{'fraction_non_alphanumeric': 0.02836411609498681, 'fraction_numerical': 0.02308707124010554, 'mean_word_length': 4.66044776119403, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Reply to Guedj et al.: Early transient increase of hepatitis C virus viral load in genotype 1 and 2 infections, and the use of mathematical modeling

We appreciate the comments of Guedj et al. (1) on our paper addressing the association of IL28B gene variations with mathematical modeling of viral kinetics in patients with chronic hepatitis C treated with pegylated IFN plus ribavirin therapy (2). Regarding the distribution of the blips among hepatitis C virus (HCV) genotypes, we not only found a lower virion production rate but earlier blips among patients with HCV genotype 2 infection than those with genotype 1 infection. The time for the observed maximal viral load and the estimated time for maximal viral load were significantly different between these two genotypes (genotype 1 vs. 2: 0.33 ± 0.35 vs. 0.19 ± 0.12; P = 0.0048 and P = 0.0106 for the t test and Wilcoxon test), and the time for the maximal value also showed that patients with HCV genotype 1 infection had a poorer virological response than those with genotype 2 infection (Table 1). However, as reported in our paper, although HCV genotype has long been known as a predictor of achieving sustained virological response (SVR) in patients treated with combination therapy, it also serves as a latent factor of viral kinetics, especially for virion production rate. Thus, the impact of HCV genotype on SVR was not significant in our regression models, and viral kinetic parameters were still better than HCV genotype in the prediction of SVR.