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Liver Stiffness Value-Based Risk Estimation of Late Recurrence after Curative Resection of Hepatocellular Carcinoma: Development and Validation of a Predictive Model

Authors
 Kyu Sik Jung  ;  Ji Hong Kim  ;  Seung Up Kim  ;  Kijun Song  ;  Beom Kyung Kim  ;  Jun Yong Park  ;  Do Young Kim  ;  Sang Hoon Ahn  ;  Do Chang Moon  ;  In Ji Song  ;  Gi Hong Choi  ;  Young Nyun Park  ;  Kwang-Hyub Han 
Citation
 PLOS ONE, Vol.9(6) : e99167, 2014 
Journal Title
PLOS ONE
Issue Date
2014
MeSH
Adult ; Aged ; Aged, 80 and over ; Area Under Curve ; Carcinoma, Hepatocellular/pathology ; Carcinoma, Hepatocellular/surgery* ; Diagnostic Imaging* ; Female ; Follow-Up Studies ; Humans ; Liver/pathology* ; Liver/surgery ; Liver Neoplasms/pathology ; Liver Neoplasms/surgery* ; Male ; Middle Aged ; Neoplasm Grading ; Neoplasm Recurrence, Local/diagnosis* ; Prognosis ; Prospective Studies ; Risk Factors
Abstract
BACKGROUND:
Preoperative liver stiffness (LS) measurement using transient elastography (TE) is useful for predicting late recurrence after curative resection of hepatocellular carcinoma (HCC). We developed and validated a novel LS value-based predictive model for late recurrence of HCC.
METHODS:
Patients who were due to undergo curative resection of HCC between August 2006 and January 2010 were prospectively enrolled and TE was performed prior to operations by study protocol. The predictive model of late recurrence was constructed based on a multiple logistic regression model. Discrimination and calibration were used to validate the model.
RESULTS:
Among a total of 139 patients who were finally analyzed, late recurrence occurred in 44 patients, with a median follow-up of 24.5 months (range, 12.4-68.1). We developed a predictive model for late recurrence of HCC using LS value, activity grade II-III, presence of multiple tumors, and indocyanine green retention rate at 15 min (ICG R15), which showed fairly good discrimination capability with an area under the receiver operating characteristic curve (AUROC) of 0.724 (95% confidence intervals [CIs], 0.632-0.816). In the validation, using a bootstrap method to assess discrimination, the AUROC remained largely unchanged between iterations, with an average AUROC of 0.722 (95% CIs, 0.718-0.724). When we plotted a calibration chart for predicted and observed risk of late recurrence, the predicted risk of late recurrence correlated well with observed risk, with a correlation coefficient of 0.873 (P<0.001).
CONCLUSION:
A simple LS value-based predictive model could estimate the risk of late recurrence in patients who underwent curative resection of HCC.
Files in This Item:
T201401682.pdf Download
DOI
10.1371/journal.pone.0099167
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
Yonsei Authors
Kim, Do Young(김도영)
Kim, Beom Kyung(김범경) ORCID logo https://orcid.org/0000-0002-5363-2496
Kim, Seung Up(김승업) ORCID logo https://orcid.org/0000-0002-9658-8050
Kim, Ji Hong(김지홍)
Moon, Do Chang(문도창)
Park, Young Nyun(박영년) ORCID logo https://orcid.org/0000-0003-0357-7967
Park, Jun Yong(박준용) ORCID logo https://orcid.org/0000-0001-6324-2224
Song, Ki Jun(송기준) ORCID logo https://orcid.org/0000-0003-2505-4112
Song, In Ji(송인지)
Ahn, Sang Hoon(안상훈) ORCID logo https://orcid.org/0000-0002-3629-4624
Jung, Kyu Sik(정규식)
Choi, Gi Hong(최기홍) ORCID logo https://orcid.org/0000-0002-1593-3773
Han, Kwang-Hyub(한광협) ORCID logo https://orcid.org/0000-0003-3960-6539
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/98888
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