Surgery Division Department of Surgery, Graduate School of Medicine, University of Tokyo, Tokyo, Japan., Hasegawa K; Hepato-Biliary-Pancreatic Surgery Division Department of Surgery, Graduate School of Medicine, University of Tokyo, Tokyo, Japan., Memeo R; Department of Hepato-Pancreatic-Biliary Surgery, Miulli Hospital, Bari, Italy., Zanus G; Department of Surgical, Oncological and Gastroenterological Science (DISCOG), University of Padua, Padua, Italy.; Hepatobiliary and Pancreatic Surgery Unit-Treviso Hospital, Treviso, Italy., Griseri G; HPB Surgical Unit, San Paolo Hospital, Savona, Italy., Chiarelli M; Department of Emergency and Robotic Surgery, ASST Lecco, Lecco, Italy., Jovine E; Alma Mater Studiorum, University of Bologna, AOU Sant'Orsola Malpighi, IRCCS at Maggiore Hospital, Bologna, Italy., Zago M; Department of Surgery, Ponte San Pietro Hospital, Bergamo, Italy.; Department of Emergency and Robotic Surgery, ASST Lecco, Lecco, Italy., Abu Hilal M; Department of General Surgery, Poliambulanza Foundation Hospital, Brescia, Italy., Tarchi P; Division of General Surgery, Department of Medical and Surgical Sciences, ASUGI, Trieste, Italy., Baiocchi GL; Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy., Frena A; Department of General and Pediatric Surgery, Bolzano Central Hospital, Bolzano, Italy., Ercolani G; General and Oncologic Surgery, Morgagni-Pierantoni Hospital, Department of Medical and Surgical Sciences - University of Bologna, Forlì, Italy., Rossi M; General Surgery and Organ Transplantation Unit, Sapienza University of Rome, Umberto I Polyclinic of Rome, Rome, Italy., Maestri M; Unit of General Surgery 1, University of Pavia and Foundation IRCCS Policlinico San Matteo, Pavia, Italy., Ruzzenente A; Division of General and Hepatobiliary Surgery, Department of Surgical Sciences, Dentistry, Gynecology and Pediatrics, University of Verona, Verona, Italy., Grazi GL; Division of Hepatobiliarypancreatic Unit, IRCCS - Regina Elena National Cancer Institute, Rome, Italy., Dalla Valle R; Department of Medicine and Surgery, University of Parma, Parma, Italy., Romano F; School of Medicine and Surgery, University of Milano-Bicocca, San Gerardo Hospital, Monza, Italy., Giuliante F; Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy., Ferrero A; Department of General and Oncological Surgery, Mauriziano Hospital 'Umberto I', Turin, Italy., Aldrighetti L; Hepatobiliary Surgery Division, 'Vita e Salute' University, Ospedale San Raffaele IRCCS, Milano, Italy., Bernasconi DP; Bicocca Bioinformatics Biostatistics and Bioimaging Centre-B4, School of Medicine and Surgery, University of Milan - Bicocca, Monza, Italy., Torzilli G; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.; Department of Hepatobiliary and General Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy.
Jazyk:	angličtina
Zdroj:	JAMA surgery [JAMA Surg] 2023 Feb 01; Vol. 158 (2), pp. 192-202.
DOI:	10.1001/jamasurg.2022.6697
Abstrakt:	Importance: Clear indications on how to select retreatments for recurrent hepatocellular carcinoma (HCC) are still lacking. Objective: To create a machine learning predictive model of survival after HCC recurrence to allocate patients to their best potential treatment. Design, Setting, and Participants: Real-life data were obtained from an Italian registry of hepatocellular carcinoma between January 2008 and December 2019 after a median (IQR) follow-up of 27 (12-51) months. External validation was made on data derived by another Italian cohort and a Japanese cohort. Patients who experienced a recurrent HCC after a first surgical approach were included. Patients were profiled, and factors predicting survival after recurrence under different treatments that acted also as treatment effect modifiers were assessed. The model was then fitted individually to identify the best potential treatment. Analysis took place between January and April 2021. Exposures: Patients were enrolled if treated by reoperative hepatectomy or thermoablation, chemoembolization, or sorafenib. Main Outcomes and Measures: Survival after recurrence was the end point. Results: A total of 701 patients with recurrent HCC were enrolled (mean [SD] age, 71 [9] years; 151 [21.5%] female). Of those, 293 patients (41.8%) received reoperative hepatectomy or thermoablation, 188 (26.8%) received sorafenib, and 220 (31.4%) received chemoembolization. Treatment, age, cirrhosis, number, size, and lobar localization of the recurrent nodules, extrahepatic spread, and time to recurrence were all treatment effect modifiers and survival after recurrence predictors. The area under the receiver operating characteristic curve of the predictive model was 78.5% (95% CI, 71.7%-85.3%) at 5 years after recurrence. According to the model, 611 patients (87.2%) would have benefited from reoperative hepatectomy or thermoablation, 37 (5.2%) from sorafenib, and 53 (7.6%) from chemoembolization in terms of potential survival after recurrence. Compared with patients for which the best potential treatment was reoperative hepatectomy or thermoablation, sorafenib and chemoembolization would be the best potential treatment for older patients (median [IQR] age, 78.5 [75.2-83.4] years, 77.02 [73.89-80.46] years, and 71.59 [64.76-76.06] years for sorafenib, chemoembolization, and reoperative hepatectomy or thermoablation, respectively), with a lower median (IQR) number of multiple recurrent nodules (1.00 [1.00-2.00] for sorafenib, 1.00 [1.00-2.00] for chemoembolization, and 2.00 [1.00-3.00] for reoperative hepatectomy or thermoablation). Extrahepatic recurrence was observed in 43.2% (n = 16) for sorafenib as the best potential treatment vs 14.6% (n = 89) for reoperative hepatectomy or thermoablation as the best potential treatment and 0% for chemoembolization as the best potential treatment. Those profiles were used to constitute a patient-tailored algorithm for the best potential treatment allocation. Conclusions and Relevance: The herein presented algorithm should help in allocating patients with recurrent HCC to the best potential treatment according to their specific characteristics in a treatment hierarchy fashion.
Databáze:	MEDLINE
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