Assessment of facility performance during mass treatment of chronic hepatitis C in Egypt: Enablers and obstacles.

BACKGROUND: The national committee for control of viral hepatitis (NCCVH) in Egypt, settled by the Ministry of health, treated over one million patients in around 60 centers with chronological changes in drug combinations. This research aims to study the health care facilities and services provided by NCCVH treatment centers in Egypt and explore hinders faced. METHODS: A cross-sectional operational research study. Multistage random sampling technique was applied for Egyptian governorates. From each stratum one governorate was chosen from which one center was randomly selected. Quality of recorded data for each center in the central server (Data-oriented parameter), newly designed score to assess the overall performance of the centers was retrieved from computer based recording system. A self-administered questionnaire was completed by the centers head. RESULTS: This study included 24 treatment centers from urban, rural areas, Upper and Lower Egypt. The Upper centers showed the best completeness of follow-up records and the least compliance rates. None of the centers had 100% completeness of follow-up data. Proportion of SVR is minimally less than proportion of patient with known outcome in all treatment centers. A novel indicator standardizing the comparisons of performance of different facilities was introduced: Total number of physicians/total number of SVR patients with completed records. The highest response rate: Monfiya Governorate (Lower Egypt), Aswan (Upper Egypt), Completeness of follow-up records: Kalyoubia (Lower Egypt), Sohag governorate (Upper Egypt). The average administrative score was 64%. CONCLUSION: Challenges of NCCVH program: overcrowdings, resistant sociocultural background among rural patients, limited accessibility for internal migrants and incompleteness of data entry are system lacking points. Strengths include, clear patient pathway, well-established database online application, well-trained physicians and treatment availability.

How to optimize hepatitis C virus treatment impact on life years saved in resource-constrained countries.

UNLABELLED: In resource-constrained countries where the prevalence of hepatitis C virus (HCV) disease is usually high, it is important to know which population should be treated first in order to increase treatment effectiveness. The aim was to estimate the effectiveness of different HCV treatment eligibility scenarios in three different countries. Using a Markov model, we estimated the number of life-years saved (LYS) with different treatment eligibility scenarios according to fibrosis stage (F1-F4 or F3-4), compared to base case (F2-F4), at a constant treatment rate, of patients between 18 and 60 years of age, at stages F0/F1 to F4, without liver complications or coinfections, chronically infected by HCV, and treated with pegylated interferon (IFN)/ribavirin or more-efficacious therapies (i.e. IFN free). We conducted the analysis in Egypt (prevalence = 14.7%; 45,000 patients treated/year), Thailand (prevalence = 2.2%; 1,000 patients treated/year), and Côte d'Ivoire (prevalence = 3%; 150 patients treated/year). In Egypt, treating F1 patients in addition to ≥F2 patients (SE1 vs. SE0) decreased LYS by 3.9%. Focusing treatment only on F3-F4 patients increased LYS by 6.7% (SE2 vs. SE0). In Thailand and Côte d'Ivoire, focusing treatment only on F3-F4 patients increased LYS by 15.3% and 11.0%, respectively, compared to treating patients ≥F2 (ST0 and SC0, respectively). Treatment only for patients at stages F3-F4 with IFN-free therapies would increase LYS by 16.7% versus SE0 in Egypt, 22.0% versus ST0 in Thailand, and 13.1% versus SC0 in Côte d'Ivoire. In this study, we did not take into account the yearly new infections and the impact of treatment on HCV transmission. CONCLUSION: Our model-based analysis demonstrates that prioritizing treatment in F3-F4 patients in resource-constrained countries is the most effective scenario in terms of LYS, regardless of treatment considered.

Effectiveness and cost-effectiveness of immediate versus delayed treatment of hepatitis C virus-infected patients in a country with limited resources: the case of Egypt.

BACKGROUND: Because of logistical and economic issues, in Egypt, as in other resource-limited settings, decision makers should determine for which patients hepatitis C virus (HCV) treatment should be prioritized. We assessed the effectiveness and cost-effectiveness of different treatment initiation strategies. METHODS: Using a Markov model, we simulated HCV disease in chronically infected patients in Egypt, to compare lifetime costs, quality-adjusted life expectancy (QALE), and the incremental cost-effectiveness ratio (ICER) of different treatment initiation strategies. RESULTS: Immediate treatment of patients at stages F1/F2/F3 was less expensive and more effective than delaying treatment until more severe stages or not providing treatment (in patients diagnosed at F1: QALE = 18.32 years if treatment at F1 vs 18.22 if treatment at F2). Treatment of F4 patients was more effective than no treatment at all (QALE = 10.33 years vs 8.77 years) and was cost-effective (ICER = $1915/quality-adjusted life-year [QALY]). When considering that affordable triple therapies, including new direct-acting antivirals, will be available starting in 2016, delaying treatment until stage F2, then treating all patients regardless of their disease stage after 2016, was found to be cost-effective (ICER = $33/QALY). CONCLUSIONS: In Egypt, immediate treatment of patients with fibrosis stage F1-F3 who present to care is less expensive and more effective than delaying treatment. However, immediate treatment at stage F1 is only slightly more effective than waiting for disease to progress to stage F2 before starting treatment and is sensitive to the forthcoming availability of new treatments. Treating patients at stage F4 is highly effective and cost-effective. In Egypt, decision makers should prioritize treatment for F4 patients and delay treatment for F1 patients who present to care.

The assessment of data mining for the prediction of therapeutic outcome in 3719 Egyptian patients with chronic hepatitis C.

INTRODUCTION: Decision-tree analysis; a core component of data mining analysis can build predictive models for the therapeutic outcome to antiviral therapy in chronic hepatitis C virus (HCV) patients. AIM: To develop a prediction model for the end virological response (ETR) to pegylated interferon PEG-IFN plus ribavirin (RBV) therapy in chronic HCV patients using routine clinical, laboratory, and histopathological data. PATIENTS AND METHODS: Retrospective initial data (19 attributes) from 3719 Egyptian patients with chronic HCV presumably genotype-4 was assigned to model building using the J48 decision tree-inducing algorithm (Weka implementation of C4.5). All patients received PEG-IFN plus RBV at Cairo-Fatemia Hospital, Cairo, Egypt in the context of the national treatment program. Factors predictive of ETR were explored and patients were classified into seven subgroups according to the different rates of ETR. The universality of the decision-tree model was subjected to a 10-fold cross-internal validation in addition to external validation using an independent dataset collected of 200 chronic HCV patients. RESULTS: At week 48, overall ETR was 54% according to intention to treat protocol. The decision-tree model included AFP level (<8.08 ng/ml) which was associated with high probability of ETR (73%) followed by stages of fibrosis and Hb levels according to the patients' gender followed by the age of patients. CONCLUSION: In a decision-tree model for the prediction for antiviral therapy in chronic HCV patients, AFP level was the initial split variable at a cutoff of 8.08 ng/ml. This model could represent a potential tool to identify patients' likelihood of response among difficult-to-treat presumably genotype-4 chronic HCV patients and could support clinical decisions regarding the proper selection of patients for therapy without imposing any additional costs.