Hidetoshi Nitta1, Marc-Antoine Allard2, Mylène Sebagh3, Vincent Karam2, Oriana Ciacio2, Gabriella Pittau2, Eric Vibert2, Antonio Sa Cunha2, Daniel Cherqui2, Denis Castaing2, Henri Bismuth2, Catherine Guettier4, Didier Samuel2, Hideo Baba5, René Adam2. 1. Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France; Departement of Gastroenterological Surgery, Graduate School of Life Sciences, Kumamoto University, Japan. Electronic address: hnitta5085@gmail.com. 2. Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France. 3. Departement of Pathology, Hôpital Paul Brousse, Assistance Publique-Hôpitaux de Paris, Villejuif, France. 4. Departement of Pathology, Bicêtre University Hospital, Université Paris-Sud, Le Kremlin-Bicêtre, Ile-de-France, France. 5. Departement of Gastroenterological Surgery, Graduate School of Life Sciences, Kumamoto University, Japan.
Abstract
BACKGROUND: Microvascular invasion is the strongest prognostic factor of survival in patients with hepatocellular carcinoma. We therefore developed a predictive model for microvascular invasion of hepatocellular carcinoma to help guide treatment strategies in patients scheduled for either hepatic resection or liver transplantation. METHODS: Patients with hepatocellular carcinoma who underwent hepatic resection or liver transplantation from 1994 to 2016 were divided into training and validation cohorts. A predictive model for microvascular invasion was developed based on microvascular invasion risk factors in the training cohort and validated in the validation cohort. RESULTS: A total of 910 patients (425 having received hepatic resection, 485 having received liver transplantation) were included in the training (n = 637) and validation (n = 273) cohorts. Multivariate analysis identified α-fetoprotein ≥100 ng/mL (relative risk 3.05, P < .0001), tumor size ≥40 mm (relative risk 1.98, P = .0002), nonboundary hepatocellular carcinoma type (relative risk 1.91, P = .001), neutrophil-to-lymphocyte ratio (relative risk 1.86, P = .002), and aspartate aminotransferase (relative risk 1.53, P = .02) as associated with microvascular invasion. The estimated probability of microvascular invasion ranged from 17.0% in patients with none of these factors to 86.9% in the presence of all factors. This model achieved a C-index of 0.732 in the validation cohort. The 5-year overall survival of patients with ≥50% probability of microvascular invasion was poorer than that of patients with <50% probability (hepatic resection; 39.1% vs 61.2%, P < .0001, liver transplantation; 5-year overall survival, 54.8% vs 79.0%, P = .05). CONCLUSION: This model developed from preoperative data allows reliable prediction of microvascular invasion in candidates for either hepatic resection or liver transplantation.
BACKGROUND: Microvascular invasion is the strongest prognostic factor of survival in patients with hepatocellular carcinoma. We therefore developed a predictive model for microvascular invasion of hepatocellular carcinoma to help guide treatment strategies in patients scheduled for either hepatic resection or liver transplantation. METHODS:Patients with hepatocellular carcinoma who underwent hepatic resection or liver transplantation from 1994 to 2016 were divided into training and validation cohorts. A predictive model for microvascular invasion was developed based on microvascular invasion risk factors in the training cohort and validated in the validation cohort. RESULTS: A total of 910 patients (425 having received hepatic resection, 485 having received liver transplantation) were included in the training (n = 637) and validation (n = 273) cohorts. Multivariate analysis identified α-fetoprotein ≥100 ng/mL (relative risk 3.05, P < .0001), tumor size ≥40 mm (relative risk 1.98, P = .0002), nonboundary hepatocellular carcinoma type (relative risk 1.91, P = .001), neutrophil-to-lymphocyte ratio (relative risk 1.86, P = .002), and aspartate aminotransferase (relative risk 1.53, P = .02) as associated with microvascular invasion. The estimated probability of microvascular invasion ranged from 17.0% in patients with none of these factors to 86.9% in the presence of all factors. This model achieved a C-index of 0.732 in the validation cohort. The 5-year overall survival of patients with ≥50% probability of microvascular invasion was poorer than that of patients with <50% probability (hepatic resection; 39.1% vs 61.2%, P < .0001, liver transplantation; 5-year overall survival, 54.8% vs 79.0%, P = .05). CONCLUSION: This model developed from preoperative data allows reliable prediction of microvascular invasion in candidates for either hepatic resection or liver transplantation.
Authors: Joonho Jeong; Jung Gu Park; Kwang Ill Seo; Ji Hyun Ahn; Jae Chun Park; Byung Cheol Yun; Sang Uk Lee; Jin Wook Lee; Jong Hyouk Yun Journal: Medicine (Baltimore) Date: 2021-07-09 Impact factor: 1.889