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Published on: September 30, 2021
CLINICAL AND GENETIC PREDICTORS AND PROGNOSTIC MODEL OF RAPIDLY PROGRESSIVE HEPATIC FIBROSIS IN CHRONIC HEPATITIS C
G Dubinskaya1, L Sizova1, T Koval1
1Higher State Educational Establishment of Ukraine "Ukrainian Medical Stomatological Academy", Poltava, Ukraine.
Insights
Identifying risk factors for rapid hepatic fibrosis (HF) progression in chronic hepatitis C (CHC) is crucial. A new prognostic model incorporating clinical and genetic factors accurately predicts rapid HF in CHC patients.
Area of Science:
- Hepatology
- Medical Genetics
- Clinical Epidemiology
Background:
- Chronic hepatitis C (CHC) poses a significant risk for progressive hepatic fibrosis (HF).
- Identifying patients with rapidly progressing HF is essential for timely intervention and personalized treatment strategies.
- Current understanding of predictors for rapid HF progression in CHC requires further refinement.
Purpose of the Study:
- To identify clinical and genetic predictors of rapid hepatic fibrosis progression in patients with chronic hepatitis C.
- To develop and validate a prognostic model for predicting rapid HF progression in CHC.
Main Methods:
- Retrospective cohort study involving 125 patients diagnosed with CHC.
- Analysis of 46 potential clinical and genetic predictors.
- Statistical methods included logistic regression and Receiver Operating Characteristic (ROC) analysis.
Main Results:
- Significant predictors identified include male gender, elevated liver enzymes (ALT, AST, GGTP, alkaline phosphatase), total bilirubin, alcohol intake (>40 g/day), Gln11Gln genotype of the TLR7 gene, and presence of chronic cholecystitis and/or pancreatitis.
- A prognostic model incorporating GGTP, male gender, TLR7 genotype, chronic cholecystitis/pancreatitis, total bilirubin, and AST demonstrated high predictive accuracy (AUC ROC-curve = 0.840).
- The model achieved a sensitivity of 85.5% and specificity of 68.3% for predicting rapid HF progression.
Conclusions:
- The developed prognostic model effectively predicts rapid hepatic fibrosis progression in CHC patients.
- This model can aid in identifying high-risk individuals who may benefit from tailored antiviral therapy approaches.
- Clinical and genetic factors play a significant role in the rate of fibrosis progression in CHC.
Abstract:
The search for risk factors for rapid progression of hepatic fibrosis (HF) in chronic hepatitis C (CHC) is a topical scientific and practical task. The purpose of the study is to identify clinical and genetic predictors and create the prognostic model of rapidly progressive HF in CHC. A retrospective cohort study of 125 patients with CHC has been carried out. The logistic regression and ROC-analysis have been applied for statistical data processing. The resulting analysis of 46 potential predictors of rapidly progressive HF in CHC identified the following significant ctiteria: male gender - ОR=3.44 [95% СΙ 1.60-7.39], р=0.001; increased levels of alanine aminotransferase (ALT) - ОR=4.93 [95% СΙ 1.54-15.76], р=0.007, particularly, moderate cytolytic activity - ОR=2.36 [95% СΙ 1.08-5.16], р=0.031; aspartate aminotransferase (АSТ) - ОR=3.65 [95% СΙ 1.41-9.43] р=0.007; γ-glutamiltranspeptidase (GGTP) - ОR=3.63 [95% СΙ 1.73-7.61], р=0.001; total bilirubin - ОR=3.53 [95% СΙ 1.47-8.47], р=0.005; alkaline phosphatase - ОR=9.18 [95% 1.11-75.80], р=0.039; alcohol intake>40 g/day (ОR=3.53 [95% СΙ 1.36-9.17], р=0.009), Gln11Gln genotype of the TLR7 gene (ОR=4.56 [95% СΙ 1.57-13.22], р=0.005), presence of chronic cholecystitis and/or pancreatitis (ОR=5.30 [95% СΙ 1.84-15.25], р=0.002). The prognostic model, comprising 6 predictors (level of GGTP>upper limit of normal (ULN), male gender, Gln11Gln genotype of the TLR7 gene chronic cholecystitis and/or pancreatitis, levels of total bilirubin and АSТ>ULN) have been created, demonstrating the statistical significance (p=0.000) and high operational characteristics (sensitivity - 85.5%, specificity - 68.3%, total number of the appropriate assignments - 76.8%, positive and negative predictive value - 72,6% and 82.7%,, respectively, the AUC ROC-curve - 0.840). Use of the created model will help to predict the rapid progression of HF in CHC and form the risk-group, requiring individual approaches to prescribing antiviral therapy for CHC.
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