Liver volume-based prediction model stratifies risks for hepatocellular carcinoma in chronic hepatitis B patients on surveillance

Chung Seop Lee, Yong Jin Jung, Soon Sun Kim, Jae Youn Cheong, Ga Ram Lee, Han Gyeol Kim, Beom Hee Kim, Jung Wha Chung, Eun Sun Jang, Sook-Hyang Jeong, Kyung Ho Lee and Jin-Wook Kim

PLOS ONE, 2018, vol. 13, issue 1, 1-13

Abstract: Background and aim: The aim of this study was to determine whether dynamic computed tomography (CT)-measured liver volume predicts the risk of hepatocellular carcinoma (HCC) when the CT scans do not reveal evidence of HCC in chronic hepatitis B (CHB) patients on surveillance. Methods: This retrospective multicentre cohort study included 1,246 patients who received entecavir and regular HCC surveillance in three tertiary referral centres in South Korea. Liver volumes were measured on portal venous phase CT images. A nomogram was developed based on Cox independent predictors and externally validated. Time-dependent receiver operating characteristic (ROC) analysis was performed for comparison with previous prediction models. Results: Patients who received dynamic CT studies during surveillance had significantly higher risk for HCC compared to patients without CT studies (hazard ratio [HR] = 3.1; p 150; p

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0190261

DOI: 10.1371/journal.pone.0190261

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