Objectives Sustained hepatitis B surface antigen (HBsAg) loss or 'functional cure' (FC) is considered an optimal treatment endpoint by international clinical guidelines for chronic hepatitis B (CHB), yet rarely is this achieved with current standard of care (SoC). This leads to an under-reporting of FC in clinical trials, observational studies and health economic (HE) models. This paper systematically identifies and assesses how FC is incorporated in published HE models of CHB. Methods A systematic literature review was conducted in PubMed and Embase (conducted February 2019) to review how HBsAg loss is captured in HE models. The following items were extracted: rate of (and transition probabilities to) HBsAg loss, HBsAg loss health state costs, and HBsAg loss health state utilities. Results Sixty-five economics evaluations were identified, and < 50% of these (27/65) incorporated HBsAg loss in their models. Only 15/27 stated HBsAg loss health state costs, 15/27 stated HBsAg loss health state utilities, and 11/27 mentioned treatment-specific transition probabilities to HBsAg loss. The majority of sources these inputs were derived from are not transparent. Conclusions The benefits of FC in current HE models are not well captured, as FC is often not reported or not directly related to modelled treatments. This has the potential for novel agents with higher efficacy compared with SoC to be overlooked and undervalued if their worth is not appropriately communicated. In order to ensure optimal access for patients to new and effective therapies, it is important that the benefits of FC are better assessed and captured within HE models.Peter Wigfield and Urbano Sbarigia contributed equally to the work.The benefits of functional cure in current health economic models are not well captured, as functional cure is often not reported or not directly related to modelled treatments.In order to ensure optimal access for patients to new and effective therapies, it is important that the benefits of functional cure are better assessed and captured within health economic models.

Objective: Published network meta-analyses of chronic hepatitis B (CHB) treatments are either out-of-date or excluded key treatments. Therefore, we aimed to comprehensively update the efficacy evidence for the following end points: Hepatitis B surface antigen (HBsAg) loss, hepatitis B early antigen (HBeAg) seroconversion and hepatitis B virus DNA (HBV DNA) suppression. Materials & methods: Approved treatments in CHB and their combinations were evaluated. A systematic literature review was conducted to identify all randomized controlled trials in treatment-naïve CHB patients. Included studies reported at least one of the end points of interest. A frequentist probability network meta-analysis was performed for each end point. The choice of fixed effect or random-effect model was based on the I-square statistic, a measure of variation in study outcomes between studies. The analyses were performed separately for HBeAg-positive and HBeAg-negative patients. For the primary analyses, end points measured 48 ± 4 weeks after treatment initiation were considered. Results: A total of 47 randomized controlled trials (13,826 patients), covering 23 unique treatment regimens, were included: a total of 29 reported HBsAg loss, 36 reported HBeAg seroconversion and 37 reported HBV DNA suppression. For both HBsAg loss and HBeAg seroconversion, pegylated interferon-based regimens were the most effective strategy in both HBeAg-positive and HBeAg-negative patients. On the other hand, for HBV DNA suppression, nucleosides-based regimens were the most effective strategy in both HBeAg-positive and HBeAg-negative patients. Conclusion: Our findings confirm available evidence around the comparative efficacy of available CHB treatments. Therefore, they can be used to update relevant cost–effectiveness analyses and clinical guidelines.

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Objectives: Nucleoside/Nucleotide analogues (NAs) are used for the treatment of chronic hepatitis B virus infection (CHB), but the treatment may fail due to several factors, including viral resistance. Resistance pattern in Egyptian patients is still S168 VALUE IN HEALTH -MAY 2020