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Poster display session

397P - Development of prediction model for hepatocellular carcinoma in chronic hepatitis B patients

Date

23 Nov 2019

Session

Poster display session

Topics

Bioethical Principles and GCP

Tumour Site

Hepatobiliary Cancers

Presenters

Teerapat Ungtrakul

Citation

Annals of Oncology (2019) 30 (suppl_9): ix131-ix134. 10.1093/annonc/mdz432

Authors

T. Ungtrakul1, K. Soonklang2, J. Dechma3, P. Kusuman3, W. Pongpun3

Author affiliations

  • 1 Faculty Of Medicine And Public Health, Chulabhorn Royal Academy, 10210 - Bangkok/TH
  • 2 Data Management Unit, Chulabhorn Royal Academy, 10210 - Bangkok/TH
  • 3 Excellent Centre Of Liver Cancer, Chulabhorn Royal Academy, 10210 - Bangkok/TH

Resources

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Abstract 397P

Background

Chronic hepatitis B infection is one of the leading causes of hepatocellular carcinoma (HCC) worldwide. Despite the endorsement of semi-annual ultrasonography as HCC surveillance method by international societies in at risk population, the accurate prediction of HCC risk is important for public policy strategy in a limited-resource country. Thus, we aim to develop the scoring systems, which are individualized surveillance strategy and cost-effectiveness to assess the risk of HCC in patients with chronic hepatitis B.

Methods

This retrospective cohort study was conducted to develop a risk estimate model of HCC in chronic hepatitis B (CHB) patients. Our prediction model was derived from data obtained in 2,208 CHB patients from Chulabhorn Hospital, Thailand. (Follow-up period: 2011-2017). Forward stepwise multivariable parametric regression model was applied to obtain coefficients for each predictor. Model input included age, sex, liver cirrhosis, cigarette smoking, alcohol consumption, diabetes mellitus, body mass index, serum HBV DNA level, HBeAg status, alanine aminotransferase, aspartate aminotransferase (AST), alpha-fetoprotein and AST to platelet ratio index. Receiver operating characteristic curves were used to assess discriminatory accuracy of the model.

Results

During a median follow-up of 6.67 years, 20 cases of HCC were newly diagnosed. Age and liver cirrhosis were statistical significant independent predictors of HCC risk. In the bootstrap simulation (1000 random samplings), the corrected c-index was 0.75 (0.58-0.91). The HCC risk was calculated from the following formula: Age (<50 year = 0; 50-59 year = 1; ≥ 60 year = 2) + Cirrhosis (Yes = 4; No = 0). A 6-point risk score could predict HCC risk at 10 years, ranging from 1.95%, 18.29% and 56.96% in low- (score 0-2), medium- (score 4-5) and high-risk group (score 6).

Conclusions

A simple prediction score constructed from routine clinical and laboratory parameters are accurate in predicting HCC development in Thai patients with CHB infection. Individualized HCC surveillance strategy including surveillance interval and/or alternative surveillance test could be reasonable and cost effectiveness based on our risk scoring. Future prospective validation study is warranted.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Teerapat Ungtrakul.

Funding

Chulabhorn Royal Academy.

Disclosure

All authors have declared no conflicts of interest.

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