IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0190261.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
  • Jin-Wook Kim

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

Suggested Citation

  • 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 & Jin-Wook Kim, 2018. "Liver volume-based prediction model stratifies risks for hepatocellular carcinoma in chronic hepatitis B patients on surveillance," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0190261
    DOI: 10.1371/journal.pone.0190261
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190261
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0190261&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0190261?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jung Wha Chung & Beom Hee Kim & Chung Seop Lee & Gi Hyun Kim & Hyung Rae Sohn & Bo Young Min & Joon Chang Song & Hyun Kyung Park & Eun Sun Jang & Hyuk Yoon & Jaihwan Kim & Cheol Min Shin & Young Soo P, 2016. "Optimizing Surveillance Performance of Alpha-Fetoprotein by Selection of Proper Target Population in Chronic Hepatitis B," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-13, December.
    2. Patrick J. Heagerty & Thomas Lumley & Margaret S. Pepe, 2000. "Time-Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker," Biometrics, The International Biometric Society, vol. 56(2), pages 337-344, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Claire L Heslop & Gregory E Miller & John S Hill, 2009. "Neighbourhood Socioeconomics Status Predicts Non-Cardiovascular Mortality in Cardiac Patients with Access to Universal Health Care," PLOS ONE, Public Library of Science, vol. 4(1), pages 1-8, January.
    2. Chin-Tsang Chiang & Shr-Yan Huang, 2009. "Estimation for the Optimal Combination of Markers without Modeling the Censoring Distribution," Biometrics, The International Biometric Society, vol. 65(1), pages 152-158, March.
    3. Sebastian Cremer & Lisa Pilgram & Alexander Berkowitsch & Melanie Stecher & Siegbert Rieg & Mariana Shumliakivska & Denisa Bojkova & Julian Uwe Gabriel Wagner & Galip Servet Aslan & Christoph Spinner , 2021. "Angiotensin II receptor blocker intake associates with reduced markers of inflammatory activation and decreased mortality in patients with cardiovascular comorbidities and COVID-19 disease," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-17, October.
    4. Te-Ling Ma & Tsung-Hui Hu & Chao-Hung Hung & Jing-Houng Wang & Sheng-Nan Lu & Chien-Hung Chen, 2019. "Incidence and predictors of retreatment in chronic hepatitis B patients after discontinuation of entecavir or tenofovir treatment," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-16, October.
    5. Liu Xinhua & Jin Zhezhen, 2009. "A Non-Parametric Approach to Scale Reduction for Uni-Dimensional Screening Scales," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-22, January.
    6. Yingye Zheng & Patrick Heagerty, 2004. "Semiparametric Estimation of Time-Dependent: ROC Curves for Longitudinal Marker Data," UW Biostatistics Working Paper Series 1052, Berkeley Electronic Press.
    7. Shannon M Lynch & Elizabeth Handorf & Kristen A Sorice & Elizabeth Blackman & Lisa Bealin & Veda N Giri & Elias Obeid & Camille Ragin & Mary Daly, 2020. "The effect of neighborhood social environment on prostate cancer development in black and white men at high risk for prostate cancer," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-18, August.
    8. Nir Y. Krakauer & Jesse C. Krakauer, 2021. "Association of X-ray Absorptiometry Body Composition Measurements with Basic Anthropometrics and Mortality Hazard," IJERPH, MDPI, vol. 18(15), pages 1-13, July.
    9. Weining Shen & Jing Ning & Ying Yuan, 2015. "A direct method to evaluate the time-dependent predictive accuracy for biomarkers," Biometrics, The International Biometric Society, vol. 71(2), pages 439-449, June.
    10. Matthias Schmid & Thomas Hielscher & Thomas Augustin & Olaf Gefeller, 2011. "A Robust Alternative to the Schemper–Henderson Estimator of Prediction Error," Biometrics, The International Biometric Society, vol. 67(2), pages 524-535, June.
    11. Si Cheng & Kathleen F Kerr & Heather Thiessen-Philbrook & Steven G Coca & Chirag R Parikh, 2020. "BioPETsurv: Methodology and open source software to evaluate biomarkers for prognostic enrichment of time-to-event clinical trials," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-11, September.
    12. Tim Johnson & Valen Johnson, 2004. "A Bayesian Hierarchical Approach to Multirater Correlated ROC Analysis," The University of Michigan Department of Biostatistics Working Paper Series 1027, Berkeley Electronic Press.
    13. P. Saha & P. J. Heagerty, 2010. "Time-Dependent Predictive Accuracy in the Presence of Competing Risks," Biometrics, The International Biometric Society, vol. 66(4), pages 999-1011, December.
    14. Lori E. Dodd, 2010. "ROC Curves for Continuous Data by KRZANOWSKI, W. J. and HAND, D. J," Biometrics, The International Biometric Society, vol. 66(2), pages 657-658, June.
    15. Janez Stare & Maja Pohar Perme & Robin Henderson, 2011. "A Measure of Explained Variation for Event History Data," Biometrics, The International Biometric Society, vol. 67(3), pages 750-759, September.
    16. Minta Thomas & Yu-Ru Su & Elisabeth A. Rosenthal & Lori C. Sakoda & Stephanie L. Schmit & Maria N. Timofeeva & Zhishan Chen & Ceres Fernandez-Rozadilla & Philip J. Law & Neil Murphy & Robert Carreras-, 2023. "Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    17. Yingye Zheng & Tianxi Cai & Ziding Feng, 2006. "Application of the Time-Dependent ROC Curves for Prognostic Accuracy with Multiple Biomarkers," Biometrics, The International Biometric Society, vol. 62(1), pages 279-287, March.
    18. C. Jason Liang & Patrick J. Heagerty, 2017. "Rejoinder to discussions on: A risk-based measure of time-varying prognostic discrimination for survival models," Biometrics, The International Biometric Society, vol. 73(3), pages 745-748, September.
    19. Ozcan, Erhan C. & Görgülü, Berk & Baydogan, Mustafa G., 2024. "Column generation-based prototype learning for optimizing area under the receiver operating characteristic curve," European Journal of Operational Research, Elsevier, vol. 314(1), pages 297-307.
    20. C. Jason Liang & Patrick J. Heagerty, 2017. "A risk-based measure of time-varying prognostic discrimination for survival models," Biometrics, The International Biometric Society, vol. 73(3), pages 725-734, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0190261. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.