Research Paper Volume 12, Issue 24 pp 26063—26079
An Immuno-Clinic score model for evaluating T cell immunity and predicting early antiviral therapy effectiveness in chronic hepatitis B
- 1 Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
- 2 Guangdong Provincial Key Laboratory of Liver Disease Research, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
Received: March 24, 2020 Accepted: November 13, 2020 Published: December 26, 2020https://doi.org/10.18632/aging.202274
How to Cite
Copyright: © 2020 Gu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
We generated an Immuno-Clinic score (ICS) model to evaluate T cell immunity based on the clustering of antiviral cytokines and inhibitory molecules in 229 naïve chronic hepatitis B (CHB) patients. 126 patients receiving antiviral therapy were used to validate the model for predicting antiviral therapy effectiveness. Through receiver-operator characteristic curve analysis, the area under the curve, sensitivity, and specificity of the ICS model were 0.801 (95%CI 0.703-0.900), 0.727, and 0.722, respectively. The cut-off value was 0.442. Re-evaluation of T cell immunity in different phases of CHB showed that patients in the immune tolerant phase had the lowest percentage of ICS-high (15%), while patients in the inactive carrier phase had the highest percentage of ICS-high (92%). Patients in the immune active and gray zone phases had 17% and 56% ICS-high, respectively. Elevation of ICS as early as four weeks after treatment could predict the effectiveness of hepatitis B virus (HBV) DNA loss and normalization of alanine aminotransferase, while eight weeks after treatment could predict HBV surface antigen decline. Thus, this ICS model helps clinicians choose an optimal time for initiating antiviral therapy and predicting its efficacy.