Literature DB >> 25690672

A novel prognostic nomogram accurately predicts hepatocellular carcinoma recurrence after liver transplantation: analysis of 865 consecutive liver transplant recipients.

Vatche G Agopian1, Michael Harlander-Locke1, Ali Zarrinpar1, Fady M Kaldas1, Douglas G Farmer1, Hasan Yersiz1, Richard S Finn2, Myron Tong1, Jonathan R Hiatt1, Ronald W Busuttil3.   

Abstract

BACKGROUND: Although radiologic size criteria (Milan/University of California, San Francisco [UCSF]) have led to improved outcomes after liver transplantation (LT) for hepatocellular carcinoma (HCC), recurrence remains a significant challenge. We analyzed our 30-year experience with LT for HCC to identify predictors of recurrence. STUDY
DESIGN: A novel clinicopathologic risk score and prognostic nomogram predicting post-transplant HCC recurrence was developed from a multivariate competing-risk Cox regression analysis of 865 LT recipients with HCC between 1984 and 2013.
RESULTS: Overall patient and recurrence-free survivals were 83%, 68%, 60% and 79%, 63%, and 56% at 1-, 3-, and 5-years, respectively. Hepatocellular carcinoma recurred in 117 recipients, with a median time to recurrence of 15 months, involving the lungs (59%), abdomen/pelvis (38%), liver (35%), bone (28%), pleura/mediastinum (12%), and brain (5%). Multivariate predictors of recurrence included tumor grade/differentiation (G4/poor diff hazard ratio [HR] 8.86; G2-3/mod-poor diff HR 2.56), macrovascular (HR 7.82) and microvascular (HR 2.42) invasion, nondownstaged tumors outside Milan criteria (HR 3.02), nonincidental tumors with radiographic maximum diameter ≥ 5 cm (HR 2.71) and <5 cm (HR 1.55), and pretransplant neutrophil-to-lymphocyte ratio (HR 1.77 per log unit), maximum alpha fetoprotein (HR 1.21 per log unit), and total cholesterol (HR 1.14 per SD). A pretransplantation model incorporating only known radiographic and laboratory parameters had improved accuracy in predicting HCC recurrence (C statistic 0.79) compared with both Milan (C statistic 0.64) and UCSF (C statistic 0.64) criteria alone. A novel clinicopathologic prognostic nomogram included explant pathology and had an excellent ability to predict post-transplant recurrence (C statistic 0.85).
CONCLUSIONS: In the largest single-institution experience with LT for HCC, excellent long-term survival was achieved. Incorporation of routine pretransplantation biomarkers to existing radiographic size criteria significantly improves the ability to predict post-transplant recurrence, and should be considered in recipient selection. A novel clinicopathologic prognostic nomogram accurately predicts HCC recurrence after LT and may guide frequency of post-transplantation surveillance and adjuvant therapy.
Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

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Year:  2014        PMID: 25690672     DOI: 10.1016/j.jamcollsurg.2014.12.025

Source DB:  PubMed          Journal:  J Am Coll Surg        ISSN: 1072-7515            Impact factor:   6.113


  73 in total

1.  A novel multimarker assay for the phenotypic profiling of circulating tumor cells in hepatocellular carcinoma.

Authors:  Colin M Court; Shuang Hou; Paul Winograd; Nicholas H Segel; Qingyu Wilda Li; Yazhen Zhu; Saeed Sadeghi; Richard S Finn; Ekambaram Ganapathy; Min Song; Samuel W French; Bita V Naini; Shonan Sho; Fady M Kaldas; Ronald W Busuttil; James S Tomlinson; Hsian-Rong Tseng; Vatche G Agopian
Journal:  Liver Transpl       Date:  2018-07       Impact factor: 5.799

2.  An FDG PET/CT metabolic parameter-based nomogram for predicting the early recurrence of hepatocellular carcinoma after liver transplantation.

Authors:  Wenjie Miao; Pei Nie; Guangjie Yang; Yangyang Wang; Lei Yan; Yujun Zhao; Ting Yu; Mingming Yu; Fengyu Wu; Wei Rao; Zhenguang Wang
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-04-04       Impact factor: 9.236

3.  Hepatocellular carcinoma (HCC) recurrence and what to do when it happens.

Authors:  Adam S Bodzin
Journal:  Hepatobiliary Surg Nutr       Date:  2016-12       Impact factor: 7.293

4.  Nomograms in Hepatectomy Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma.

Authors:  Jong Man Kim; Choon Hyuck David Kwon; Jae-Won Joh; Heejin Yoo; Kyunga Kim; Dong Hyun Sinn; Gyu-Seong Choi; Joon Hyeok Lee
Journal:  J Gastrointest Surg       Date:  2019-01-22       Impact factor: 3.452

Review 5.  When to consider liver transplantation in hepatocellular carcinoma patients?

Authors:  Ka Wing Ma; Tan To Cheung
Journal:  Hepat Oncol       Date:  2017-07-06

6.  Prognostic stratification and nomogram for survival prediction in hepatocellular carcinoma patients treated with radiotherapy for lymph node metastasis.

Authors:  Chan Woo Wee; Kyubo Kim; Eui Kyu Chie; Su Jong Yu; Yoon Jun Kim; Jung Hwan Yoon
Journal:  Br J Radiol       Date:  2016-07-15       Impact factor: 3.039

7.  Impact of pathological features of primary hepatocellular carcinoma on the outcomes of intrahepatic recurrence management: single center experience from Southern Taiwan.

Authors:  Mahmoud Abdelwahab Ali; Wei-Feng Li; Jing-Houng Wang; Chih-Che Lin; Ying-Ju Chen; Ting-Lung Lin; Tsan-Shiun Lin; Sheng-Nan Lu; Chih-Chi Wang; Chao-Long Chen
Journal:  HPB (Oxford)       Date:  2016-08-25       Impact factor: 3.647

Review 8.  Liver transplantation for hepatocellular carcinoma - factors influencing outcome and disease-free survival.

Authors:  René Fahrner; Felix Dondorf; Michael Ardelt; Yves Dittmar; Utz Settmacher; Falk Rauchfuß
Journal:  World J Gastroenterol       Date:  2015-11-14       Impact factor: 5.742

Review 9.  Liver transplantation for hepatobiliary malignancies: a new era of "Transplant Oncology" has begun.

Authors:  Taizo Hibi; Osamu Itano; Masahiro Shinoda; Yuko Kitagawa
Journal:  Surg Today       Date:  2016-04-29       Impact factor: 2.549

10.  Gadoxetic acid-enhanced MRI as a predictor of recurrence of HCC after liver transplantation.

Authors:  Sunyoung Lee; Kyoung Won Kim; Woo Kyoung Jeong; Myeong-Jin Kim; Gi Hong Choi; Jin Sub Choi; Gi-Won Song; Sung-Gyu Lee
Journal:  Eur Radiol       Date:  2019-08-30       Impact factor: 5.315

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