Claudia Campani1, Alessandro Vitale2, Gabriele Dragoni1, Umberto Arena1, Giacomo Laffi1, Umberto Cillo2, Edoardo G Giannini3, Francesco Tovoli4, Gian Ludovico Rapaccini5, Maria Di Marco6, Eugenio Caturelli7, Marco Zoli8, Rodolfo Sacco9, Giuseppe Cabibbo10, Andrea Mega11, Maria Guarino12, Antonio Gasbarrini13, Gianluca Svegliati-Baroni14, Francesco Giuseppe Foschi15, Elisabetta Biasini16, Alberto Masotto17, Gerardo Nardone18, Giovanni Raimondo19, Francesco Azzaroli20, Gianpaolo Vidili21,22, Maurizia Rossana Brunetto23, Fabio Farinati2, Franco Trevisani24, Fabio Marra1. 1. Internal Medicine and Hepatology Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy. 2. Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy. 3. Gastroenterology Unit, Department of Internal Medicine, University of Genoa, IRCCS Policlinico San Martino, Genoa, Italy. 4. Internal Medicine-Piscaglia Unit, Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, University of Bologna, Bologna, Italy. 5. Gastroenterology Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy. 6. Medicine Unit, Bolognini Hospital, Seriate, Italy. 7. Gastroenterology Unit, Belcolle Hospital, Viterbo, Italy. 8. Internal Medicine-Zoli Unit, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy. 9. Gastroenterology and Digestive Endoscopy Unit, Foggia University Hospital, Foggia, Italy. 10. Gastroenterology & Hepatology Unit, Department of Health Promotion, Mother & Child Care, Internal Medicine & Medical Specialties, PROMISE, University of Palermo, Palermo, Italy. 11. Gastroenterology Unit, Bolzano Regional Hospital, Bolzano, Italy. 12. Gastroenterology Unit, Department of Clinical Medicine and Surgery, University of Naples "Federico II", Naples, Italy. 13. Internal Medicine and Gastroenterology Unit, Policlinico Gemelli, Università Cattolica del Sacro Cuore, Rome, Italy. 14. Liver Injury and Transplant Unit, and Obesity Center, Polytechnic University of Marche, Ancona, Italy. 15. Department of Internal Medicine, Ospedale per gli Infermi di Faenza, Faenza, Italy. 16. Infectious Diseases and Hepatology Unit, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy. 17. Gastroenterology Unit, Ospedale Sacro Cuore Don Calabria, Negrar, Italy. 18. Hepato-Gastroenterology Unit, Department of Clinical Medicine and Surgery, University of Naples "Federico II", Naples, Italy. 19. Clinical and Molecular Hepatology Unit, Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy. 20. Gastroenterology Unit, Department of Surgical and Medical Sciences, Alma Mater Studiorum - Università of Bologna, Bologna, Italy. 21. Department of Medical, Surgical and Experimental Sciences, Sassari, Italy. 22. Clinica Medica Unit, University of Sassari, Azienda Ospedaliero-Universitaria di Sassari, Sassari, Italy. 23. Hepatology and Liver Physiopathology Laboratory and Internal Medicine, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy. 24. Department of Medical and Surgical Sciences, Semeiotics Unit, Alma Mater Studiorum-University of Bologna, Bologna, Italy.
Abstract
INTRODUCTION: The prognosis of patients undergoing transarterial chemoembolization (TACE) is extremely variable, and a confounding factor is that TACE is often repeated several times. We retrospectively evaluated the accuracy of different prognostic scores and staging systems in estimating overall survival (OS) in patients with hepatocellular carcinoma (HCC). METHODS: An analysis considering prognostic models as time-varying variables was performed, calculating OS from the time of TACE to the time of the subsequent treatment. Total follow-up time for each patient was therefore split into several observation times accounting for each TACE procedure. Values of the likelihood ratio test (LRT) and Akaike information criterion (AIC) were used to compare different systems. Univariable and multivariable analyses were conducted to identify additional factors predictive of OS. We analyzed 1,610 TACE performed in 1,058 patients recorded in the Italian Liver Cancer database from 2008 through 2016. RESULTS: The median OS of the enrolled patients was 41 months. According to LRT χ2 and AIC values based on the time-varying analysis, mHAP-III achieved the best values (41.72 and 4,625.49, respectively, p < 0.0001), indicating the highest predictive performance compared with all other scores (HAP, mHAP-II, ALBI, and pALBI) and staging systems (MELD, ITALICA, CLIP, MESH, MESIAH, JIS, HKLC, and BCLC). In the multivariable Cox proportional hazards model, mHAP-III maintained an independent effect on OS (hazard ratio 1.31, 95% CI: 1.10-1.55, p < 0.0001). Time-varying age, alcoholic etiology, radiologic response to TACE, and performing ablation or surgery after TACE were additional significant variables resulting from the multivariable model. CONCLUSION: An innovative time-varying analysis revealed that mHAP-III was the most accurate model in predicting OS in patients with HCC undergoing TACE. Other clinical pre- and post-TACE variables were also found to be relevant for this prediction.
INTRODUCTION: The prognosis of patients undergoing transarterial chemoembolization (TACE) is extremely variable, and a confounding factor is that TACE is often repeated several times. We retrospectively evaluated the accuracy of different prognostic scores and staging systems in estimating overall survival (OS) in patients with hepatocellular carcinoma (HCC). METHODS: An analysis considering prognostic models as time-varying variables was performed, calculating OS from the time of TACE to the time of the subsequent treatment. Total follow-up time for each patient was therefore split into several observation times accounting for each TACE procedure. Values of the likelihood ratio test (LRT) and Akaike information criterion (AIC) were used to compare different systems. Univariable and multivariable analyses were conducted to identify additional factors predictive of OS. We analyzed 1,610 TACE performed in 1,058 patients recorded in the Italian Liver Cancer database from 2008 through 2016. RESULTS: The median OS of the enrolled patients was 41 months. According to LRT χ2 and AIC values based on the time-varying analysis, mHAP-III achieved the best values (41.72 and 4,625.49, respectively, p < 0.0001), indicating the highest predictive performance compared with all other scores (HAP, mHAP-II, ALBI, and pALBI) and staging systems (MELD, ITALICA, CLIP, MESH, MESIAH, JIS, HKLC, and BCLC). In the multivariable Cox proportional hazards model, mHAP-III maintained an independent effect on OS (hazard ratio 1.31, 95% CI: 1.10-1.55, p < 0.0001). Time-varying age, alcoholic etiology, radiologic response to TACE, and performing ablation or surgery after TACE were additional significant variables resulting from the multivariable model. CONCLUSION: An innovative time-varying analysis revealed that mHAP-III was the most accurate model in predicting OS in patients with HCC undergoing TACE. Other clinical pre- and post-TACE variables were also found to be relevant for this prediction.
Authors: Wolfgang Sieghart; Florian Hucke; Matthias Pinter; Ivo Graziadei; Wolfgang Vogel; Christian Müller; Harald Heinzl; Michael Trauner; Markus Peck-Radosavljevic Journal: Hepatology Date: 2013-05-03 Impact factor: 17.425
Authors: Tomi Akinyemiju; Semaw Abera; Muktar Ahmed; Noore Alam; Mulubirhan Assefa Alemayohu; Christine Allen; Rajaa Al-Raddadi; Nelson Alvis-Guzman; Yaw Amoako; Al Artaman; Tadesse Awoke Ayele; Aleksandra Barac; Isabela Bensenor; Adugnaw Berhane; Zulfiqar Bhutta; Jacqueline Castillo-Rivas; Abdulaal Chitheer; Jee-Young Choi; Benjamin Cowie; Lalit Dandona; Rakhi Dandona; Subhojit Dey; Daniel Dicker; Huyen Phuc; Donatus U. Ekwueme; Maysaa El Sayed Zaki; Florian Fischer; Thomas Fürst; Jamie Hancock; Simon I. Hay; Peter Hotez; Sun Ha Jee; Amir Kasaeian; Yousef Khader; Young-Ho Khang; Anil Kumar; Michael Kutz; Heidi Larson; Alan Lopez; Raimundas Lunevicius; Reza Malekzadeh; Colm McAlinden; Toni Meier; Walter Mendoza; Ali Mokdad; Maziar Moradi-Lakeh; Gabriele Nagel; Quyen Nguyen; Grant Nguyen; Felix Ogbo; George Patton; David M. Pereira; Farshad Pourmalek; Mostafa Qorbani; Amir Radfar; Gholamreza Roshandel; Joshua A Salomon; Juan Sanabria; Benn Sartorius; Maheswar Satpathy; Monika Sawhney; Sadaf Sepanlou; Katya Shackelford; Hirbo Shore; Jiandong Sun; Desalegn Tadese Mengistu; Roman Topór-Mądry; Bach Tran; Vasiliy Vlassov; Stein Emil Vollset; Theo Vos; Tolassa Wakayo; Elisabete Weiderpass; Andrea Werdecker; Naohiro Yonemoto; Mustafa Younis; Chuanhua Yu; Zoubida Zaidi; Liguo Zhu; Christopher J. L. Murray; Mohsen Naghavi; Christina Fitzmaurice Journal: JAMA Oncol Date: 2017-12-01 Impact factor: 31.777
Authors: Fabio Farinati; Alessandro Vitale; Gaya Spolverato; Timothy M Pawlik; Teh-la Huo; Yun-Hsuan Lee; Anna Chiara Frigo; Anna Giacomin; Edoardo G Giannini; Francesca Ciccarese; Fabio Piscaglia; Gian Lodovico Rapaccini; Mariella Di Marco; Eugenio Caturelli; Marco Zoli; Franco Borzio; Giuseppe Cabibbo; Martina Felder; Rodolfo Sacco; Filomena Morisco; Elisabetta Biasini; Francesco Giuseppe Foschi; Antonio Gasbarrini; Gianluca Svegliati Baroni; Roberto Virdone; Alberto Masotto; Franco Trevisani; Umberto Cillo Journal: PLoS Med Date: 2016-04-26 Impact factor: 11.069
Authors: Gauri Mishra; Ammar Majeed; Anouk Dev; Guy D Eslick; David J Pinato; Hirofumi Izumoto; Atsushi Hiraoka; Teh-Ia Huo; Po-Hong Liu; Philip J Johnson; Stuart K Roberts Journal: J Gastrointest Cancer Date: 2022-05-30
Authors: Filippo Pelizzaro; Selion Haxhi; Barbara Penzo; Alessandro Vitale; Edoardo G Giannini; Vito Sansone; Gian Ludovico Rapaccini; Maria Di Marco; Eugenio Caturelli; Donatella Magalotti; Rodolfo Sacco; Ciro Celsa; Claudia Campani; Andrea Mega; Maria Guarino; Antonio Gasbarrini; Gianluca Svegliati-Baroni; Francesco Giuseppe Foschi; Andrea Olivani; Alberto Masotto; Gerardo Nardone; Giovanni Raimondo; Francesco Azzaroli; Gianpaolo Vidili; Maurizia Rossana Brunetto; Franco Trevisani; Fabio Farinati Journal: Front Oncol Date: 2022-01-31 Impact factor: 6.244