Development and Validation of a Clinical Scoring System for Predicting Risk of HCC in Asymptomatic Individuals Seropositive for Anti-HCV Antibodies

The development of a risk assessment tool for long-term hepatocellular carcinoma risk would be helpful in identifying high-risk patients and providing information of clinical consultation. The model derivation and validation cohorts consisted of 975 and 572 anti-HCV seropositives, respectively. The...

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Published inPloS one Vol. 9; no. 5; p. e94760
Main Authors Lee, Mei-Hsuan, Lu, Sheng-Nan, Yuan, Yong, Yang, Hwai-I, Jen, Chin-Lan, You, San-Lin, Wang, Li-Yu, L'Italien, Gilbert, Chen, Chien-Jen
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 06.05.2014
Public Library of Science (PLoS)
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ISSN1932-6203
1932-6203
DOI10.1371/journal.pone.0094760

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Summary:The development of a risk assessment tool for long-term hepatocellular carcinoma risk would be helpful in identifying high-risk patients and providing information of clinical consultation. The model derivation and validation cohorts consisted of 975 and 572 anti-HCV seropositives, respectively. The model included age, alanine aminotransferase (ALT), the ratio of aspirate aminotransferase to ALT, serum HCV RNA levels and cirrhosis status and HCV genotype. Two risk prediction models were developed: one was for all-anti-HCV seropositives, and the other was for anti-HCV seropositives with detectable HCV RNA. The Cox's proportional hazards models were utilized to estimate regression coefficients of HCC risk predictors to derive risk scores. The cumulative HCC risks in the validation cohort were estimated by Kaplan-Meier methods. The area under receiver operating curve (AUROC) was used to evaluate the performance of the risk models. All predictors were significantly associated with HCC. The summary risk scores of two models derived from the derivation cohort had predictability of HCC risk in the validation cohort. The summary risk score of the two risk prediction models clearly divided the validation cohort into three groups (p<0.001). The AUROC for predicting 5-year HCC risk in the validation cohort was satisfactory for the two models, with 0.73 and 0.70, respectively. Scoring systems for predicting HCC risk of HCV-infected patients had good validity and discrimination capability, which may triage patients for alternative management strategies.
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Competing Interests: Drs. Yong Yuan and Gilbert L'Italien are employed by the commercial funder of the research (Bristol-Myers Squibb Co.) The authors declare no conflicts relating to their employment, consultancy, patents, products in development or marketed products, etc. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.
Conceived and designed the experiments: MHL HIY CJC. Performed the experiments: MHL YY SNL HIY CLJ SLY LYW GLI CJC. Analyzed the data: MHL. Contributed reagents/materials/analysis tools: MHL YY SNL HIY CLJ SLY LYW GLI CJC. Wrote the paper: MHL. Critically revised the manuscript for important intellectual content: MHL YY SNL HIY CLJ SLY LYW GLI CJC. Performed statistical analysis: MHL. Obtained funding: CJC. Provided administrative, technical, or material support: MHL YY SNL HIY CLJ SLY LYW GLI CJC.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0094760