Literature DB >> 28965221

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

Jian Xing1, Philip R Spradling2, Anne C Moorman1, Scott D Holmberg1, Eyasu H Teshale1, Loralee B Rupp3, Stuart C Gordon3, Mei Lu3, Joseph A Boscarino4, Mark A Schmidt5, Connie M Trinacty6, Fujie Xu1.   

Abstract

BACKGROUND: Risk of hepatocellular carcinoma (HCC) may be difficult to determine in the clinical setting. AIM: Develop a scoring system to forecast HCC risk among patients with chronic hepatitis C.
METHODS: Using data from the Chronic Hepatitis Cohort Study collected during 2005-2014, we derived HCC risk scores for males and females using an extended Cox model with aspartate aminotransferase-to-platelet ratio index (APRI) as a time-dependent variables and mean Kaplan-Meier survival functions from patient data at two study sites, and used data collected at two separate sites for external validation. For model calibration, we used the Greenwood-Nam-D'Agostino goodness-of-fit statistic to examine differences between predicted and observed risk.
RESULTS: Of 12,469 patients (1628 with a history of sustained viral response [SVR]), 504 developed HCC; median follow-up was 6 years. Final predictors in the model included age, alcohol abuse, interferon-based treatment response, and APRI. Point values, ranging from -3 to 14 (males) and -3 to 12 (females), were established using hazard ratios of the predictors aligned with 1-, 3-, and 5-year Kaplan-Meier survival probabilities of HCC. Discriminatory capacity was high (c-index 0.82 males and 0.84 females) and external calibration demonstrated no differences between predicted and observed HCC risk for 1-, 3-, and 5-year forecasts among males (all p values >0.97) and for 3- and 5-year risk among females (all p values >0.87).
CONCLUSION: This scoring system, based on age, alcohol abuse history, treatment response, and APRI, can be used to forecast up to a 5-year risk of HCC among hepatitis C patients before and after SVR.

Entities:  

Keywords:  Hepatitis C; Hepatocellular carcinoma; Prediction; Risk; Score

Mesh:

Substances:

Year:  2017        PMID: 28965221     DOI: 10.1007/s10620-017-4762-0

Source DB:  PubMed          Journal:  Dig Dis Sci        ISSN: 0163-2116            Impact factor:   3.199


  33 in total

Review 1.  Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.

Authors:  F E Harrell; K L Lee; D B Mark
Journal:  Stat Med       Date:  1996-02-28       Impact factor: 2.373

2.  A method for checking regression models in survival analysis based on the risk score.

Authors:  J K Grønnesby; O Borgan
Journal:  Lifetime Data Anal       Date:  1996       Impact factor: 1.588

Review 3.  Validation of probabilistic predictions.

Authors:  M E Miller; C D Langefeld; W M Tierney; S L Hui; C J McDonald
Journal:  Med Decis Making       Date:  1993 Jan-Mar       Impact factor: 2.583

4.  Impact of aging on the development of hepatocellular carcinoma in patients with posttransfusion chronic hepatitis C.

Authors:  Hisayuki Hamada; Hiroshi Yatsuhashi; Koji Yano; Manabu Daikoku; Kokichi Arisawa; Osami Inoue; Michiaki Koga; Keisuke Nakata; Katsumi Eguchi; Michitami Yano
Journal:  Cancer       Date:  2002-07-15       Impact factor: 6.860

5.  Hepatocellular carcinoma risk prediction model for the general population: the predictive power of transaminases.

Authors:  Chi-Pang Wen; Jie Lin; Yi Chen Yang; Min Kuang Tsai; Chwen Keng Tsao; Carol Etzel; Maosheng Huang; Chung Yi Hsu; Yuanqing Ye; Lopa Mishra; Ernest Hawk; Xifeng Wu
Journal:  J Natl Cancer Inst       Date:  2012-10-17       Impact factor: 13.506

6.  Noninvasive serum fibrosis markers for screening and staging chronic hepatitis C virus patients in a large US cohort.

Authors:  Scott D Holmberg; Mei Lu; Loralee B Rupp; Lois E Lamerato; Anne C Moorman; Vinutha Vijayadeva; Joseph A Boscarino; Emily M Henkle; Stuart C Gordon
Journal:  Clin Infect Dis       Date:  2013-04-16       Impact factor: 9.079

7.  Impact of aging on the development of hepatocellular carcinoma in patients with hepatitis C virus infection in Japan.

Authors:  W Ohishi; M Kitamoto; H Aikata; K Kamada; Y Kawakami; H Ishihara; M Kamiyasu; T Nakanishi; S Tazuma; K Chayama
Journal:  Scand J Gastroenterol       Date:  2003-08       Impact factor: 2.423

8.  Clinicopathological features, background liver disease, and survival analysis of HCV-positive patients with hepatocellular carcinoma: differences between young and elderly patients.

Authors:  Hiromi Saneto; Masahiro Kobayashi; Yusuke Kawamura; Hiromi Yatsuji; Hitomi Sezaki; Tetsuya Hosaka; Norio Akuta; Fumitaka Suzuki; Yoshiyuki Suzuki; Yasuji Arase; Kenji Ikeda; Hiromitsu Kumada
Journal:  J Gastroenterol       Date:  2008-12-24       Impact factor: 7.527

9.  Hepatitis C treatment failure is associated with increased risk of hepatocellular carcinoma.

Authors:  Mei Lu; Jia Li; Loralee B Rupp; Scott D Holmberg; Anne C Moorman; Philip R Spradling; Eyasu H Teshale; Yueren Zhou; Joseph A Boscarino; Mark A Schmidt; Lois E Lamerato; Connie Trinacty; Sheri Trudeau; Stuart C Gordon
Journal:  J Viral Hepat       Date:  2016-03-30       Impact factor: 3.728

10.  Management of hepatocellular carcinoma: an update.

Authors:  Jordi Bruix; Morris Sherman
Journal:  Hepatology       Date:  2011-03       Impact factor: 17.425

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  1 in total

Review 1.  Long-Term Liver Disease, Treatment, and Mortality Outcomes Among 17,000 Persons Diagnosed with Chronic Hepatitis C Virus Infection: Current Chronic Hepatitis Cohort Study Status and Review of Findings.

Authors:  Anne C Moorman; Loralee B Rupp; Stuart C Gordon; Yuna Zhong; Jian Xing; Mei Lu; Joseph A Boscarino; Mark A Schmidt; Yihe G Daida; Eyasu H Teshale; Philip R Spradling; Scott D Holmberg
Journal:  Infect Dis Clin North Am       Date:  2018-06       Impact factor: 5.982

  1 in total

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