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. 2023 Jul 24;9(3):20552173231187810.
doi: 10.1177/20552173231187810. eCollection 2023 Jul-Sep.

The socioeconomic impact of disability progression in multiple sclerosis: A retrospective cohort study of the German NeuroTransData (NTD) registry

Paul Dillon, Yanic Heer  1 , Eleni Karamasioti  1 , Erwan Muros-Le Rouzic  2 , Guiseppe Marcelli  2 , Danilo Di Maio  3 , Stefan Braune  2 , Gisela Kobelt  4   5 , Jürgen Wasem  6
Affiliations

The socioeconomic impact of disability progression in multiple sclerosis: A retrospective cohort study of the German NeuroTransData (NTD) registry

Paul Dillon et al. Mult Scler J Exp Transl Clin. .

Abstract

Background: Multiple sclerosis (MS) is a progressively debilitating neurologic disease that poses significant costs to the healthcare system and workforce.

Objective: To evaluate the impact of MS disease progression on societal costs and quality of life (QoL) using data from the German NeuroTransData (NTD) MS registry.

Methods: Cross-sectional cohort study. The cost cohort included patients with MS disability assessed using Expanded Disability Status Scale (EDSS) in 2019 while the QoL cohort included patients assessed using EDSS and EuroQol-5 Dimension 5-Levels between 2009 and 2019. Direct and indirect medical, and non-medical resource use was quantified and costs derived from public sources.

Results: Within the QoL cohort (n = 9821), QoL worsened with increasing EDSS. Within the cost cohort (n = 7286), increasing resource use with increasing EDSS was observed. Societal costs per patient, excluding or including disease-modifying therapies, increased from €5694 or €19,315 at EDSS 0 to 3.5 to €25,419 or €36,499 at EDSS 4 to 6.5, and €52,883 or €58,576 at EDSS 7 to 9.5. In multivariate modeling, each 0.5-step increase in EDSS was significantly associated with increasing costs, and worsening QoL.

Conclusion: This study confirms the major socioeconomic burden associated with MS disability progression. From a socioeconomic perspective, delaying disability progression may benefit patients and society.

Keywords: Multiple sclerosis; disease progression; economic burden of disease; quality of life.

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Conflict of interest statement

Paul Dillon was an employee of F. Hoffmann-La Roche Ltd, Basel, Switzerland during completion of the work related to this manuscript and has shares/ownership of F. Hoffmann-La Roche Ltd. Yanic Heer was an employee of PricewaterhouseCoopers (PwC), Zurich, Switzerland during completion of the work related to this manuscript. Eleni Karamasioti was an employee of PricewaterhouseCoopers (PwC), Zurich, Switzerland during completion of the work related to this manuscript. Erwan Muros-Le Rouzic is an employee of and shareholder in F. Hoffmann-La Roche Ltd, Basel, Switzerland. Giuseppe Marcelli is an employee of F. Hoffmann-La Roche Ltd, Basel, Switzerland. Danilo Di Maio is an employee of F. Hoffmann-La Roche Ltd, Basel, Switzerland. Stefan Braune received honoraria from Kassenärztliche Vereinigung Bayerns and health maintenance organizations for patient care, and from Biogen, Merck, NeuroTransData, Novartis, and Roche for consulting, project management, clinical studies, and lectures; he also received honoraria and expense compensation as a board member of NeuroTransData. Gisela Kobelt is president of EHE International GmbHan and employee of European Health Economics, Mulhouse, France. Jürgen Wasem is a professor for health services management at University Duisburg-Essen, Germany. He has received an honorarium for consulting study concept and quality assurance of data calculations.

Figures

Figure 1.
Figure 1.
Population flowchart for the QoL and cost populations. Full covariate list: age, sex, living status, educational attainment, time since diagnosis, time since manifestation, MS subtype, time since last relapse, number of relapses in previous year, time since last confirmed disability progression, current DMT, and time since last DMT change. DMT, disease-modifying therapy; EDSS, Expanded Disability Status Scale; EQ-5D-5L, EuroQol-5 Dimension 5-Llevels; HCRU, healthcare resource utilization; MS, multiple sclerosis; NTD, NeuroTransData; QoL, quality of life.
Figure 2.
Figure 2.
Study population demographics and MS disease characteristics. DMT, disease-modifying therapy; EDSS, Expanded Disability Status Scale; MS, multiple sclerosis; NTD, NeuroTransData; RRMS, relapsing-remitting multiple sclerosis; SD, standard deviation.
Figure 3.
Figure 3.
Mean utility estimated with the EQ-5D-5L by EDSS level in the NTD registry QoL population (2009–2019) compared with Flachenecker et al. NTD utility population (2009–2019) N = 9435, Flachenecker et al. Patients with EDSS >7 are not included in this chart due to low numbers and wide error bars. Note the previous study relied on patient-reported EDSS, which has minor scoring differences at low EDSS compared with the official EDSS. EDSS, Expanded Disability Status Scale; EQ-5D-5L, EuroQol-5 Dimension 5-Levels; NTD, NeuroTransData; QoL, quality of life.
Figure 4.
Figure 4.
Multivariate regression models of the association between EDSS and separately: (A) QoL (n = 9821) and (B) costs (n = 7286). QoL (measured using German value set); multivariate regression model was adjusted for age, living status, sex, time since last relapse, time since MS diagnosis, time since manifestation, time since last DMT change, number of relapses in previous year, time since last confirmed progression event, current DMT use, educational attainment, MS subtype, and included NTD center as a random effect. CI, confidence interval; DMT, disease-modifying therapy; EDSS, Expanded Disability Status Scale; MS, multiple sclerosis; NTD, NeuroTransData; QoL, quality of life.
Figure 5.
Figure 5.
Percentage of patients per EDSS score within the NTD registry cost population (2019): (A) requiring direct non-medical investments; (B) requiring direct medical care (including inpatient, outpatient, and short-term care) and direct non-medical care (including family, domestic, and community daycare); (C) incurring direct medical costs (including consultations, tests, and non-DMT medications [fampridine and cannabinoids]); (D) with indirect costs due to short-term and long-term leave. NTD cost population (2019) N = 7286. Note: for those of working age less than 65 years, n = 6838, and for those of working age and working full time, n = 3195. AU, sick day; DMT, disease-modifying therapy; EDSS, Expanded Disability Status Scale; MRI, magnetic resonance imaging; NTD, NeuroTransData; y, year.
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