Content uploaded by Tjalf Ziemssen
Author content
All content in this area was uploaded by Tjalf Ziemssen on Mar 30, 2022
Content may be subject to copyright.
Comparing the long-term clinical and economic
impact of ofatumumab versus dimethyl fumarate
and glatiramer acetate in patients with relapsing
multiple sclerosis: A cost-consequence analysis
from a societal perspective in Germany
Dominik Koeditz, Juergen Frensch, Martin Bierbaum , Nils-Henning Ness, Benjamin Ettle,
Umakanth Vudumula, Kapil Gudala, Nicholas Adlard, Santosh Tiwari and Tjalf Ziemssen
Abstract
Background: Evidence suggests that early highly efficacious therapy in relapsing multiple sclerosis is
superior to escalation strategies.
Objective: A cost-consequence analysis simulated different treatment scenarios with ofatumumab (OMB),
dimethyl fumarate (DMF) and glatiramer acetate (GA): immediate OMB initiation as first treatment, early
switch to OMB after 1 year on DMF/GA, late switch after 5 years or no switch.
Methods: An EDSS-based Markov model with a 10-year time horizon was applied. Cycle transitions
included EDSS progression, improvement or stabilization, treatment discontinuation, relapse or death.
Input data were extracted from OMB trials, a network meta-analysis, published literature, and publicly
available sources.
Results: The late switch compared to the immediate OMB scenario resulted in a lower proportion of
patients with EDSS 0–3(Δ−7.5% DMF; Δ−10.3% GA), more relapses (Δ+0.72 DMF; Δ+1.23
GA) and lower employment rates (Δ−4.0% DMF; Δ−5.6% GA). The same applies to late versus
early switches. No switch scenarios resulted in worse outcomes. Higher drug acquisition costs in the imme-
diate OMB and early switch scenarios were almost compensated by lower costs for patient care and prod-
uctivity loss.
Conclusion: Immediate OMB treatment and an early switch improves clinical and productivity outcomes
while remaining almost cost neutral compared to late or no switches.
Keywords: multiple sclerosis, disease-modifying therapies, disability progression, societal costs
Date received: 11 October 2021; revised: 21 January 2022; accepted 18 February 2022
Introduction
Multiple sclerosis (MS) is a chronic, inflammatory,
autoimmune disease of the central nervous system
manifesting typically between 20 and 40 years of
age and leading to accumulation of disability.
1
The
disease represents an enormous health and societal
burden.
2,3
Current strategies in relapsing MS (RMS), i.e., clinic-
ally isolated syndrome, relapsing-remitting MS
(RRMS) and active secondary progressive MS
(SPMS), initially suggest mildly to moderately effect-
ive therapies (e.g. beta interferons, glatiramer acetate
[GA], dimethyl fumarate [DMF], and teriflunomide)
followed by a switch to highly effective therapies
(e.g. fingolimod, natalizumab, ocrelizumab, alemtu-
zumab, cladribine) in case of insufficient response.
4–6
The use of highly effective, disease-modifying therap-
ies (DMT) in the early phase of MS is evolving,
7–10
as
an early window of opportunity is assumed, when
Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/
licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as
specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Correspondence to:
Tjalf Ziemssen,
Zentrum fuer klinische
Neurowissenschaften,
Universitaetsklinikum Carl
Gustav Carus, Fetscherstraße
74, 01307 Dresden,Germany.
Tjalf.Ziemssen@
uniklinikum-dresden.de
Dominik Koeditz,
Juergen Frensch,
Martin Bierbaum,
Novartis Pharma GmbH,
Nuremberg, Germany
Original Research Article
Multiple Sclerosis Journal—
Experimental, Translational
and Clinical
January–March 2022, 1–12
DOI: 10.1177/
20552173221085741
© The Author(s), 2022.
Article reuse guidelines:
sagepub.com/journals-
permissions
treatment is most effective and critical to maintain
neurological function
11
and reduce disability progres-
sion.
8–10
In line with this, the early intervention with
fingolimod, natalizumab and alemtuzumab in patients
with RRMS was associated with a reduced risk of tran-
sition to SPMS.
7
The anti-CD20 monoclonal antibodies ocrelizumab
and ofatumumab (OMB) are highly effective DMTs,
which selectively deplete B-cells.
12,13
Ocrelizumab
is a humanized antibody and is applied through intra-
venous infusion,
13
while OMB is fully human and can
be applied subcutaneously.
12
Treatment with ocreli-
zumab or OMB significantly reduced the relapse
rates compared to standard treatment in the pivotal
RMS studies.
14,15
The early application of OMB
revealed a positive benefit-risk ratio in the pivotal
ASCLEPIOS trials, which was even more pro-
nounced in treatment-naïve RMS patients.
14,16
OMB
was approved for RMS in August 2020 by the
United States Food and Drug Administration
17
and
in March 2021 by the European Medicines Agency.
18
Beyond clinical outcomes, cost consequences are
becoming a focal point of drug characterizations,
19
but have not yet been evaluated for OMB. The object-
ive of the present analysis was to simulate the long-
term clinical and health economic effects of an imme-
diate initiation of OMB (at time of first treatment)
compared to an early (after one year), a late (after 5
years) and no switch to OMB after standard DMT
in RMS patients. For this purpose, a cost-consequence
analysis (CCA) was applied. A CCA approach
involves wide-ranging assessments of direct and
indirect costs as well as various outcomes (conse-
quences). In contrast to cost-effectiveness analyses
or cost-utility analyses, outcomes are listed separ-
ately, and no cost-outcome ratio is calculated. The
CCA provides decision-makers with a comprehensive
overview of the impact of interventions, enabling
them to form their opinions about the relative import-
ance of costs and outcomes in their particular
context.
20
Materials and methods
This CCA is a mathematical simulation which com-
bines clinical and health economic data of RMS
patients from various sources in a discrete-time
Markov model. The model assumes that the patient
is always in one of a finite number of discrete health
states. Disease improvement or worsening is repre-
sented as the risk of transition to another Markov
(health) state within a certain time frame (cycle).
Clinical and health economic data are assigned to
these health states and accumulated over time per
patient. The Markov states are based on the
Expanded Disability Status Score (EDSS) using
integer EDSS values (intermediates were rounded
down). The cohort was exposed to the following
risks in each cycle: EDSS progression, EDSS
improvement, stable EDSS, DMT discontinuation at
an EDSS > 6.0 (in line with OMB trials), relapse or
death.
Details of the model structure and the input variables
are described in the supplement. In brief, the model
included patients with RMS and a baseline EDSS of
0–6. The treatment-naïve subpopulation of the com-
bined ASCLEPIOS I and II trials were used for base-
line data input. This subpopulation was typical of
early RMS with 98.7% RRMS and 1.3% SPMS
patients, a mean (±standard deviation, SD) EDSS
of 2.3 ±1.2, a mean (±SD) age of 36.3 ±9.23 years
and 33.0% male patients (Supplementary Table S1).
The transition probabilities between EDSS states of
the untreated model were based on published British
Columbia Natural History data. Annualized relapse
rates (ARR) in the natural history model ranged
from approximately 0.7 (EDSS ≤4) to 0.5 (EDSS >
4) (Supplementary Table S2). The transition probabil-
ities and relapse rates for the treatment-adjusted
model were derived from 6-month confirmed disabil-
ity progression (6-CDP) and relapse rates of a
network meta-analysis (NMA), respectively. Details
on the resulting NMA including study comparability
have been published by Samjoo et al.
21
The CDP
and ARR results included in the model are presented
in Supplementary Table S2. Mortality rates were
based on the general population mortality,
22
stratified
for gender and age and adjusted using MS population
mortality hazard ratios.
23
Productivity loss data, dis-
ability weights of health states, drug- and
disease-related costs were identified from published
literature and publicly available data sources
(Supplementary Tables S3–S6). Costs and effects
were discounted at 3% per year. The assignment to
an EDSS health state based on the untreated and
treated transition probabilities and relapse rates deter-
mined clinical and economic outcomes.
Scenarios
Four scenarios with a time horizon of 10 years were
simulated. The two base scenarios evaluated OMB
versus standard DMT (DMF or GA) without any
treatment switches. Two switch scenarios were
defined similar to an analysis of the MSBase registry
and the Swedish MS registry recently reported by He
et al.
9
He et al.
9
analyzed patients who started 0–2
Nils-Henning Ness,
Hexal AG, Holzkirchen,
Germany
Benjamin Ettle,
Novartis Pharma GmbH,
Nuremberg, Germany
Umakanth Vudumula,
Novartis Ireland Limited,
Dublin, Ireland
Kapil Gudala,
Novartis Healthcare Pvt. Ltd,
Hyderabad, India
Nicholas Adlard,
Novartis Pharma AG, Basel,
Switzerland
Santosh Tiwari,
Novartis Ireland Limited,
Dublin, Ireland
Tjalf Ziemssen,
Zentrum für klinische
Neurowissenschaften,
Universitaetsklinikum Carl
Gustav Carus Dresden,
Dresden, Germany
Multiple Sclerosis Journal—Experimental, Translational and Clinical
2 www.sagepub.com/msjetc
years (early) or 4–6 years (late) after clinical disease
onset. The mean time to first high-efficacy therapy
was 1.08 years (SD 0.52) in the early and 4.99
years (SD 0.60) in the late treatment group. To
allow for comparability with real-life data reported
by He et al.
9
the present simulation accordingly
included a scenario with early switch to OMB after
one year of treatment with DMF (early DMF/OMB
group) or GA (early GA/OMB group) as well as a
late switch scenario after 5 years of DMF or GA treat-
ment (late DMF/OMB group and late GA/OMB
group).
Model outcomes
Clinical outcomes included EDSS distribution, time
spent in different health states, mean EDSS score
over time, progression to immobility (EDSS ≥7),
and number of relapses. Further clinical outcomes
were disability-adjusted life years (DALY), including
year’s life-lost (YLL) and years lived with disability
(YLD). YLL corresponds to the number of deaths
multiplied by the remaining age- and sex-specific
life expectancy of the general population at the time
of death. To calculate the YLD, the number of
patients in a particular EDSS state was multiplied
by MS-specific weighting factors.
Economic analyses were conducted from the societal
perspective accounting for direct and indirect costs
regardless of who bears them. Direct costs comprised
healthcare costs (DMT acquisition, inpatient care, day
care admissions, consultations, tests and investiga-
tions, other medications than DMT) as well as costs
for services and informal care (community and
social services, investments, equipment and aids,
informal care). The calculations for informal care
costs included resource utilization in time in days.
Indirect costs comprised expenses associated with
MS-related productivity loss (short-term absenteeism,
long-term absenteeism, invalidity, and early retire-
ment). The calculations were based on the productiv-
ity outputs (proportion of patients being employed/
self-employed, working full-time or receiving invalid-
ity pension). Input data on direct and indirect costs
include relapse-related expenses (e.g. healthcare
costs, medications, absenteeism). As it remained
unclear, to which extent relapse-related costs have
already been covered, relapse costs were estimated
separately. For this purpose, the quarterly costs
reported by Ness and colleagues
24
were upscaled to
annual relapse costs and estimated at 2662 €, taking
into account the consumer price indices
(Supplementary Table S6).
Sensitivity analyzes
Univariate sensitivity analyses were performed to
determine the impact of drug acquisition costs of
OMB at Year 1, 2 and from Year 2 onwards,
6-CDP hazard ratio; cohort size, age, gender; discount
rates and annual relapse costs on the model outputs.
The factors varied the parameter value by +10% or
−10% of the base case value.
Results
Clinical outcomes, informal care utilization and
productivity output
Patients immediately treated with OMB had a lower
degree of disability after 10 years compared to
patients who initially received a standard DMT. In
detail, the proportion of patients with no or mild
impairment (EDSS 0–3) was lower in the late
switch scenario compared to the immediate
OMB scenario (DMF/OMB Δ−7.5%; GA/OMB
Δ−10.3%) while early switch scenarios showed
minor differences (DMF/OMB Δ−1.4%; GA/OMB
Δ−2.0%). Vice versa, the proportion of immobile
patients (EDSS 7–9) in the immediate OMB cohort
and the early switch scenario were comparable
(DMF/OMB Δ+0.7%; GA/OMB Δ+0.9%) but
increased in the late switch scenario (DMF/OMB Δ
+3.5%; GA/OMB Δ+4.9%) (Table 1). Mean
EDSS after 10 years was lower in the immediate
OMB group (2.4) and the early switch groups (2.5
early DMF/OMB and 2.5 early GA/OMB) compared
to the late switch scenario (2.9 late DMF/OMB and
3.0 late GA/OMB) (Figure 1(a) and (b)). EDSS distri-
bution over time is presented in Supplementary
Figure 2S and 3S. Patients with immediate or early
OMB treatment remained in EDSS stages 0–3 for 8
years while those in the late switch scenario remained
there for 7 years (Figure 2(a) and (b)).
The number of DALYs increased with the duration of
standard treatment compared to immediate OMB
treatment (early switch: DMF/OMB Δ+0.07%; GA/
OMB Δ+0.10%; late switch: DMF/OMB Δ+0.28%;
GA/OMB Δ+0.40%) (Table 1). The increase of
DALYs depended solely on YLD (Table 1). The
analysis also revealed more relapses in the late switch
compared to the immediate OMB scenario (DMF/
OMB Δ+0.72; GA/OMB Δ+1.23), while the early
OMB scenario showed minor differences (DMF/OMB
Δ+0.15; GA/OMB Δ+0.26) (Table 1).
After 10 years, the proportion of patients still
employed or self-employed at working age was
lower in the late switch scenarios (DMF/OMB Δ
Koeditz et al.
www.sagepub.com/msjetc 3
Table 1. Outcomes (OMB vs. DMF/GA).
Base-Scenario (10/0)
a
Scenario A (1/9)
b
Scenario B (5/5)
c
Base-Scenario (0/10)
a
Outcomes OMB
DMF&OMB
Δ
*
GA&OMB
Δ
*
DMF&OMB
Δ
*
GA&OMB
Δ
*
DMF
Δ
*
GA
Δ
*
Clinical outcomes
% Patient distribution in EDSS states
Mild disability (EDSS 0–3) 76.1% −1.4% −2.0% −7.5% −10.3% −14.7% −20.2%
Walking aid (EDSS 4–6.5) 18.0% +0.8% 1.1% +4.0% +5.4% +8.2% +10.7%
Wheelchair (EDSS 7) 2.4% +0.3% +0.3% +1.2% +1.7% +2.8% +4.1%
Bedridden (EDSS 8–9) 3.5% +0.4% +0.6% +2.3% +3.2% +3.7% +5.4%
Immobile patients (EDSS 7–9) 5.9% +0.7% +0.9% +3.5% +4.9% +6.5% +9.5%
DALYs 1.49 +0.07 +0.10 +0.28 +0.40 +0.38 +0.53
YLD 0.86 +0.07 +0.10 +0.28 +0.40 +0.38 +0.53
YLL 0.63 0 0 0 0 0 0
Number of relapse events 2.15 +0.15 +0.26 +0.72 +1.23 +1.33 +2.26
Informal care utilization
Informal care (time in days) 168.38 +12.44 +17.13 +52.42 +74.27 +71.12 +101.50
Productivity output
Employed or self-employed at working
age (%)
d
62.3% −0.7% −1.0% −4.0% −5.6% −8.0% −11.0%
Working full time (%)
e
36.7% −0.1% −0.1% −0.4% −0.6% −0.8% −1.1%
Receiving invalidity pension (%)
d
26.5% +0.6% +0.8% +2.8% +3.9% +5.4% +7.6%
DALYs: Disability adjusted life years; DMF: Dimethyl fumarate; EDSS: Expanded Disability Status Scale; GA: Glatiramer acetate; OMB: Ofatumumab; YLD: Years lost due to
disability; YLL: Years of life lost; Δ: Difference.
*
The delta indicates the difference in outcomes between the comparator arms of the respective scenarios (baseline scenario, scenario A & B) and the intervention group (10 years
of OMB administration).
a
Base-Scenario: H2H: 10 years of therapy with OMB vs. 10 years of therapy with DMF/GA.
b
Scenario A: 1-year therapy with DMF/GA followed by 9 years of treatment with OMB.
c
Scenario B: 5 years therapy with DMF/GA followed by 5 years of treatment with OMB.
d
Measured in terms of the number of people of working age (retirement age: 67).
e
Measured in terms of the number of employees.
Multiple Sclerosis Journal—Experimental, Translational and Clinical
4 www.sagepub.com/msjetc
−4.0%; GA/OMB Δ−5.6%) compared to immedi-
ate OMB treatment. More patients received invalid-
itypensioninthelateswitchcomparedtoimmediate
OMB scenario (DMF/OMB Δ+2.8%; GA/OMB Δ
+3.9%). Informal care was utilized to a consider-
ably higher extent in the late switch scenario com-
pared to the group with immediate OMB treatment
(DMF/OMB Δ+52.42 days; GA/OMB Δ+74.27
days) (Table 1). Differences between early switch
and immediate OMB scenarios regarding productiv-
ity and informal care use were marginal (Table 1).
The worst results with respect to clinical outcomes,
informal care utilization and productivity output
were estimated for patients receiving standard DMT
throughout 10 years (Table 1; Figures 1(a), (b), 2(a)
and (b)).
Economic outcomes from a societal perspective
For 10 years treatment with OMB, cumulative DMT
costs of 145,918 €per patient were estimated. The
costs slightly decreased in the early switch scenario
(DMF/OMB Δ−6.3%; GA/OMB Δ−4.9%) and to
a greater extent in the late switch scenario (DMF/
OMB Δ−22.2%; GA/OMB Δ−15.4%). These
decreases were contrasted by higher costs especially
in the late and no switch scenario for inpatient care,
informal care, community, and social services as
Figure 1. Development of the mean EDSS score over 10 years per scenario; OMB vs. DMF (A); OMB vs. GA (B); DMF,
Dimethyl fumarate; EDSS, Expanded Disability Status Scale; GA, Glatiramer acetate; OMB, Ofatumumab.
Koeditz et al.
www.sagepub.com/msjetc 5
well as long-term absence, invalidity and early retire-
ment (Table 2).
The different scenarios resulted in similar expendi-
tures when direct and indirect costs were summarized
(Table 2). Direct and indirect costs amounted to
294,470 €per patient for 10 years of OMB treatment
with small differences of Δ−8.0% to Δ+3.3% com-
pared to the other scenarios. Taking into account the
costs of relapses (5028 €), the total costs for 10
years of OMB treatment amounted to 299.498 €
with small differences of Δ−6.8% to Δ+4.0% com-
pared to the switch scenarios (Table 2).
The breakdown of cost types per scenario revealed
that DMT costs accounted for more than half of
direct costs, followed by costs for informal care,
inpatient care, and consultations. Indirect costs were
dominated by the expenses due to long-term
absence from work, invalidity, and early retirement.
Approximately two thirds of the total costs were
attributed to direct costs and one third to indirect
costs. A general cost shifting trend from direct to
indirect costs was observed starting from immediate
OMB treatment over early to late switch scenarios
(Table 3).
Sensitivity analyses
Sensitivity analyses showed that the incremental costs
were primarily influenced by DMT costs from the
second year onwards. In addition, the results are par-
ticularly sensitive to the hazard ratio of 6-CDP.
Variations in annual relapse costs as well as age and
gender distribution did not impact the results
(Figure 3; Figure 4S and 5S).
Discussion
Over 10 years, immediate OMB treatment or early
switch after standard therapy with DMF or GA was
estimated to delay EDSS progression, reduce relapse
rates, and result in fewer DALYs, less days with infor-
mal care as well as higher productivity compared to
prolonged standard DMTs. Higher DMT costs asso-
ciated with immediate or early OMB treatment were
compensated by lower additional direct and indirect
costs compared to prolonged standard DMTs. The
model produced stable and plausible estimates and
Figure 2. Patient time spent in health states (in years); OMB vs. DMF (A); OMB vs. GA (B); DMF, Dimethyl fumarate;
EDSS, Expanded Disability Status Scale; GA, Glatiramer acetate; OMB, Ofatumumab.
Multiple Sclerosis Journal—Experimental, Translational and Clinical
6 www.sagepub.com/msjetc
Table 2. Breakdown of costs (discounted)—costs per patient.
Base-Scenario (10/0)
a
Scenario A (1/9)
b
Scenario B (5/5)
c
Base-Scenario (0/10)
a
OMB
DMF&OMB
Δ%
*
GA&OMB Δ
%
*
DMF&OMB Δ
%
*
GA&OMB Δ
%
*
DMF
Δ%
*
GA
Δ%
*
Direct costs**
Healthcare costs (€)
DMT costs 145.918 −6.3% −4.9% −22.2% −15.4% −36.9% −24.3%
Inpatient care 14.963 +4.6% +6.4% +17.9% +24.8% +23.3% +32.3%
Day care admissions 1.281 +1.8% +2.4% +6.8% +9.2% +8.9% +11.9%
Consultations 10.125 +2.0% +2.8% +7.7% +10.6% +10.1% +13.8%
Tests & Investigations 2.866 −0.1% −0.1% −0.3% −0.6% −0.4% −0.7%
Medications 5.270 +5.0% +6.9% +18.7% +25.8% +24.3% +33.5%
Services and informal care costs (€)
Community & social services 4.815 +11.2% +15.4% +45.9% +65.3% +60.1% +85.9%
Investments, equipment & aids 4.463 +7.6% +10.4% +29.2% +40.8% +38.2% +53.5%
Informal care 15.220 +8.4% +11.5% +33.0% +46.4% +43.4% +61.1%
Sum direct costs (€)204.921 −2.9% −1.2% −9.4% −2.1% −17.9% −5.6%
Indirect costs
Short-term absence 5.617 −0.6% −0.8% −1.8% −2.8% −2.1% −3.5%
Long-term absence, invalidity &
early retirement
83.932 +3.3% +4.5% +12.3% +17.0% +16.1% +21.9%
Sum indirect cost (€)89.549 +3.0% +4.2% +11.5% +15.7% +14.9% +20.3%
Total costs
Sum direct/indirect costs (€)
#
294.470 −1.1% +0.4% −3.1% +3.3% −8.0% +2.3%
Relapse costs (€)
#
5.028 +7.8% +13.4% +35.5% +61.0% +61.7% +105.1%
Total costs (€)
#
299.498 −0.9% +0.6% −2.4% +4.3% −6.8% +4.0%
DMF: Dimethyl fumarate; DMT: Disease-modifying therapies; GA: Glatiramer acetate; OMB: Ofatumumab.
*
The delta indicates the difference in costs between the comparator arms of the respective scenarios (base-scenario, scenario A & B) and the intervention group (10 years of OMB
treatment). A negative delta (−) is equivalent to lower costs in the cohorts with permanent DMF administration or delayed therapy initiation compared to the population with
permanent OMB treatment. A positive delta (+) equates to lower costs in the intervention group compared to the respective comparator arms.
** Direct costs also include “out-of-pocket”expenses, making it impossible to look at them from a payor perspective.
#: Direct and indirect costs extracted from the referenced data sources include relapse-related expenses, however, it remained unclear, to which extent relapse-related costs were
covered. In case of incomplete coverage of relapse costs in the input data, the sum of direct/indirect costs might underestimate MS-related costs. Therefore, a separate estimation of
relapse-related costs was included in the total costs. As the sum of direct and indirect costs already include relapse costs at least partially, the total cost estimation represents an
overestimation.
a
Base-Scenario: H2H: 10 years of therapy with OMB vs. 10 years of therapy with DMF/GA.
b
Scenario A: 1-year therapy with DMF/GA followed by 9 years of treatment with OMB.
c
Scenario B: 5 years therapy with DMF/GA followed by 5 years of treatment with OMB.
Koeditz et al.
www.sagepub.com/msjetc 7
Table 3. Percentage breakdown of cost types per scenario (OMB vs. DMF/GA).
Base-Scenario
(10/0)
a
Scenario A
(1/9)
b
Scenario B
(5/5)
c
Base-Scenario
(0/10)
a
OMB DMF&OMB GA&OMB DMF&OMB GA&OMB DMF GA
Direct costs
Healthcare costs
DMT costs
d
71.2% 68.7% 68.6% 61.2% 61.5% 54.7% 57.1%
Inpatient care
d
7.3% 7.9% 7.9% 9.5% 9.3% 11.0% 10.2%
Day case admissions
d
0.6% 0.7% 0.6% 0.7% 0.7% 0.8% 0.7%
Consultations
d
4.9% 5.2% 5.1% 5.9% 5.6% 6.6% 6.0%
Tests & Investigations
d
1.4% 1.4% 1.4% 1.5% 1.4% 1.7% 1.5%
Medications
d
2.6% 2.8% 2.8% 3.4% 3.3% 3.9% 3.6%
Services and informal care costs
Community & social services
d
2.3% 2.7% 2.7% 3.8% 4.0% 4.6% 4.6%
Investments, equipment & aids
d
2.2% 2.4% 2.4% 3.1% 3.1% 3.7% 3.5%
Informal care
d
7.4% 8.3% 8.4% 10.9% 11.1% 13.0% 12.7%
Sum direct costs
e
69.6% 68.3% 68.4% 65.0% 65.9% 62.0% 64.2%
Indirect costs
Short-term absence
f
6.3% 6.1% 6.0% 5.5% 5.3% 5.3% 5.0%
Long-term absence, invalidity & early retirement
f
93.7% 93.9% 94.0% 94.5% 94.7% 94.7% 95.0%
Sum indirect costs
e
30.4% 31.7% 31.6% 35.0% 34.1% 38.0% 35.8%
Sum direct/indirect costs 100% 100% 100% 100% 100% 100% 100%
Relapse costs
e
1.7% 1.9% 1.9% 2.4% 2.7% 3.0% 3.4%
DMF: Dimethyl fumarate; DMT: Disease-modifying therapies; GA: Glatiramer acetate; OMB: Ofatumumab.
a
Base-Scenario: H2H: 10 years of therapy with OMB vs. 10 years of therapy with DMF/GA.
b
Scenario A: 1-year therapy with DMF/GA followed by 9 years of treatment with OMB.
c
Scenario B: 5 years therapy with DMF/GA followed by 5 years of treatment with OMB.
d
In proportion to direct costs.
e
In proportion to sum direct/indirect costs (Basis: lower cost limit).
f
In proportion to indirect costs.
Multiple Sclerosis Journal—Experimental, Translational and Clinical
8 www.sagepub.com/msjetc
was insensitive to variables known to have no impact
on total costs, e.g., gender.
25
Our results are in line with clinical studies and real-
world evidence reporting a reduced risk of disability
progression with highly effective compared to stand-
ard DMTs.
7,10,26–28
The timing of highly effective
treatment initiation impacts outcomes. Early initiation
delays EDSS progression compared to escalation
strategies.
8
According to data from the international
MSBase and Swedish MS registry, 10 years after
treatment onset, patients with an early switch to
highly effective treatment had an almost stable
mean EDSS score, while late switchers showed
EDSS worsening of +1.4 and a three-fold increase
in the proportion of immobile patients (EDSS ≥7).
9
Likewise, the present model showed almost stable
EDSS scores and lower proportions of immobile
patients in the immediate and early OMB groups
after 10 years compared to late and no switch scen-
arios. Hence, the results of He et al.
9
underline the
robustness of the model outcomes and indicate that
results on immediate or early OMB treatment are
similar to real-world settings. Furthermore, the
results of He et al.
9
highlight that an early switch is
a relevant scenario in clinical practice. Although sup-
ported by the Multiple Sclerosis Therapy Consensus
Group,
29
an immediate use of highly effective
DMTs is still linked to a highly active disease
course and poor prognosis in current treatment recom-
mendations.
5,6
For example, the German S2k guide-
line, which had been revised in May 2021,
recommendsaswitchstrategytohighlyeffective
DMTs including anti-CD20 antibodies after initial
standard treatment.
6
Consequently, with early
switches being superior to late switches in the
present simulation and as long as immediate high
efficacious therapy has not yet been established,
Figure 3. Sensitivity analysis base-scenario: 10 years OMB vs. 10 years DMF (A); 10 years OMB vs. 10 years GA (B);
6-CDP, 6-month confirmed disability progression; DMF, Dimethyl fumarate; EDSS, Expanded Disability Status Scale; GA,
Glatiramer acetate; HR, Hazards ratio; OMB, Ofatumumab.
Koeditz et al.
www.sagepub.com/msjetc 9
early switch scenarios will be relevant in clinical
practice.
In our model, the lowest number of DALYs were esti-
mated in the immediate OMB cohort. Differences in
DALYs between the scenarios were driven by
YLDs. No differences were found with regard to
YLL, which might be explained by a low mortality
ratio of 1.7 used in the model for all EDSS states.
23
The lower number of DALYs in the immediate
OMB and the early switch cohorts were associated
with lower EDSS states. This is consistent with a
DALY-based estimate of disease burden in Swiss
MS patients, in which patients with an EDSS score
<4 (68.4% of the total MS population) contributed
only 39.8% to the total MS-specific YLD.
30
The estimated number of relapses and the
relapse-related costs in the model were lower in the
immediate OMB and early switch cohorts than in
the late and no switch cohorts. As two thirds of
relapse costs can be attributed to indirect costs,
31
relapse-related absenteeism, early retirement and
invalidity also need consideration. The model
revealed the potential of immediate or early OMB
treatment to reduce societal burden through better
productivity. Furthermore, the model clearly shows
that higher DMT costs can be offset when accounting
for direct and indirect costs.
The present simulation showed considerable effects
on clinical and productivity outcomes of immediate
or early treatment with OMB within 10 years.
Long-term economic analyses suggest that the benefi-
cial effects will increase over a time horizon of 20
years or more.
32–34
With increasing disease duration,
informal care, inpatient care, and long-term absentee-
ism become more important due to accumulation of
disability. Consequently, the share of drug costs in
the total cost assumption will be reduced. It can be
expected that over several decades, an early OMB ini-
tiation strategy might become both clinically and eco-
nomically superior compared to prolonged standard
DMT.
The Markov model used was EDSS-based, which
bears some limitations. The EDSS focusses on func-
tional mobility and is insensitive to impairments
such as cognition.
35
Nevertheless, no composite mea-
sures were used, as an EDSS-based definition delivers
reproducible results while being less complex.
Inherent limitations of Markov models are constant
transition probabilities for each cycle and constant
efficacy parameters regardless of individual disease
course. As this applies to all cohorts, a bias is not
expected. The model might underestimate small
changes as it used integer EDSS values for modeling
tractability and consistency with published literature.
As the CCA uses data from various sources, differ-
ences between underlying studies bear further limita-
tions. For example, input data on transition
probabilities are based on a longitudinal dataset
from 1980–1995 and may be outdated. Efficacy data
had to be derived from a NMA with adjusted out-
comes and short study periods due to a lack of
direct comparative data. However, the study popula-
tions in the NMA were sufficiently similar to allow
for indirect comparison and sufficiently represent
the cohort of interest to allow for application in the
model. Due to remaining uncertainties of the indirect
approach, it remains unclear, whether the observed
small differences between the immediate OMB
cohort and the early switch scenario will translate
into relevant differences in clinical practice.
Nevertheless, the considerable differences between
estimates for immediate or early OMB and late or
no switch cohorts allow the assumption of relevant
differences in practice. Probabilities for DMT discon-
tinuation and a possible decrease in effectiveness
were not imputed due to a lack of adequate long-term
data. This might explain discrepancies between the
outcomes reported by He et al.
9
and our model esti-
mates. Furthermore, the magnitude of difference in
proportion of patients in different EDSS states is
influenced by the baseline EDSS distribution of
patients. The model included RMS patients only
while the cost inputs from Flachenecker et al.
3
included data of primary progressive MS (PPMS)
patients. This bias is assumed to be negligible
because differences between RMS and PPMS are
mainly based on DMT costs, which are calculated
separately. In addition, cost input data were based
on patients mainly on mildly/moderately efficacious
DMTs and thus an overestimation of costs for patients
on highly efficacious drugs is possible.
3
In conclusion, this simulation indicates that immedi-
ate OMB treatment or an early switch to OMB
results in an overall better health state and higher
productivity over 10 years than a late (after 5 years)
or no switch from standard DMTs. The clinical
benefit of immediate and early OMB treatment
together with the approximate cost neutrality from a
societal perspective was demonstrated. While
medical and patient-related reasons are the main
drivers for treatment decisions, from the payer per-
spective cost neutrality in the long-term becomes rele-
vant. It can be assumed that immediate or early
Multiple Sclerosis Journal—Experimental, Translational and Clinical
10 www.sagepub.com/msjetc
treatment with highly effective DMTs improves the
disease course without causing additional costs and
should be considered in RMS patients.
Acknowledgements
Medical writing support was provided by Karin Eichele
(mediwiz) and Angelika Schedel (Schedel Medical
Communication). Medical Writing support was funded by
Novartis Pharma GmbH.
Declaration of conflicting interests
The author(s) declared the following potential conflicts of
interest with respect to the research, authorship, and/or pub-
lication of this article: D. Köditz was a fellow of Novartis
Pharma GmbH at the time the research was conducted
and received funding for his services from Novartis
Pharma GmbH. J. Frensch, M. Bierbaum, N.-H. Ness,
B. Ettle, U. Vudumula, K. Gudala, N. Adlard and
S. Tiwari are salaried employees of Novartis Pharma AG
and its subsidiaries. T. Ziemssen has received personal com-
pensation for participating on advisory boards, trial steering
committees, and data and safety monitoring committees, as
well as for scientific talks and project support from: Bayer
HealthCare, Biogen, Celgene, Genzyme, Merck, Novartis,
Roche, Sanofi, and Teva.
Funding
The author(s) disclosed receipt of the following financial
support for the research, authorship, and/or publication of
this article: This work was supported by the Novartis
Pharma GmbH.
ORCID iDs
Martin Bierbaum https://orcid.org/0000-0003-3708-
0182
Tjalf Ziemssen https://orcid.org/0000-0001-8799-8202
Supplemental material
Supplemental material for this article is available online.
References
1. Kip M and Zimmermann A Krankheitsbild Multiple
Sklerose. In: Kip M, Schoenfelder T and Bless H
(eds) Weißbuch Multiple Sklerose in Deutschland. 1st
ed. Springer Berlin Heidelberg, 2016.
2. Kobelt G, Thompson A, Berg J, et al. New insights into
the burden and costs of multiple sclerosis in Europe.
Mult Scler 2017; 23: 1123–1136.
3. Flachenecker P, Kobelt G, , Berg J, et al. New insights
into the burden and costs of multiple sclerosis in
Europe: results for Germany. Mult Scler 2017;
23(2_suppl): 78–90.
4. Kip M and Wiendl H. Therapie der Multiplen Sklerose.
In: Kip M, Schoenfelder T and Bless HH (eds)
Weißbuch Multiple Sklerose in Deutschland. 1st ed.
Springer Berlin Heidelberg, 2016.
5. Montalban X, Gold R, Thompson AJ, et al. ECTRIMS/
EAN guideline on the pharmacological treatment of
people with multiple sclerosis. Mult Scler 2018; 24:
96–120.
6. Hemmer B, Bayas A, Berthele A, et al. Diagnose und
Therapie der Multiplen Sklerose, Neuromyelitis-optica-
Spektrum-Erkrankungen und MOG-IgG-assoziierten
Erkrankungen, S2k-Leitlinie. Leitlinien für Diagnostik
und Therapie in der Neurologie: Deutsche Gesellschaft
für Neurologie. 2021.
7. Brown JWL, Coles A, Horakova D, et al. Association
of initial disease-modifying therapy with later conver-
sion to secondary progressive multiple sclerosis.
JAMA 2019; 321: 175–187.
8. Harding K, Williams O, Willis M, et al. Clinical out-
comes of escalation vs early intensive disease-
modifying therapy in patients with multiple sclerosis.
JAMA Neurol 2019; 76: 536–541.
9. He A, Merkel B, Brown JWL, et al. Timing of high-
efficacy therapy for multiple sclerosis: a retrospective
observational cohort study. Lancet Neurol 2020; 19:
307–316.
10. Buron MD, Chalmer TA, Sellebjerg F, et al. Initial
high-efficacy disease-modifying therapy in multiple
sclerosis: a nationwide cohort study. Neurology 2020;
95: e1041–e51.
11. Ziemssen T, Derfuss T, de Stefano N, et al. Optimizing
treatment success in multiple sclerosis. J Neurol 2016;
263: 1053–1065.
12. Bar-Or A, Grove RA, Austin DJ, et al. Subcutaneous
ofatumumab in patients with relapsing-remitting mul-
tiple sclerosis: the MIRROR study. Neurology 2018;
90: e1805–e14.
13. Genovese MC, Kaine JL, Lowenstein MB, et al.
Ocrelizumab, a humanized anti-CD20 monoclonal anti-
body, in the treatment of patients with rheumatoid arthritis:
a phase I/II randomized, blinded, placebo-controlled,
dose-ranging study. Arthritis Rheum 2008; 58:
2652–2661.
14. Hauser SL, Bar-Or A, Cohen JA, et al. Ofatumumab
versus teriflunomide in multiple sclerosis. N Engl J
Med 2020; 383: 546–557.
15. Hauser SL, Bar-Or A, Comi G, et al. Ocrelizumab
versus interferon beta-1a in relapsing multiple sclerosis.
N Engl J Med 2017; 376: 221–234.
16. Gartner J, Hauser S, Bar-Or A, et al. MSVirtual 2020—
poster abstracts. P0192. Benefit-risk of ofatumumab in
treatment-naïve early relapsing multiple sclerosis
patients. Mult Scler 2020; 26(3_suppl): 118–659.
17. FDA. Drugs@FDA: FDA-Approved Drugs. Biologic
License Application (BLA): 125326 2020 [updated
20.08.2020]. [last accessed 14.01.2022]https://www.
accessdata.fda.gov/scripts/cder/daf/index.cfm?event=
overview.process&ApplNo=125326.
18. EMA. Kesimpta. Ofatumumab 2021 [updated
12.05.2021, https://www.ema.europa.eu/en/medicines/
human/EPAR/kesimpta.
Koeditz et al.
www.sagepub.com/msjetc 11
19. Ness NH, Haase R, Kern R, et al. The multiple sclerosis
health resource utilization survey (MS-HRS): develop-
ment and validation study. J Med Internet Res 2020; 22:
e17921.
20. Mauskopf JA, Paul JE, Grant DM, et al. The role of
cost-consequence analysis in healthcare decision-
making. Pharmacoeconomics 1998; 13: 277–288.
21. Samjoo IA, Worthington E, Drudge C, et al.
Comparison of ofatumumab and other disease-modifying
therapies for relapsing multiple sclerosis: a network
meta-analysis. JCompEffRes2020; 9: 1255–1274.
22. Statistisches Bundesamt. Sterbetafeln: Ergebnisse aus
der laufenden Berechnung von Periodensterbetafeln
für Deutschland und die Bundesländer: 2017/2019.2020,
https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/
Bevoelkerung/Sterbefaelle-Lebenserwartung/_inhalt.html
(accessed 14 October 2020).
23. Jick SS, Li L, Falcone GJ, et al. Mortality of patients
with multiple sclerosis: a cohort study in UK primary
care. J Neurol 2014; 261: 1508–1517.
24. Ness NH, Schriefer D, Haase R, et al. Real-world evi-
dence on the societal economic relapse costs in patients
with multiple sclerosis. Pharmacoeconomics 2020; 38:
883–892.
25. Schriefer D, Ness NH, Haase R, et al. Gender dispar-
ities in health resource utilization in patients with
relapsing-remitting multiple sclerosis: a prospective
longitudinal real-world study with more than 2000
patients. Ther Adv Neurol Disord 2020; 13:
1756286420960274.
26. Hutchinson M, Kappos L, Calabresi PA, et al. The effi-
cacy of natalizumab in patients with relapsing multiple
sclerosis: subgroup analyses of AFFIRM and
SENTINEL. J Neurol 2009; 256: 405–415.
27. Cohen JA, Barkhof F, Comi G, et al. Oral fingolimod or
intramuscular interferon for relapsing multiple scler-
osis. N Engl J Med 2010; 362: 402–415.
28. Coles AJ, Compston DA, Selmaj KW, et al.
Alemtuzumab vs. interferon beta-1a in early multiple
sclerosis. N Engl J Med 2008; 359: 1786–1801.
29. Wiendl H, Gold R, Berger T, et al. Multiple sclerosis
therapy consensus group (MSTCG): position statement
on disease-modifying therapies for multiple sclerosis
(white paper). Ther Adv Neurol Disord 2021; 14:
17562864211039648.
30. Kaufmann M, Puhan MA, Salmen A, et al. 60/30: 60%
of the morbidity-associated multiple sclerosis disease
burden comes from the 30% of persons with higher
impairments. Front Neurol 2020; 11: 156.
31. Ness NH, Schriefer D, Haase R, et al. Differentiating
societal costs of disability worsening in multiple scler-
osis. J Neurol 2020; 267: 1035–1042.
32. Frasco MA, Shih T, Incerti D, et al. Incremental net
monetary benefit of ocrelizumab relative to subcutane-
ous interferon β-1a. J Med Econ 2017; 20: 1074–1082.
33. Furneri G, Santoni L, Ricella C, et al.
Cost-effectiveness analysis of escalating to natalizumab
or switching among immunomodulators in
relapsing-remitting multiple sclerosis in Italy. BMC
Health Serv Res 2019; 19: 436.
34. Yang H, Duchesneau E, Foster R, et al.
Cost-effectiveness analysis of ocrelizumab versus sub-
cutaneous interferon beta-1a for the treatment of relaps-
ing multiple sclerosis. J Med Econ 2017; 20: 1056–
1065.
35. Inojosa H, Schriefer D and Ziemssen T. Clinical
outcome measures in multiple sclerosis: a review.
Autoimmun Rev 2020; 19: 102512.
Multiple Sclerosis Journal—Experimental, Translational and Clinical
12 www.sagepub.com/msjetc