Literature DB >> 25418332

Development of risk scoring system for stratifying population for hepatocellular carcinoma screening.

Yi-Chun Hung1, Chih-Lin Lin2, Chun-Jen Liu3, Hung Hung1, Shi-Ming Lin4, Shou-Dong Lee5,6, Pei-Jer Chen3, Shu-Chun Chuang7, Ming-Whei Yu1.   

Abstract

UNLABELLED: The age and risk level that warrants hepatocellular carcinoma (HCC) screening remains to be defined. To develop risk scores for stratifying average-risk population for mass HCC screening, we conducted a pooled analysis using data from three cohorts involving 12,377 Taiwanese adults 20-80 years of age. During 191,240.3 person-years of follow-up, 387 HCCs occurred. We derived risk scores from Cox's model in two thirds of participants and used another one third for model validation. Besides assessing discrimination and calibration, we performed decision curve analysis to translate findings into public health policy. A risk score according to age, sex, alanine aminotransferase, previous chronic liver disease, family history of HCC, and cumulative smoking had good discriminatory accuracy in both model derivation and validation sets (c-statistics for 3-, 5-, and 10-year risk prediction: 0.76-0.83). It also performed well across cohorts and diverse subgroups. Decision curve analyses revealed that use of the score in selecting persons for screening improved benefit at threshold probabilities of >2% 10-year risk, compared with current guidelines and a strategy of screening all hepatitis B carriers. Using 10-year risk 2% as a threshold for initiating screening, the screening age ranged from 20 to ≥60 years, depending on the tertile of risk scores and status of hepatitis B/C virus infection. Combining risk-score tertile levels and hepatitis virus status to stratify participants was more sensitive than current guidelines for HCC detection within 10 years (89.4% vs. 76.8%), especially for young-onset HCCs <50 years (79.4% vs. 40.6%), under slightly lower specificity (67.8% vs. 71.8%).
CONCLUSION: A simple HCC prediction algorithm was developed using accessible variables combined with hepatitis virus status, which allows selection of asymptomatic persons for priority of HCC screening.
© 2015 by the American Association for the Study of Liver Diseases.

Entities:  

Mesh:

Year:  2015        PMID: 25418332     DOI: 10.1002/hep.27610

Source DB:  PubMed          Journal:  Hepatology        ISSN: 0270-9139            Impact factor:   17.425


  12 in total

Review 1.  Liver cancer screening in high-risk populations.

Authors:  Morris Sherman
Journal:  Hepat Oncol       Date:  2015-11-30

2.  Plasma DNA methylation marker and hepatocellular carcinoma risk prediction model for the general population.

Authors:  Hui-Chen Wu; Hwai-I Yang; Qiao Wang; Chien-Jen Chen; Regina M Santella
Journal:  Carcinogenesis       Date:  2017-10-01       Impact factor: 4.944

3.  A Point System to Forecast Hepatocellular Carcinoma Risk Before and After Treatment Among Persons with Chronic Hepatitis C.

Authors:  Jian Xing; Philip R Spradling; Anne C Moorman; Scott D Holmberg; Eyasu H Teshale; Loralee B Rupp; Stuart C Gordon; Mei Lu; Joseph A Boscarino; Mark A Schmidt; Connie M Trinacty; Fujie Xu
Journal:  Dig Dis Sci       Date:  2017-09-30       Impact factor: 3.199

4.  Tailored algorithms for hepatocellular carcinoma surveillance: Is one-size-fits-all strategy outdated?

Authors:  Nicolas Goossens; C Billie Bian; Yujin Hoshida
Journal:  Curr Hepatol Rep       Date:  2017-02-01

Review 5.  Prediction models of hepatocellular carcinoma development in chronic hepatitis B patients.

Authors:  Hye Won Lee; Sang Hoon Ahn
Journal:  World J Gastroenterol       Date:  2016-10-07       Impact factor: 5.742

Review 6.  Screening for hepatocellular carcinoma: patient selection and perspectives.

Authors:  Waleed Fateen; Stephen D Ryder
Journal:  J Hepatocell Carcinoma       Date:  2017-05-17

7.  A novel risk score system for assessment of ovarian cancer based on co-expression network analysis and expression level of five lncRNAs.

Authors:  Qian Zhao; Conghong Fan
Journal:  BMC Med Genet       Date:  2019-06-10       Impact factor: 2.103

8.  Circulating Osteopontin and Prediction of Hepatocellular Carcinoma Development in a Large European Population.

Authors:  Talita Duarte-Salles; Sandeep Misra; Magdalena Stepien; Amelie Plymoth; David Muller; Kim Overvad; Anja Olsen; Anne Tjønneland; Laura Baglietto; Gianluca Severi; Marie-Christine Boutron-Ruault; Renee Turzanski-Fortner; Rudolf Kaaks; Heiner Boeing; Krasimira Aleksandrova; Antonia Trichopoulou; Pagona Lagiou; Christina Bamia; Valeria Pala; Domenico Palli; Amalia Mattiello; Rosario Tumino; Alessio Naccarati; H B As Bueno-de-Mesquita; Petra H Peeters; Elisabete Weiderpass; J Ramón Quirós; Antonio Agudo; Emilio Sánchez-Cantalejo; Eva Ardanaz; Diana Gavrila; Miren Dorronsoro; Mårten Werner; Oskar Hemmingsson; Bodil Ohlsson; Klas Sjöberg; Nicholas J Wareham; Kay-Tee Khaw; Kathryn E Bradbury; Marc J Gunter; Amanda J Cross; Elio Riboli; Mazda Jenab; Pierre Hainaut; Laura Beretta
Journal:  Cancer Prev Res (Phila)       Date:  2016-06-23

Review 9.  Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine.

Authors:  Naoto Fujiwara; Scott L Friedman; Nicolas Goossens; Yujin Hoshida
Journal:  J Hepatol       Date:  2017-10-06       Impact factor: 30.083

10.  Risk prediction models for hepatocellular carcinoma in different populations.

Authors:  Xiao Ma; Yang Yang; Hong Tu; Jing Gao; Yu-Ting Tan; Jia-Li Zheng; Freddie Bray; Yong-Bing Xiang
Journal:  Chin J Cancer Res       Date:  2016-04       Impact factor: 5.087

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.