Unknown

Dataset Information

0

Models estimating risk of hepatocellular carcinoma in patients with alcohol or NAFLD-related cirrhosis for risk stratification.


ABSTRACT: BACKGROUND & AIMS:Hepatocellular carcinoma (HCC) risk varies dramatically in patients with cirrhosis according to well-described, readily available predictors. We aimed to develop simple models estimating HCC risk in patients with alcohol-related liver disease (ALD)-cirrhosis or non-alcoholic fatty liver disease (NAFLD)-cirrhosis and calculate the net benefit that would be derived by implementing HCC surveillance strategies based on HCC risk as predicted by our models. METHODS:We identified 7,068 patients with NAFLD-cirrhosis and 16,175 with ALD-cirrhosis who received care in the Veterans Affairs (VA) healthcare system in 2012. We retrospectively followed them for the development of incident HCC until January 2018. We used Cox proportional hazards regression to develop and internally validate models predicting HCC risk using baseline characteristics at entry into the cohort in 2012. We plotted decision curves of net benefit against HCC screening thresholds. RESULTS:We identified 1,278 incident cases of HCC during a mean follow-up period of 3.7?years. Mean annualized HCC incidence was 1.56% in NAFLD-cirrhosis and 1.44% in ALD-cirrhosis. The final models estimating HCC were developed separately for NAFLD-cirrhosis and ALD-cirrhosis and included 7 predictors: age, gender, diabetes, body mass index, platelet count, serum albumin and aspartate aminotransferase to ?alanine aminotransferase ratio. The models exhibited very good measures of discrimination and calibration and an area under the receiver operating characteristic curve of 0.75 for NAFLD-cirrhosis and 0.76 for ALD-cirrhosis. Decision curves showed higher standardized net benefit of risk-based screening using our prediction models compared to the screen-all approach. CONCLUSIONS:We developed simple models estimating HCC risk in patients with NAFLD-cirrhosis or ALD-cirrhosis, which are available as web-based tools (www.hccrisk.com). Risk stratification can be used to inform risk-based HCC surveillance strategies in individual patients or healthcare systems or to identify high-risk patients for clinical trials. LAY SUMMARY:Patients with cirrhosis of the liver are at risk of getting hepatocellular carcinoma (HCC or liver cancer) and therefore it is recommended that they undergo surveillance for HCC. However, the risk of HCC varies dramatically in patients with cirrhosis, which has implications on if and how patients get surveillance, how providers counsel patients about the need for surveillance, and how healthcare systems approach and prioritize surveillance. We used readily available predictors to develop models estimating HCC risk in patients with cirrhosis, which are available as web-based tools at www.hccrisk.com.

SUBMITTER: Ioannou GN 

PROVIDER: S-EPMC6702126 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

Models estimating risk of hepatocellular carcinoma in patients with alcohol or NAFLD-related cirrhosis for risk stratification.

Ioannou George N GN   Green Pamela P   Kerr Kathleen F KF   Berry Kristin K  

Journal of hepatology 20190528 3


<h4>Background & aims</h4>Hepatocellular carcinoma (HCC) risk varies dramatically in patients with cirrhosis according to well-described, readily available predictors. We aimed to develop simple models estimating HCC risk in patients with alcohol-related liver disease (ALD)-cirrhosis or non-alcoholic fatty liver disease (NAFLD)-cirrhosis and calculate the net benefit that would be derived by implementing HCC surveillance strategies based on HCC risk as predicted by our models.<h4>Methods</h4>We  ...[more]

Similar Datasets

| S-EPMC6641542 | biostudies-literature
| S-EPMC10069645 | biostudies-literature
| S-EPMC8138213 | biostudies-literature
| S-EPMC9970023 | biostudies-literature
| S-EPMC10661677 | biostudies-literature
| S-EPMC8236897 | biostudies-literature
| S-EPMC9818663 | biostudies-literature
| S-EPMC8318072 | biostudies-literature
| S-EPMC6201746 | biostudies-literature
| S-EPMC6882638 | biostudies-literature