Yutaka Endo1, Laura Alaimo1,2, Henrique A Lima1, Zorays Moazzam1, Francesca Ratti3, Hugo P Marques4, Olivier Soubrane5, Vincent Lam6, Minoru Kitago7, George A Poultsides8, Irinel Popescu9, Sorin Alexandrescu9, Guillaume Martel10, Aklile Workneh10, Alfredo Guglielmi2, Tom Hugh11, Luca Aldrighetti3, Itaru Endo12, Timothy M Pawlik13. 1. Department of Surgery, The Urban Meyer III and Shelley Meyer Chair for Cancer Research, Health Services Management and Policy, James Comprehensive Cancer Center, The Ohio State University Wexner Medical Center, Columbus, OH, USA. 2. Department of Surgery, University of Verona, Verona, Italy. 3. Department of Surgery, Ospedale San Raffaele, Milan, Italy. 4. Department of Surgery, Curry Cabral Hospital, Lisbon, Portugal. 5. Department of Hepatibiliopancreatic Surgery, APHP, Beaujon Hospital, Clichy, France. 6. Department of Surgery, Westmead Hospital, Sydney, NSW, Australia. 7. Department of Surgery, Keio University, Tokyo, Japan. 8. Department of Surgery, Stanford University, Stanford, CA, USA. 9. Department of Surgery, Fundeni Clinical Institute, Bucharest, Romania. 10. Department of Surgery, University of Ottawa, Ottawa, ON, Canada. 11. Department of Surgery, School of Medicine, The University of Sydney, Sydney, NSW, Australia. 12. Yokohama City University School of Medicine, Yokohama, Japan. 13. Department of Surgery, The Urban Meyer III and Shelley Meyer Chair for Cancer Research, Health Services Management and Policy, James Comprehensive Cancer Center, The Ohio State University Wexner Medical Center, Columbus, OH, USA. Tim.Pawlik@osumc.edu.
Abstract
BACKGROUND: The presence of microvascular invasion (MVI) has been highlighted as an important determinant of hepatocellular carcinoma (HCC) prognosis. We sought to build and validate a novel model to predict MVI in the preoperative setting. METHODS: Patients who underwent curative-intent surgery for HCC between 2000 and 2020 were identified using a multi-institutional database. Preoperative predictive models for MVI were built, validated, and used to develop a web-based calculator. RESULTS: Among 689 patients, MVI was observed in 323 patients (46.9%). On multivariate analysis in the test cohort, preoperative parameters associated with MVI included α-fetoprotein (AFP; odds ratio [OR] 1.50, 95% confidence interval [CI] 1.23-1.83), imaging tumor burden score (TBS; hazard ratio [HR] 1.11, 95% CI 1.04-1.18), and neutrophil-to-lymphocyte ratio (NLR; OR 1.18, 95% CI 1.03-1.35). An online calculator to predict MVI was developed based on the weighted β-coefficients of these three variables ( https://yutaka-endo.shinyapps.io/MVIrisk/ ). The c-index of the test and validation cohorts was 0.71 and 0.72, respectively. Patients with a high risk of MVI had worse disease-free survival (DFS) and overall survival (OS) compared with low-risk MVI patients (3-year DFS: 33.0% vs. 51.9%, p < 0.001; 5-year OS: 44.2% vs. 64.8%, p < 0.001). DFS was worse among patients who underwent an R1 versus R0 resection among those patients at high risk of MVI (R0 vs. R1 resection: 3-year DFS, 36.3% vs. 16.1%, p = 0.002). In contrast, DFS was comparable among patients at low risk of MVI regardless of margin status (R0 vs. R1 resection: 3-year DFS, 52.9% vs. 47.3%, p = 0.16). CONCLUSION: Preoperative assessment of MVI using the online tool demonstrated very good accuracy to predict MVI.
BACKGROUND: The presence of microvascular invasion (MVI) has been highlighted as an important determinant of hepatocellular carcinoma (HCC) prognosis. We sought to build and validate a novel model to predict MVI in the preoperative setting. METHODS: Patients who underwent curative-intent surgery for HCC between 2000 and 2020 were identified using a multi-institutional database. Preoperative predictive models for MVI were built, validated, and used to develop a web-based calculator. RESULTS: Among 689 patients, MVI was observed in 323 patients (46.9%). On multivariate analysis in the test cohort, preoperative parameters associated with MVI included α-fetoprotein (AFP; odds ratio [OR] 1.50, 95% confidence interval [CI] 1.23-1.83), imaging tumor burden score (TBS; hazard ratio [HR] 1.11, 95% CI 1.04-1.18), and neutrophil-to-lymphocyte ratio (NLR; OR 1.18, 95% CI 1.03-1.35). An online calculator to predict MVI was developed based on the weighted β-coefficients of these three variables ( https://yutaka-endo.shinyapps.io/MVIrisk/ ). The c-index of the test and validation cohorts was 0.71 and 0.72, respectively. Patients with a high risk of MVI had worse disease-free survival (DFS) and overall survival (OS) compared with low-risk MVI patients (3-year DFS: 33.0% vs. 51.9%, p < 0.001; 5-year OS: 44.2% vs. 64.8%, p < 0.001). DFS was worse among patients who underwent an R1 versus R0 resection among those patients at high risk of MVI (R0 vs. R1 resection: 3-year DFS, 36.3% vs. 16.1%, p = 0.002). In contrast, DFS was comparable among patients at low risk of MVI regardless of margin status (R0 vs. R1 resection: 3-year DFS, 52.9% vs. 47.3%, p = 0.16). CONCLUSION: Preoperative assessment of MVI using the online tool demonstrated very good accuracy to predict MVI.
Authors: Mahul B Amin; Frederick L Greene; Stephen B Edge; Carolyn C Compton; Jeffrey E Gershenwald; Robert K Brookland; Laura Meyer; Donna M Gress; David R Byrd; David P Winchester Journal: CA Cancer J Clin Date: 2017-01-17 Impact factor: 508.702