Hamish Innes1, David Goldberg1, John Dillon2, Sharon J Hutchinson1. 1. School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK Health Protection Scotland, Glasgow, UK. 2. Ninewells hospital and Medical School, Dundee, UK.
Abstract
OBJECTIVE: The expense of new therapies for HCV infection may force health systems to prioritise the treatment of certain patient groups over others. Our objective was to forecast the population impact of possible prioritisation strategies for the resource-rich setting of Scotland. DESIGN: We created a dynamic Markov simulation model to reflect the HCV-infected population in Scotland. We determined trends in key outcomes (e.g., incident cases of chronic infection and severe liver morbidity (SLM)) until the year 2030, according to treatment strategies involving prioritising, either: (A) persons with moderate/advanced fibrosis or (B) persons who inject drugs (PWID). RESULTS: Continuing to treat the same number of patients with the same characteristics will give rise to a fall in incident infection (from 600 cases in 2015 to 440 in 2030) and a fall in SLM (from 195 cases in 2015 to 145 in 2030). Doubling treatment-uptake and prioritising PWID will reduce incident infection to negligible levels (<50 cases per year) by 2025, while SLM will stabilise (at 70-75 cases per year) in 2028. Alternatively, doubling the number of patients treated, but, instead, prioritising persons with moderate/advanced fibrosis will reduce incident infection less favourably (only to 280 cases in 2030), but SLM will stabilise by 2023 (i.e., earlier than any competing strategy). CONCLUSIONS: Prioritising treatment uptake among PWID will substantially impact incident transmission, however, this approach foregoes the optimal impact on SLM. Conversely, targeting those with moderate/advanced fibrosis has the greatest impact on SLM but is suboptimal in terms of averting incident infection. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
OBJECTIVE: The expense of new therapies for HCV infection may force health systems to prioritise the treatment of certain patient groups over others. Our objective was to forecast the population impact of possible prioritisation strategies for the resource-rich setting of Scotland. DESIGN: We created a dynamic Markov simulation model to reflect the HCV-infected population in Scotland. We determined trends in key outcomes (e.g., incident cases of chronic infection and severe liver morbidity (SLM)) until the year 2030, according to treatment strategies involving prioritising, either: (A) persons with moderate/advanced fibrosis or (B) persons who inject drugs (PWID). RESULTS: Continuing to treat the same number of patients with the same characteristics will give rise to a fall in incident infection (from 600 cases in 2015 to 440 in 2030) and a fall in SLM (from 195 cases in 2015 to 145 in 2030). Doubling treatment-uptake and prioritising PWID will reduce incident infection to negligible levels (<50 cases per year) by 2025, while SLM will stabilise (at 70-75 cases per year) in 2028. Alternatively, doubling the number of patients treated, but, instead, prioritising persons with moderate/advanced fibrosis will reduce incident infection less favourably (only to 280 cases in 2030), but SLM will stabilise by 2023 (i.e., earlier than any competing strategy). CONCLUSIONS: Prioritising treatment uptake among PWID will substantially impact incident transmission, however, this approach foregoes the optimal impact on SLM. Conversely, targeting those with moderate/advanced fibrosis has the greatest impact on SLM but is suboptimal in terms of averting incident infection. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Authors: Hannah Fraser; Natasha K Martin; Henrikki Brummer-Korvenkontio; Patrizia Carrieri; Olav Dalgard; John Dillon; David Goldberg; Sharon Hutchinson; Marie Jauffret-Roustide; Martin Kåberg; Amy A Matser; Mojca Matičič; Havard Midgard; Viktor Mravcik; Anne Øvrehus; Maria Prins; Jens Reimer; Geert Robaeys; Bernd Schulte; Daniela K van Santen; Ruth Zimmermann; Peter Vickerman; Matthew Hickman Journal: J Hepatol Date: 2018-01-08 Impact factor: 25.083
Authors: Natasha K Martin; Peter Vickerman; Iain F Brew; Joan Williamson; Alec Miners; William L Irving; Sushma Saksena; Sharon J Hutchinson; Sema Mandal; Eamonn O'Moore; Matthew Hickman Journal: Hepatology Date: 2016-03-22 Impact factor: 17.425
Authors: Lauren E Cipriano; Shan Liu; Kaspar S Shahzada; Mark Holodniy; Jeremy D Goldhaber-Fiebert Journal: Med Decis Making Date: 2018-08-22 Impact factor: 2.583