title: Modeling and simulating dynamics of complete- and poor-response chronic hepatitis B chinese patients for adefovir and traditional chinese medicine plus adefovir therapy.
abstract: ChiCTR-TRC-11001263 study was the first large-scale double-blind randomized placebo-controlled traditional Chinese medicines (TCMs) and adefovir (ADV) antihepatitis B virus (HBV) infection trial in the world. A total of 560 hepatitis B e antigen- (HBeAg-) positive Chinese patients with chronical HBV were randomly classified, in 1 : 1 ratio, into two groups: experimental group (EXG) receiving TCMs + ADV and controlled group (CTG) receiving ADV + TCM-placebo treatment for 48 weeks. This paper introduces two models to model and simulate the evolutions of dynamics for the complete-response patients and the poor-response patients in EXG and CTG, respectively. The stimulated mean HBV DNA and alanine aminotransferase (ALT) levels were close to the patients' experimental data. Analysis and simulations suggest that the activated patients' immune functions by TCMs + ADV may not only clear infected hepatocytes, but also clear HBV, which made the complete-response patients' mean serum HBV DNA levels in EXG reduce rapidly 12 weeks' earlier than the ones in CTG. One can assume that both the TCMs and ADV have the function of preventing complete-response patients' infected hepatocytes from being injured by cytotoxic T lymphocytes (CTLs); the patients' activated immune cells may also block HBV replications.
authors.affiliation: School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China ; School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China.
authors.forename: Lequan
authors.initials: L
authors.lastname: Min
authors.forename: Xiao
authors.initials: X
authors.lastname: Chen
authors.forename: Yongan
authors.initials: Y
authors.lastname: Ye
authors.forename: Qun
authors.initials: Q
authors.lastname: Zhang
authors.forename: Shuying
authors.initials: S
authors.lastname: Ru
authors.forename: Xiaoke
authors.initials: X
authors.lastname: Li