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A Study Validating Changes in the Multiple Sclerosis Functional Composite
Erwin L. J. Hoogervorst, MD;
Nynke F. Kalkers, MD;
Bernard M. J. Uitdehaag, MD;
Chris H. Polman, MD
Arch Neurol. 2002;59:113-116.
ABSTRACT
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Objective To prospectively characterize the relation between 1-year changes in
neurologist ratings of abnormalities as measured by means of the Expanded
Disability Status Scale (EDSS) and changes in observations of functional impairment
as measured by means of the Multiple Sclerosis Functional Composite (MSFC)
in the clinical assessment of multiple sclerosis (MS).
Methods One hundred twenty patients with MS were recruited at our outpatient
clinic. Impairment and disability at baseline and follow-up were assessed
using the EDSS and MSFC. We studied correlations between change ( )
in the EDSS, MSFC, and MSFC components for the total population and different
subgroups and analyzed the contribution of change in MSFC components to change
in the EDSS and MSFC.
Results Median EDSS score at baseline was 4.5; at follow-up, 5.0. Mean MSFC
score at baseline was -0.00; at follow-up, -0.04. Good cross-sectional
correlations were found between the EDSS and MSFC at baseline (-0.72)
and follow-up (-0.73). Only weak correlations were found between EDSS
and MSFC. Although EDSS showed the strongest correlations with
change in leg function and weak or no correlation with change in cognitive
function or arm function, MSFC showed the highest correlation with
change in arm function and cognitive function.
Conclusion Our longitudinal data indicate that the MSFC reflects change from different
dimensions of neurologic functions, which is a favorable characteristic when
compared with the EDSS.
INTRODUCTION
NEUROLOGIC impairment and disability in patients with multiple sclerosis
(MS) can be measured in several ways. The often-used primary outcome measure
in clinical trials is the Expanded Disability Status Scale (EDSS).1 The EDSS ranges from 0 (normal) to 10 (death due to
MS), based on results of a neurologic examination of 8 functional systems
(visual, brainstem, sensory, cerebellar, sphincter, cerebral, and others)
and the ability of patients to walk. The EDSS, however, fails to fulfill requirements
for a reliable outcome measure. The major problems are related to standardization,
resulting in suboptimal interrater reliability, marginal sensitivity to change,
and bias toward locomotor function.2-5
Some of these problems are related to the fact that the EDSS is an ordinal
scale.
The Multiple Sclerosis Functional Composite (MSFC) was introduced recently
as an alternative to the available MS clinical rating scales.6-8
The MSFC is a clinical outcome measure that includes quantitative tests of
arm and hand function (9-hole peg test [9-HPT]), cognitive function (3-second
version of the Paced Auditory Serial Addition Test [PASAT]), and leg function
and ambulation (7.62-m Timed Walk Test [TWT]). At development, quantitative
tests were assumed to be more sensitive to change over time than traditional
ordinal measures.
Previous studies from our center performed cross-sectional comparisons
between the EDSS and MSFC.9-10
In these studies, good correlations were shown between the scales, mainly
because of the importance of spinal cord–related neurologic functions,
and the construct validity of the MSFC was confirmed and extended in different
subgroups of MS.
To our knowledge, only 2 studies have reported data on longitudinal
measurements of the MSFC. Cutter et al6 showed
correlations between changes in the MSFC and EDSS, and Fisher et al11 showed correlations between changes in the MSFC and
brain parenchymal fraction.
The aim of the current study was to prospectively characterize the relation
between 1-year change in neurologist rating of neurologic abnormalities as
measured by means of the EDSS and change in observations of functional impairment
as measured by means of the MSFC. More specifically, we studied correlations
among changes () in the EDSS, MSFC, and MSFC components for a population
of patients with MS and for different subgroups. We also analyzed the contribution
of MSFC components to EDSS and MSFC scores.
PATIENTS AND METHODS
PATIENTS
One hundred twenty patients with MS12
were recruited at our outpatient clinic to undergo longitudinal examinations
using the EDSS and MSFC. Diagnoses included relapsing-remitting (n = 40),
secondary progressive (n = 37), and primary progressive (n = 43) MS.13 The group was also stratified by disability strata,
on the basis of whether the EDSS score was mainly derived from the underlying
functional systems or from ambulatory function, as mildly disabled (baseline
EDSS score,  4.0 [n = 57]) and more disabled (baseline EDSS score, >4.0
[n = 63]).
TEST PROCEDURES
Patients underwent EDSS and MSFC examinations at baseline and after
1 year to assess impairment and disability. Data from the EDSS and MSFC were
collected in the same visit under carefully standardized conditions by well-trained
physicians (including E.L.J.H. and N.F.K.), as described previously.9-10,14 Full assessment of
both tests required 30 to 40 minutes (15-20 minutes for the EDSS and 15-20
minutes for the MSFC). Inability to perform a test of the MSFC because of
MS-related symptoms was scored with the maximum time allowed for the 9-HPT
(300 seconds) and TWT (180 seconds) and with the worst possible score for
the PASAT (0). If patients refused to participate in a test, results were
scored as missing.
ANALYSIS
To calculate the MSFC score, z scores were
created for the 9-HPT, PASAT, and TWT.6 These z scores were obtained using means and SDs of an external
reference population consisting of a wide range of patients with MS.9 The composite score was calculated by adding the z scores and dividing the sum by 3, as seen in the following
equation15:
The MSFC score becomes higher when patients have better scores and lower
when patients have worse scores on the MSFC components compared with the reference
population.
Results were analyzed in several ways. We studied cross-sectional correlations
between baseline EDSS and MSFC scores and between follow-up EDSS and MSFC
scores, and longitudinal correlations among EDSS, MSFC, and
changes in MSFC components (9-HPT, PASAT, and TWT) for
the total population and for the different disability strata and subtypes
of MS. For change in MSFC components, we used the relative change in actual
measurements of 9-HPT, PASAT, and TWT.
Since this analysis incorrectly assumes that the EDSS is a continuous
variable, we also studied the total number of patients showing significant
change on the EDSS by quartile of change on the MSFC. A significant change
on the EDSS was defined as a change of 1.0 point or more at EDSS levels of
less than 5.5, or a change of 0.5 point or more at EDSS levels of at least
5.5.16 Quartiles of change were defined by
the amount of change in the MSFC.
STATISTICS
Cross-sectional correlations between EDSS and MSFC scores at baseline
and follow-up and correlations between EDSS, MSFC, and MSFC
components were calculated using the Spearman rank correlation coefficient
(r). We considered P values
of less than .01 as significant and P values of less
than .05 as a trend only. We analyzed the contribution of 9-HPT, PASAT,
and TWT for EDSS and MSFC in the total population by
using a stepwise multiple linear regression method (P
to enter .05), with EDSS or MSFC as the dependent variable and
the changes in the MSFC components as predictors.
RESULTS
Patient characteristics and scores on the EDSS and MSFC at baseline
and follow-up are summarized in Table 1 for the total population, different MS subtypes, and disability
strata. Mean age at baseline was 47.1 years (SD, 12.1 years); 37% of the patients
were male and 63% were female. Average time from baseline to follow-up measurement
was 1.1 years (SD, 0.2 year). Data were incomplete for 5 patients who refused
to undergo the PASAT and 2 patients who refused to undergo the TWT.
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Table 1. Patient Characteristics*
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The EDSS showed a bimodal distribution in the total population, with
EDSS baseline peak scores of 4.0 and 6.5 and follow-up peak scores of 4.0
and 6.0. Median EDSS score at baseline was 4.5; at follow-up, 5.0. Mean MSFC
score at baseline was -0.00; at follow-up, -0.04.
Cross-sectional correlations between EDSS and MSFC scores at baseline
(r = -0.72; P<.01)
and follow-up (r = -0.73; P<.01) were strong. Correlations were also found between EDSS
and MSFC for the total population and for the more disabled patients;
these correlations, however, were weak and not statistically significant (Table 2).
Figure 1 shows the number
of patients with a significant EDSS by quartile of MSFC. The
first quartile of MSFC contains patients in whom the MSFC score worsened
most in 1 year (MSFC, -0.16); the second quartile, MSFC
from greater than -0.16 to -0.014; the third quartile, MSFC
from greater than -0.014 to 0.14; and the fourth quartile, MSFC
improved most in 1 year (MSFC score increased >0.14). In total, 30 patients
showed a significant worsening and 19 patients a significant improvement in
EDSS score.
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Number of patients showing significant change in the Expanded Disability
Status Scale (EDSS) by quartile of change in the Multiple Sclerosis Functional
Composite (MSFC). In the first MSFC quartile (most worsening), more patients
show worsening than improvement on the EDSS, whereas in the last MSFC quartile
(most improvement), more patients show EDSS improvement.
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Table 2 shows correlations
of EDSS with MSFC, 9-HPT, PASAT, and TWT
for the total population, different MS subtypes, and disability strata. No
significant correlation was found between EDSS and PASAT, and
only a trend was found between EDSS and 9-HPT. Moderate correlations
were found between EDSS and TWT for the total population (r = -0.39), the different disability strata (mild, r = -0.39; more disability, r
= -0.48), relapsing-remitting subtype (r = -0.53),
and primary progressive subtype (r = -0.44).
Table 3 shows the correlations
of MSFC with its components for the total population and different
subgroups. Correlations were strong with 9-HPT in the total population
(r = 0.65), both disability strata (mild, r = 0.71; more disability, r = 0.62), relapsing-remitting
subtype (r = 0.74), and secondary progressive subtype
(r = 0.65). Significant correlations of PASAT
with MSFC were seen in all subpopulations. For the TWT only, significant
correlations were found for both progressive MS subtypes and more disabled
patients. No significant correlations were found in mildly disabled patients
or the relapsing-remitting MS subtype.
Stepwise multiple linear regression analysis using EDSS as the
dependent variable and 9-HPT, PASAT, and TWT as independent
variables showed no valuable contribution for predicting EDSS (data
not shown).
When using MSFC as the dependent variable, PASAT disclosed
the most valuable predictor for MSFC (adjusted R2 = 0.13); when 9-HPT was also included, the adjusted R2 was 0.23. No valuable contribution of TWT
was seen for predicting the MSFC.
COMMENT
To our knowledge, only one other study has reported on the relation
between MSFC and EDSS scores. That study was retrospective and
based on compiled data sets from different sources.6
Our prospective study demonstrates the concurrent validity of 1-year MSFC
by comparing it with EDSS. In addition, we tried to understand the
background of the MSFC and EDSS by relating them to changes
in the actual measurements of cognition, arm function, and leg function that
form the basis of the MSFC.
Analysis of the number of patients showing a significant EDSS
by quartiles of MSFC showed that patients in the lowest quartile (most
MSFC worsening) were about 2 times more likely (11 vs 6 patients) to have
a significant worsening on the EDSS and 2 to 3 times less likely (3 vs 8 patients)
to have a significant improvement on the EDSS when compared with patients
in the highest MSFC quartile (most MSFC improvement).
Our finding on longitudinal MSFC is, to our knowledge, the first
independent and prospective confirmation of the observations in the original
data by Cutter et al.6 The Spearman rank correlation
coefficient between MSFC and EDSS is also very comparable in
both studies (r = 0.24 vs r
= -0.22), although indicative of only a weak correlation between the
changes in both measures.
Our study clearly indicates why this correlation is weak. Although EDSS
is especially correlated to changes in leg function (and not or marginally
to changes in cognition and arm function), MSFC is strongly correlated
to changes in arm function and cognition and to a lesser degree—in patients
with greater disability or in the progressive phase of the disease—to
change in ambulatory function.
The correlation found between EDSS and TWT is in line
with the fact that the EDSS is heavily biased to locomotor function.3, 5 Our data do not show any correlation
between EDSS and PASAT, which is in line with previous findings9 that results of a cognition test (PASAT) do not contribute
to the EDSS. Our correlation between EDSS and 9-HPT (r = -0.24) is comparable to that reported by Cutter et al6 (r = 0.27).
Correlations between MSFC and changes in the underlying measurements
were not reported in the study by Cutter et al.6
However, in that report, the correlations between MSFC and EDSS
are somewhat better in more disabled patients.
These longitudinal data confirm the impression obtained from previous
cross-sectional studies that the MSFC has favorable characteristics, especially
being more multidimensional, when compared with the EDSS. Before proposing
the MSFC as the preferred outcome measure for clinical trials, however, we
advocate that more of its characteristics, including sensitivity to change
and differential weighting of changes in actual measurements on z scores, be prospectively investigated in larger cohorts of patients
with a wide range of disability.
AUTHOR INFORMATION
Accepted for publication August 28, 2001.
Author Contributions: Study concept and
design (Drs Hoogervorst, Kalkers, Uitdehaag, and Polman); acquistion
of data (Drs Hoogervorst and Kalkers); analysis and interpretation
of data (Drs Hoogervorst, Kalkers, Uitdehaag, and Polman); drafting
of the manuscript (Drs Hoogervorst and Kalkers); critical revision
of the manuscript for important intellectual content (Drs Hoogervorst,
Kalkers, Uitdehaag, and Polman); statistical expertise (Drs Hoogervorst,
Kalkers, and Uitdehaag); study supervision (Drs Uitdehaag and
Polman).
This study was partially sponsored by a research grant from Biogen Inc,
Cambridge, Mass.
We thank M. Judith Eikelenboom, MD, and Lisa M. L. van Winsen, MD, for
their help examining patients.
Corresponding author and reprints: Erwin L. J. Hoogervorst, MD, VU
Medical Center, Department of Neurology, PO Box 7057, 1007 MB Amsterdam, the
Netherlands(e-mail: e.hoogervorst{at}vumc.nl).
From the Departments of Neurology (Drs Hoogervorst, Kalkers, Uitdehaag,
and Polman) and Clinical Epidemiology and Biostatistics (Dr Uitdehaag), Vrije
Universiteit Medical Center, Amsterdam, the Netherlands.
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