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Published on: May 10, 2022
A decision-making model for prediction of a stable disease course in chronic hepatitis B patients
Imri Ofri1,2, Noam Peleg2,3, Moshe Leshno4
1Department of Medicine D and the Laboratory of Liver Research, Rabin Medical Center, Beilinson Hospital, 39 Jabotinsky Street, Petah-Tikva, Israel.
Insights
Identifying predictors for a stable chronic hepatitis B (CHB) course can optimize patient monitoring. Older age, lower baseline HBV DNA viral load (VL), and normal ALT levels predict a stable CHB disease course, potentially reducing unnecessary tests and healthcare costs.
Area of Science:
- Hepatology
- Virology
- Clinical Medicine
Background:
- Chronic hepatitis B (CHB) requires regular monitoring of HBV DNA and liver enzymes to guide antiviral therapy.
- Identifying patients with stable disease can lead to less frequent monitoring, reduced testing, and cost savings.
Purpose of the Study:
- To identify predictors of a stable disease course in patients with CHB.
- To enable optimized monitoring strategies for CHB patients off antiviral treatment.
Main Methods:
- Retrospective analysis of 220 CHB patients followed between 2004-2018.
- Defined stable CHB as low, steady viral load (<2000 IU/ml) and normal ALT (<40 IU/ml) over 6 consecutive visits.
- Utilized stepwise multivariate logistic regression and decision tree models to identify predictors.
Main Results:
- Older age, higher percentage of women, and lower baseline AST, ALT, and viral load (VL) were associated with stable CHB.
- Multivariate analysis showed age (OR 0.94), baseline ALT (OR 1.06), and VL (OR 1.05) significantly predicted stability.
- A decision tree model identified patients aged 46-67 with baseline VL <149 IU/mL and ALT <40 IU/mL had a 91% probability of a stable course.
Conclusions:
- Integrating patient age with baseline HBV DNA viral load and ALT levels can effectively predict a stable disease course in CHB patients not on treatment.
- These findings support personalized monitoring schedules, potentially improving patient management and resource allocation.
Abstract:
Patients with chronic hepatitis B (CHB) are regularly monitored for HBV DNA and liver enzymes in order to assess disease progression and the need for antiviral therapy. Identifying patients with a stable course of disease can potentially prolong the intervals between visits, withhold unnecessary tests and save money. Accordingly, we aimed to find predictors for a stable disease course in patients with CHB. 579 patients with CHB, who were followed in a tertiary referral center between January 2004-December 2018, were retrospectively analyzed. Patients with low and steady viral load titer (< 2000 IU/ml) and normal ALT levels (< 40 IU/ml) in 6 consecutive clinic encounters were considered to have a stable course of CHB. A stepwise multivariate logistic regression analysis and a decision tree model were used to identify predictors of a stable disease course. Following exclusion of ineligible patients, a total of 220 patients were included in the final analysis. 64/220 patients had a stable disease course. Patients with a stable disease were older (62.99 ± 12.36 Vs. 54.07 ± 13.64, p < 0.001) with a higher percentage of women (53% vs. 38%) and had lower baseline levels of AST, ALT and viral load (VL). In a multivariate analysis, age (OR 0.94, 95% CI 0.91-0.98), baseline ALT (OR 1.06, 95% CI 1.01-1.1) and VL (OR 1.05 95% CI 1.02-1.08), were significantly associated with a stable disease. In a decision tree model, patients 46-67 years old, with baseline VL < 149 IU/mL and ALT < 40 IU/mL had the best probability (91%) for a stable disease course over 4.4 ± 2.2 years. We conclude that integrating patients' age with baseline VL and ALT can predict a stable disease course in patients with CHB off treatment.
