OBJECTIVE: Two disease-modifying therapies are licensed in the EU for use in rapidly-evolving severe (RES) relapsing-remitting multiple sclerosis (RRMS), fingolimod and natalizumab. Here a discrete event simulation (DES) model to analyze the cost-effectiveness of natalizumab and fingolimod in the RES population, from the perspective of the National Health Service (NHS) in the UK, is reported. METHODS: A DES model was developed to track individual RES patients, based on Expanded Disability Status Scale scores. Individual patient characteristics were taken from the RES sub-groups of the pivotal trials for fingolimod. Utility data were in line with previous models. Published costs were inflated to NHS cost year 2015. Owing to the confidential patient access scheme (PAS) discount applied to fingolimod in the UK, a range of discount levels were applied to the fingolimod list price, to capture the likelihood of natalizumab being cost-effective in a real-world setting. RESULTS: At the lower National Institute of Health and Care Excellence (NICE) threshold of £20,000/quality-adjusted life year (QALY), fingolimod only required a discount greater than 0.8% of list price to be cost-effective. At the upper threshold of £30,000/QALY employed by the NICE, fingolimod was cost-effective if the confidential discount is greater than 2.5%. Sensitivity analyses conducted using fingolimod list-price showed the model to be most sensitive to changes in the cost of each drug, particularly fingolimod. CONCLUSIONS: The DES model shows that only a modest discount to the UK fingolimod list-price is required to make fingolimod a more cost-effective option than natalizumab in RES RRMS.
OBJECTIVE: Two disease-modifying therapies are licensed in the EU for use in rapidly-evolving severe (RES) relapsing-remitting multiple sclerosis (RRMS), fingolimod and natalizumab. Here a discrete event simulation (DES) model to analyze the cost-effectiveness of natalizumab and fingolimod in the RES population, from the perspective of the National Health Service (NHS) in the UK, is reported. METHODS: A DES model was developed to track individual RES patients, based on Expanded Disability Status Scale scores. Individual patient characteristics were taken from the RES sub-groups of the pivotal trials for fingolimod. Utility data were in line with previous models. Published costs were inflated to NHS cost year 2015. Owing to the confidential patient access scheme (PAS) discount applied to fingolimod in the UK, a range of discount levels were applied to the fingolimod list price, to capture the likelihood of natalizumab being cost-effective in a real-world setting. RESULTS: At the lower National Institute of Health and Care Excellence (NICE) threshold of £20,000/quality-adjusted life year (QALY), fingolimod only required a discount greater than 0.8% of list price to be cost-effective. At the upper threshold of £30,000/QALY employed by the NICE, fingolimod was cost-effective if the confidential discount is greater than 2.5%. Sensitivity analyses conducted using fingolimod list-price showed the model to be most sensitive to changes in the cost of each drug, particularly fingolimod. CONCLUSIONS: The DES model shows that only a modest discount to the UK fingolimod list-price is required to make fingolimod a more cost-effective option than natalizumab in RES RRMS.
Authors: Sameera Senanayake; Nicholas Graves; Helen Healy; Keshwar Baboolal; Adrian Barnett; Sanjeewa Kularatna Journal: Health Econ Rev Date: 2021-04-15
Authors: Timothy Spelman; William L Herring; Thibaut Dort; Yuanhui Zhang; Michael Tempest; Isobel Pearson; Ulrich Freudensprung; Carlos Acosta; Robert Hyde; Eva Havrdova; Dana Horakova; Maria Trojano; Giovanna De Luca; Alessandra Lugaresi; Guillermo Izquierdo; Pierre Grammond; Pierre Duquette; Raed Alroughani; Eugenio Pucci; Franco Granella; Jeannette Lechner-Scott; Patrizia Sola; Diana Ferraro; Francois Grand'Maison; Murat Terzi; Csilla Rozsa; Cavit Boz; Raymond Hupperts; Vincent Van Pesch; Celia Oreja-Guevara; Anneke van der Walt; Vilija G Jokubaitis; Tomas Kalincik; Helmut Butzkueven Journal: Pharmacoeconomics Date: 2021-12-18 Impact factor: 4.981