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. 2022 Mar;40(3):323-339.
doi: 10.1007/s40273-021-01106-6. Epub 2021 Dec 18.

Comparative Effectiveness and Cost-Effectiveness of Natalizumab and Fingolimod in Patients with Inadequate Response to Disease-Modifying Therapies in Relapsing-Remitting Multiple Sclerosis in the United Kingdom

Timothy Spelman #  1 , William L Herring #  2 , Yuanhui Zhang  2 , Michael Tempest  3 , Isobel Pearson  4 , Ulrich Freudensprung  5 , Carlos Acosta  6 , Thibaut Dort #  7 , Robert Hyde  5 , Eva Havrdova  8 , Dana Horakova  8 , Maria Trojano  9 , Giovanna De Luca  10 , Alessandra Lugaresi  11   12 , Guillermo Izquierdo  13 , Pierre Grammond  14 , Pierre Duquette  15 , Raed Alroughani  16 , Eugenio Pucci  17 , Franco Granella  18 , Jeannette Lechner-Scott  19 , Patrizia Sola  20 , Diana Ferraro  21 , Francois Grand'Maison  22 , Murat Terzi  23 , Csilla Rozsa  24 , Cavit Boz  25 , Raymond Hupperts  26 , Vincent Van Pesch  27 , Celia Oreja-Guevara  28 , Anneke van der Walt  1 , Vilija G Jokubaitis  1 , Tomas Kalincik  29   30 , Helmut Butzkueven  1 ; MSBase Investigators
Collaborators, Affiliations

Comparative Effectiveness and Cost-Effectiveness of Natalizumab and Fingolimod in Patients with Inadequate Response to Disease-Modifying Therapies in Relapsing-Remitting Multiple Sclerosis in the United Kingdom

Timothy Spelman et al. Pharmacoeconomics. 2022 Mar.

Abstract

Background: Patients with highly active relapsing-remitting multiple sclerosis inadequately responding to first-line therapies (interferon-based therapies, glatiramer acetate, dimethyl fumarate, and teriflunomide, known collectively as "BRACETD") often switch to natalizumab or fingolimod.

Objective: The aim was to estimate the comparative effectiveness of switching to natalizumab or fingolimod or within BRACETD using real-world data and to evaluate the cost-effectiveness of switching to natalizumab versus fingolimod using a United Kingdom (UK) third-party payer perspective.

Methods: Real-world data were obtained from MSBase for patients relapsing on BRACETD in the year before switching to natalizumab or fingolimod or within BRACETD. Three-way-multinomial-propensity-score-matched cohorts were identified, and comparisons between treatment groups were conducted for annualised relapse rate (ARR) and 6-month-confirmed disability worsening (CDW6M) and improvement (CDI6M). Results were applied in a cost-effectiveness model over a lifetime horizon using a published Markov structure with health states based on the Expanded Disability Status Scale. Other model parameters were obtained from the UK MS Survey 2015, published literature, and publicly available UK sources.

Results: The MSBase analysis found a significant reduction in ARR (rate ratio [RR] = 0.64; 95% confidence interval [CI] 0.57-0.72; p < 0.001) and an increase in CDI6M (hazard ratio [HR] = 1.67; 95% CI 1.30-2.15; p < 0.001) for switching to natalizumab compared with BRACETD. For switching to fingolimod, the reduction in ARR (RR = 0.91; 95% CI 0.81-1.03; p = 0.133) and increase in CDI6M (HR = 1.30; 95% CI 0.99-1.72; p = 0.058) compared with BRACETD were not significant. Switching to natalizumab was associated with a significant reduction in ARR (RR = 0.70; 95% CI 0.62-0.79; p < 0.001) and an increase in CDI6M (HR = 1.28; 95% CI 1.01-1.62; p = 0.040) compared to switching to fingolimod. No evidence of difference in CDW6M was found between treatment groups. Natalizumab dominated (higher quality-adjusted life-years [QALYs] and lower costs) fingolimod in the base-case cost-effectiveness analysis (0.453 higher QALYs and £20,843 lower costs per patient). Results were consistent across sensitivity analyses.

Conclusions: This novel real-world analysis suggests a clinical benefit for therapy escalation to natalizumab versus fingolimod based on comparative effectiveness results, translating to higher QALYs and lower costs for UK patients inadequately responding to BRACETD.

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Conflict of interest statement

Timothy Spelman is a statistical contractor for the MSBase Foundation and has received compensation for serving on advisory boards for Biogen and speaker honoraria from Novartis and Roche. William L. Herring, Yuanhui Zhang, and Isobel Pearson are employees of RTI Health Solutions, an independent non-profit research organisation, which received funding pursuant to a contract with Biogen. Michael Tempest, Ulrich Freudensprung, Carlos Acosta, and Robert Hyde are employees of Biogen and hold shares or stocks from Biogen as part of their remuneration. Thibaut Dort was an employee and shareholder of Biogen at the time of his passing. Eva Havrdova has received honoraria and research support from Biogen, Merck Serono, Novartis, Roche, and Teva; has served in advisory boards for Actelion, Biogen, Celgene, Merck Serono, Novartis, and Sanofi Genzyme; and has been supported by the Czech Ministry of Education research project PROGRES Q27/LF1. Dana Horakova has received speaker honoraria and consulting fees from Biogen, Merck, Novartis, Roche, Sanofi Genzyme, and Teva and has received support for research activities from Biogen and the Czech Ministry of Education (project Progres Q27/LF1). Maria Trojano has served on scientific advisory boards for Biogen, Novartis, Roche, and Merck; has received speaker honoraria from Biogen, Sanofi, Merck, Roche, Teva, and Novartis; and has received research grants for her Department from Biogen, Merck, Roche, and Novartis. Giovanna De Luca has served on scientific advisory boards for Merck, Biogen, Novartis, Roche, and Sanofi Genzyme and has received funding for travel and speaker honoraria from Biogen, Merck, Novartis, Sanofi Genzyme, and Roche. Alessandra Lugaresi has received personal compensation for consulting, serving on a scientific advisory board, speaking or other activities from Biogen, Merck Serono, Mylan, Novartis, Roche, Sanofi/Genzyme, and Teva. Her institutions have received research grants from Novartis. Guillermo Izquierdo has received speaking honoraria from Almirall, Biogen, Merck, Novartis, Roche, Sanofi, and Teva. Pierre Grammond has served in advisory boards for Novartis, EMD Serono, Roche, Biogen, Sanofi Genzyme, and Pendopharm and has received grant support from Genzyme and Roche; his institution has also received research grants from Biogen, Sanofi Genzyme, and EMD Serono. Pierre Duquette has received support for organised continuing medical education activities and travel fees to attend advisory meetings from Biogen, EMD Serono, Genzyme, and Novartis. Raed Alroughani has received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche, Sanofi, and Genzyme. Eugenio Pucci has received travel grants from Roche, Novartis, Merck, Genzyme-Sanofi, Biogen, and Teva and received equipment from Associazione Marchigiana Sclerosi Multipla e altre malattie neurologiche. Franco Granella has received research funding from Biogen and Sanofi Genzyme; fees for advisory boards and speaker honoraria from Biogen, Merck Serono, Novartis, Roche, and Sanofi Genzyme; and travel funding from Biogen, Merck Serono, Roche, and Sanofi Genzyme. Jeannette Lechner-Scott has accepted travel compensation from Novartis, Biogen, and Merck Serono; her institution receives the honoraria for talks and advisory board commitments as well as research grants from Biogen Merck, Roche, TEVA, and Novartis. Patrizia Sola has served on scientific advisory boards for Biogen and Teva; has received funding for travel and speaker honoraria from Bayer, Biogen, Merck, Novartis, Sanofi Genzyme, and Teva; and has received research grants for her institution from Bayer, Biogen, Merck, Novartis, Sanofi, and Teva. Diana Ferraro has received travel funding or speaker honoraria from Merck, Biogen, Sanofi, Novartis, Teva, and Roche and has served on advisory boards for Biogen, Merck, Novartis, Sanofi, and Roche. Francois Grand’Maison has received honoraria or research funding from Biogen, Genzyme, Mitsubishi, Novartis, Ono Pharmaceuticals, and Teva Neuroscience. Murat Terzi has received travel grants from Merck & Co., Novartis, Bayer-Schering, and Teva Pharmaceutical Industries and has participated in clinical trials by Sanofi-Aventis, Roche, and Novartis. Csilla Rozsa has received speakers’ honoraria from Biogen, Merck Serono, Roche, and Sanofi Genzyme; travel grants from Biogen, Merck, and Sanofi Genzyme; and fees for advisory boards from Biogen, Merck Serono, Novartis, and Teva. Cavit Boz has received conference travel support from Biogen, Novartis, Bayer-Schering, Merck, and Teva. Raymond Hupperts has received nurse support from Merck and Sanofi and has served on advisory boards for Sanofi, Biogen, and Roche. Vincent Van Pesch has received travel grants from Merck, Biogen, Sanofi, Bristol Meyer Squibb, Almirall, and Roche. His institution has received research grants and consultancy fees from Roche, Biogen, Sanofi, Bristol Meyer Squibb, Merck, Almirall, and Novartis Pharma. Celia Oreja-Guevara has received honoraria for speaking and consulting fees from Biogen, Celgene, Alexion, Merck, Novartis, Roche, Sanofi Genzyme, and Teva. Anneke van der Walt is an employee of Monash University and has accepted travel compensation from Merck, Biogen, and Roche; she has received honoraria for talks, steering committee activities, and research grants from Roche, Merck, Biogen, and Novartis. Vilija Jokubaitis is an employee of Monash University; she has accepted travel compensation from Biogen, Merck, and Roche and speakers’ honoraria from Biogen and Roche. Tomas Kalincik has served on scientific advisory boards for Roche, Sanofi Genzyme, Novartis, Merck, and Biogen and a steering committee for the Brain Atrophy Initiative supported by Sanofi Genzyme; has received conference travel support and/or speaker honoraria from WebMD Global, Novartis, Biogen, Sanofi Genzyme, Teva, BioCSL, and Merck; and has received research support from Biogen. Helmut Butzkueven is an employee of Monash University and has accepted travel compensation from Merck, Biogen, and Roche; his institution receives honoraria for talks, steering committee activities, and research grants from Roche, Merck, Biogen, Genzyme, Novartis, and Medday Pharma.

Figures

Fig. 1
Fig. 1
Patient selection flow chart for MSBase analysis. BRACETD interferon-based therapies, glatiramer acetate, dimethyl fumarate, and teriflunomide, RRMS relapsing-remitting multiple sclerosis. aRequires completion of ≥ 12 months uninterrupted treatment with a BRACETD therapy and a < 6-month gap between discontinuing the BRACETD therapy and initiating the switch therapy. bAll variables included in the propensity score matching algorithm (Table 1 in the main text) were required for inclusion in the analysis
Fig. 2
Fig. 2
Model structure diagram for cost-effectiveness analysis. BRACETD interferon-based therapies, glatiramer acetate, dimethyl fumarate, and teriflunomide, EDSS Expanded Disability Status Scale, RRMS relapsing-remitting multiple sclerosis, SPMS secondary progressive multiple sclerosis. Note: While not shown in the figure, EDSS changes of more than one level are permitted. aDeath is reachable from all health states
Fig. 3
Fig. 3
Comparative effectiveness analysis results for natalizumab and fingolimod compared with BRACETD. ARR annualised relapse rate, BRACETD interferon-based therapies, glatiramer acetate, dimethyl fumarate, and teriflunomide, CDI6M 6-month–confirmed disability improvement, CDW6M 6-month–confirmed disability worsening, CI confidence interval, HR hazard ratio, RR risk ratio. Note: The comparative effectiveness outcomes for ARR (panel a), CDW6M (panel c), and CDI6M (panel d) for natalizumab and fingolimod compared with BRACETD were used in the base-case cost-effectiveness analysis. The time-to-first relapse outcomes (panel b) were not used in the cost-effectiveness analysis
Fig. 4
Fig. 4
One-way and probabilistic sensitivity analysis results for cost-effectiveness analysis. BRACETD interferon-based therapies, glatiramer acetate, dimethyl fumarate, and teriflunomide, EDSS Expanded Disability Status Scale, NMB net monetary benefit, OWSA one-way sensitivity analysis, PSA probabilistic sensitivity analysis, QALY quality-adjusted life-year, SPMS secondary progressive multiple sclerosis, WTP willingness-to-pay. Note: For all parameters varied in the OWSA (panel a), natalizumab remained dominant compared with fingolimod. The NMB outcomes were estimated using a WTP threshold of £30,000 per QALY gained. The PSA results are presented in panel b
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