Predictors for significant hepatic fibrosis in chronic HBV patients in daily clinical practice: A prospective study

Fadi Abu Baker1, Saif Abu Mouch1, Dorin Nicola1

  • 1Department of Gastroenterology and Hepatology, Hillel Yaffe Medical Center, Affiliated to the Technion Faculty of Medicine, Haifa, Israel.

Insights

Simple clinical factors like age over 50, elevated ALT, high HBV DNA, diabetes, steatosis, and heavy smoking predict significant liver fibrosis in chronic hepatitis B patients, aiding clinical practice.

Area of Science:

  • Hepatology
  • Gastroenterology
  • Internal Medicine

Background:

  • Accurate assessment of liver fibrosis is crucial for managing chronic hepatitis B (CHB).
  • Current diagnostic methods like liver biopsy and elastography have limitations including cost, invasiveness, and availability.
  • There is a need for simpler methods to identify CHB patients with significant fibrosis in routine clinical settings.

Purpose of the Study:

  • To identify simple clinical and laboratory predictors of significant liver fibrosis in patients with chronic hepatitis B.
  • To develop a tool for risk stratification in resource-limited settings.

Main Methods:

  • Prospective study involving 173 CHB patients undergoing shear wave elastography (SWE), abdominal ultrasound, and blood tests.
  • Data collected included demographics, habits, medical history, and CHB status.
  • Multivariate logistic regression analysis was used to identify independent predictors of significant fibrosis (defined by SWE).

Main Results:

  • 23.0% of patients had significant liver fibrosis.
  • Independent predictors identified were: age > 50 years (OR: 3.53), ALT > 40 U/L (OR: 8.16), HBV DNA > 2000 IU/mL (OR: 9.20), diabetes mellitus (OR: 3.58), moderate-to-severe steatosis on ultrasound (OR: 4.50), and heavy smoking.
  • These factors demonstrated significant associations with the presence of fibrosis.

Conclusions:

  • Clinical and laboratory variables can effectively identify CHB patients at high risk of significant liver fibrosis.
  • These predictors can assist in prioritizing patients for further investigation and management, optimizing resource allocation.
  • This approach supports improved patient care in daily practice, especially where advanced diagnostic tools are scarce.