Evaluation of factors affecting patients' refusal of HCV treatment in a cohort of Egyptian patients.

BACKGROUND: Treatment refusal, defined as active refusal of a patient to receive treatment despite physician recommendations, has not been extensively evaluated before in hepatitis C virus in the era of direct acting antivirals. OBJECTIVE: To investigate the reasons for refusal to receive hepatitis C virus treatment in Egypt. METHODS: an observational study conducted between July 2018 and November 2019 in Egypt. Enrollment was done to all patients who refused to get hepatitis C virus treatment during the national screening and treatment campaign. Reasons for their refusal were identified using a questionnaire as an instrument for data collection. RESULTS: Out of the 220 280 Egyptian hepatitis C virus patients who did not show up to start treatment and were contacted to get therapy, only 84 patients (0.038%) refused to receive treatment. The main reason for their refusal was having concerns about treatment (82.14%) and their main concern was the fear of adverse events (85.5%). Other causes of refusal were non-satisfactory experience at treatment centers (13.09%) and patients preferred to receive complementary and alternative medicines (4.7%). Most patients (65.4%) trusted the efficacy of directly acting antivirals for hepatitis C. None of the study participants was found to suffer from any psychiatric morbidity and the average score of the GHQ-12 was 10.7155. CONCLUSION: Proper health education and awareness regarding hepatitis C virus treatment safety and efficacy is needed to increase treatment acceptance rates.

Changes in Serum Interferon Gamma and Interleukin-10 in Relation to Direct-Acting Antiviral Therapy of Chronic Hepatitis C Genotype 4: A Pilot Study.

Introduction: This study analyzes the changing levels of circulating inflammatory cytokines Interferon gamma (IFN-γ) and interleukin (IL)-10 (as the main cytokines of T-helper-1 and T-helper-2 immune responses) in patients with chronic hepatitis C virus (HCV) infection undergoing therapy with direct-acting antivirals (DAAs) and to correlate them with laboratory markers. Methods: This Pilot study included 50 HCV monoinfected patients who received DAAs for 12 or 24 weeks. They were followed up monthly during therapy and 3 months after the end of the treatment. Liver disease was determined by transient elastography, in addition to FIB-4 indices. Analysis of IFN-gamma and IL-10 was carried out using an enzyme-linked immunosorbent assay. Results: All patients carried HCV genotype 4. The Sustained virological response was 100% and 92% in cirrhotics and noncirrhotics, respectively. There was no significant difference between groups in baseline IL-10 or IFN-gamma. In noncirrhotics, IL-10 showed a significant reduction at Week 4 after treatment start. In cirrhotics, IL-10 showed a significant reduction at Week 4 after treatment starts and a significant reduction at Week 12 after the end of the treatment. At Week 12 after the end of the treatment, serum IL-10 levels were significantly lower in cirrhotics. IFN-γ showed nonsignificant changes in noncirrhotics. A significant increase of IFN-γ occurred in cirrhotics from Week 4 after treatment starts to 12 weeks after the end of the treatment. IFN-γ was significantly higher in cirrhotics at Week 12 after the end of the treatment. IFN-γ and IL-10 showed different correlations with laboratory markers. Conclusion: Viral eradication induced by DAAs caused a significant change in IL-10 and IFN-gamma.

Validation of a machine learning approach using FIB-4 and APRI scores assessed by the metavir scoring system: A cohort study.

BACKGROUND AND STUDY AIM: The study aim was to improve and validate the accuracy of the fibrosis-4 (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI) scores for use in a potential machine-learning (ML) method that accurately predicts the extent of liver fibrosis. PATIENTS AND METHODS: This retrospective multicenter study included 69,106 patients with chronic hepatitis C planned for antiviral therapy from January 2010-December 2014 with liver biopsy results. FIB-4 and APRI scores were calculated and their performance for predicting significant liver fibrosis (F3-F4) assessed against the Metavir scoring system. ML was used for feature selection and reduction to identify the most relevant attributes (CfsSubseteval/best first) for prediction. RESULTS: In this study, 57,492 (83.2%) patients were F0-F2, and 11,615 (16.8%) patients were F3-F4. The revalidation of FIB-4 and APRI showed lower accuracy and higher disagreement with the biopsy results, with AUCs of 0.68 and 0.58, respectively. FIB-4 diagnosed fewer (14%) F3-F4 patients, and the high specificity and negative predictive values of FIB-4 and APRI reflected the low prevalence of F3-F4 in the study population. Out of 15 attributes, age (>35 years), AFP (>6.5 ng/ml), and platelet count (<150,000/mm3) were the most relevant risk attributes, and patients with one or more of these risk factors were likely to be F3-F4, with a classification accuracy of ≤ 92% and receiver operating characteristics area of 0.74. CONCLUSION: FIB-4 and APRI scores were not very accurate and missed diagnosing most of the F3-F4 patients. ML implementation improved medical decisions and minimized the required clinical data to three risk factors.

Data mining of routine laboratory tests can predict liver disease progression in Egyptian diabetic patients with hepatitis C virus (G4) infection: a cohort study of 71 806 patients.

OBJECTIVES: Hepatitis C virus (HCV) and diabetes mellitus (DM) are prevalent diseases worldwide, associated with significant morbidity, mortality, and mutual association. The aims of this study were as follows: (i) find the prevalence of DM among 71 806 Egyptian patients with chronic HCV infection and its effect on liver disease progression and (ii) using data mining of routine tests to predict hepatic fibrosis in diabetic patients with HCV infection. PATIENTS AND METHODS: A retrospective multicentered study included laboratory and histopathological data of 71 806 patients with HCV infection collected by Egyptian National Committee for control of viral hepatitis. Using data mining analysis, we constructed decision tree algorithm to assess predictors of fibrosis progression in diabetic patients with HCV. RESULTS: Overall, 12 018 (16.8%) patients were diagnosed as having diabetes [6428: fasting blood glucose ≥126 mg/dl (9%) and 5590: fasting blood glucose ≥110-126 mg/dl (7.8%)]. DM was significantly associated with advanced age, high BMI and α-fetoprotein (AFP), and low platelets and serum albumin (P≤0.001). Advanced liver fibrosis (F3-F4) was significantly correlated with DM (P≤0.001) irrespective of age. Of 16 attributes, decision tree model for fibrosis showed AFP was most decisive with cutoff of 5.25 ng/ml as starting point of fibrosis. AFP level greater than cutoff in patients was the first important splitting attribute; age and platelet count were second important splitting attributes. CONCLUSION: (i) Chronic HCV is significantly associated with DM (16.8%). (ii) Advanced age, high BMI and AFP, low platelets count and albumin show significant association with DM in HCV. (iii) AFP cutoff of 5.25 is a starting point of fibrosis development and integrated into mathematical model to predict development of liver fibrosis in diabetics with HCV (G4) infection.