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EXTENDED REPORT
A disease activity score for polym yalgia rheumatica
B F Leeb, H A Bird
...............................................................................................................................
See end of article for
authors’ affiliations
.......................
Correspondence to:
Dr B F Leeb, 2nd
Department of Medicine,
Lower Austrian Centre for
Rheumatology,
Endocrinology,
Humanisklinikum Lower
Austria, A-2000
Stockerau, Landstrasse 18,
Austria;
leeb.khstockerau@
aon.at
Accepted
13 November 2003
.......................
Ann Rheum Dis 2004;63:1279–1283. doi: 10.1136/ard.2003.011379
Objective: To develop a composite score for measurement of disease activity in polymyalgia rheumatica
(PMR) and assess its internal and external validity.
Methods: A PMR activity score (AS) was designed and assessed for internal and external validity in two
patient cohorts: 57 international patients evaluated primarily for development of the PMR-AS at baseline,
weeks 4 and 24; and for validation, 24 Austrian patients assessed at baseline, week 4, and at a mean
(SD) point of week 33.6 (24.5). The PMR-AS was calculated as: CRP (mg/dl)+VAS p (0–10)+VAS ph
(0–10)+(MST (min)60.1)+EUL (3–0); Cronbach’s a was calculated. Factor analysis by linear regression
was applied, and responses calculated on the basis of the PMR response criteria and the PMR-AS applied.
PMR-AS values at different times were compared by paired t tests.
Results: Cronbach’s a for the composite score was 0.91 and 0.88 in the two cohorts. Factor analysis
showed that each single item contributed significantly to the total score and the relative weight of each item
in both cohorts was equally distributed. Mean PMR-AS at baseline was 27.54 and 28.72, respectively, at
week 4, 5.99 and 8.99, and at the final visit 5.35 and 5.92 (NS). PMR-AS values at baseline and at later
visits were significantly different (p,0.0001). PMR-AS values ,7 indicated low disease activity, 7–17
medium disease activity, and .17 high PMR activity. In a third control cohort the PMR-AS correlated
highly with patient’s global assessment, patient satisfaction, and ESR (p,0.001).
Conclusion: The PMR-AS provides an easily applicable and valid tool for monitoring disease activity, and
in combination with the PMR response criteria provides a better description of response.
P
olymyalgia rheumatica (PMR) is a common rheumatic
disorder in the elderly population, often underestimated,
affecting from 0.1 to 0.5% of over 50 year olds. However,
it may also occur in younger people, but the incidence is
lower.
1–3
Diagnosis is based upon a clinical syndrome,
consisting of pain and stiffness in the shoulder and pelvic
girdle, muscle tenderness of the arms and legs, non-specific
somatic complaints, frequently occurring fever, weight loss,
and fatigue. The acute phase response measured by erythro-
cyte sedimentation rate (ESR) and C reactive protein (CRP) is
frequently greatly increased.
1
However, PMR may also exist
with a low ESR and CRP. Whether a low acute phase
response indicates lesser severity and better prognosis is not
yet confirmed.
45
Up to now four proposals for diagnostic
criteria have been published and recently evaluated for their
validity (paper in preparation).
6–10
Monitoring and recording
disease activity in daily practice needs to be easy to perform
and not time consuming. Moreover, it should provide the
physician with enough information to enable decisions to be
made about treatment.
We have recently proposed the first response criteria for
PMR, reflecting the change of the patient’s situation from
baseline.
11
These response criteria are based on a core set of
five variables, comprising a change in the visual analogue
scale for pain (VAS p), which is obligatory, and four other
variables—namely, the visual analogue scale for physician’s
assessment (VAS ph), the ability to elevate the upper limbs
(EUL), morning stiffness (MST), and the acute phase
response, expressed by CRP or the ESR (mm/1st h), from
which the best performing three are used. The acute phase
measurements and MST have been shown to be disease
activity measures which are independent of pain. VAS ph was
included as the only measure independent of the patient, and
EUL to cover functional status, although it was shown to be
slightly pain dependent.
Recently, a simplified disease activity index (SDAI) for
rheumatoid arthritis (RA) has been described, consisting of
five items—namely, the number of swollen and tender joints,
patient’s global assessment expressed by a VAS, physician’s
global assessment also expressed by a VAS, and CRP (mg/dl),
which are simply summed.
12
This disease activity score has
been proved to correlate with the classical 28 joint disease
activity score (DAS28)
13
in RA and also reflects the American
College of Rheumatology (ACR) response.
Criteria based on percentage changes from baseline may
cause difficulties in daily practice, as is known from the ACR
response criteria for RA,
14
and therefore we considered it
useful to develop a simple disease activity index for PMR.
Such an index, providing an absolute number to reflect
disease activity, would enable comparison of patients and
avoid the need for a baseline observation to assess the actual
activity of a patient’s disease.
Based on the core set of parameters of the PMR response
criteria, on the one hand, and taking the SDAI as a model, on
the other, we developed an easily calculated disease activity
index for PMR, the PMR-AS.
PATIENTS AND METHODS
The PMR-AS was assessed for internal and external validity
in the patient cohorts who were evaluated for the develop-
ment of the PMR response criteria. Fifty seven of the 76
patients from the international patient cohort included in the
evaluation of the PMR response criteria could be followed up
for 24 weeks. These patients were chosen for the develop-
ment of the PMR-AS. As in the PMR response criteria
evaluation they were analysed at baseline, week 4, and week
24. To validate the results achieved in the original 57 patients
Abbreviations: ACR, American College of Rheumatology; CRP, C
reactive protein; DAS28, 28 joint disease activity score; ESR, erythrocyte
sedimentation rate; EUL, elevation of the upper limbs; MST, morning
stiffness; PMR, polymyalgia rheumatica; PMR-AS, polymyalgia
rheumatica activity score; RA, rheumatoid arthritis; SDAI, simplified
disease activity index; VAS p, visual analogue scale for pain; VAS ph,
visual analogue scale for physician’s assessment
1279
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an Austrian patient cohort comprising 24 patients, recruited
from the Lower Austrian Centre of Rheumatology, was
assessed. This cohort was evaluated at baseline, week 4 and
at a mean (SD) point of week 33.6 (24.5). Table 1 shows the
demographic and baseline disease activity data.
In all these patients four existing diagnostic criteria sets
were applied, as all these patients took part in the European
diagnostic criteria evaluation study. The Bird/Wood (1979)
criteria performed best in identifying patients considered
to have PMR by experienced investigators from across
Europe.
Based on the proposed diagnostic criteria and the exclusion
criteria, described previously, PMR was finally diagnosed
by an experienced clinician. Drugs other than cortico-
steroids and non-steroidal anti-inflammatory drugs were
not allowed for the treatment of PMR during the observation
period.
The development of the core set of parameters of the PMR
response criteria has been described in detail previously. As
the parameters of the core set of the PMR response criteria
had already proved their sensitivity to change during the
primary evaluation, they were considered to be part of the
disease activity index also. To provide easy applicability given
by a simple formula, on the one hand, and taking the SDAI
for RA as a model, on the other, we decided to sum the
parameters as follows:
CRP (mg/dl)+VAS p (0–10)+VAS ph (0–10)+
(MST (min)60.1)+EUL (3–0)
Thus as can be seen the PMR-AS results from the addition
of five items and one simple multiplication, which can be
done easily. In contrast with the PMR response criteria the
EUL was assessed the other way round (3 = none, 2 = below
shoulder girdle, 1 = up to shoulder girdle, 0 = above shoulder
girdle). For reasons of weighting MST was multiplied by 0.1.
For validation purposes the PMR-AS was then applied to
53 regular outpatients (36 female, 17 male; mean (SD) age
67.3 (10.7) years), resulting in 64 measurements. In this
cohort patients rated their satisfaction from 1 (excellent) to 5
(unbearable); moreover, patient’s global assessment was
determined by using a VAS and the ESR (mm/1st h) was
measured. The PMR-AS was then correlated with the other
parameters to see whether it reflected disease activity and
patient satisfaction accurately enough. Patient’s global
assessment and the ESR can be regarded as the standard of
disease activity monitoring in PMR up to now, and patient
satisfaction should be taken into consideration to enable
decision about treatment to be made.
Statistical analysis
Internal consistency of the composite score was primarily
assessed by calculating Cronbach’s a—a numerical coeffi-
cient of reliability. Values .0.7 are considered to be a marker
of high reliability.
15
The amount contributed by each single
item to the composite score was evaluated by calculating
correlation coefficients. Regression analysis between the
percentage responses calculated on the basis of the PMR
response criteria and the PMR-AS was applied. As the PMR-
AS was seen to be normally distributed in all patient cohorts
investigated, by applying the Kolmogorov-Smirnov accom-
modation, changes of the PMR-AS were evaluated by paired t
tests. Unpaired t tests were used to compare the two patient
cohorts. At the different times of evaluation a 95% confidence
interval for the PMR-AS was calculated. Moreover, correla-
tion and linear regression analysis was performed between
the PMR-AS and ESR, VAS for patient’s global assessment,
and patient satisfaction, respectively, in the third patient
cohort.
Disease activity was categorised as high, medium, and low
by calculating means of the PMR-AS at baseline, in patients
Table 1 Demographic data and baseline values, mean (SD), for the measures of the core set of the international and the
Austrian patient cohort
No Age F/M
CRP VAS p VAS ph MST EUL
PMR-AS(mg/dl) (0–10) (0–10) (min) (3–0)
International cohort 57 69.3 (51–92) 51/6 4.7 (5.0) 6.9 (2.9) 6.4 (2.9) 82.5 (78.9) 1.2 (0.6) 27.5 (12.5)
Austrian cohort 24 71.0 (52–85) 17/7 5.5 (3.3) 7.0 (1.1) 6.9 (1.3) 82.7 (44.8) 1.4 (0.3) 29.1 (6.5)
Table 2 Correlation coefficients between the single items and the total score as well as
Cronbach’s a for the PMR-AS in the international and Austrian patient cohorts
CRP VAS p VAS ph MST EUL) PMR-AS
(mg/dl) (0–10) (0–10) (min) (3–0 (Cronbach’s a)
International cohort 7.83 0.90 0.91 0.88 0.78 0.91
Austrian cohort 7.67 0.87 0.92 0.81 0.69 0.88
Figure 1 Single PMR-AS courses in the international and Austrian
patients.
1280 Leeb, Bird
www.annrheumdis.com
with 20% and 50% response, and in patients with 70% and
90% response according to the PMR response criteria,
respectively.
RESULTS
No major differences in the demographic data were seen
between the two patient cohorts, except that the Austrian
cohort contained a higher proportion of men.
Cronbach’s a for the composite score in the international
cohort was 0.91, based on an average inter-item correlation of
0.68. For the Austrian patient cohort it was 0.88 (average
inter-item correlation 0.60). Values .0.7 can be regarded as
markers of high reliability. Factor analysis performed by
regression analysis showed that each single item contributes
significantly to the total score. Moreover, the relative weight
of the single items in both patient cohorts was equally
distributed (table 2).
PMR-AS values at baseline, week 4, and the final
evaluation
Mean (SD) PMR-AS at baseline was 27.54 (12.5) (95% CI
¡4.9) in the international cohort and 29.07 (6.5) (95% CI
¡3.19) for the Austrian cohort. This difference was not
significant. At week 4, PMR-AS was 5.99 (4.73) (95% CI
¡1.73) for the international cohort and 8.99 (3.76) (95% CI
¡2.27) for the Austrian cohort, respectively, showing no
significant difference. Similarly, no significant difference was
seen at the final control between the two patient cohorts,
where the mean PMR-AS was 5.35 (6.01) (95% CI ¡2.17)
and 5.92 (2.59) (95% CI ¡1.4) in the Austrian group,
respectively. When the PMR-AS values at baseline and at the
control visits were compared highly significant differences
were seen by using paired t tests (p,0.0001). No significant
difference of the PMR-AS was seen between week 4 and the
final control in the international cohort. In the Austrian
cohort, however, the difference reached significance
(p,0.01), as had already been found in the PMR response
criteria evaluation. Figure 1 shows the individual courses of
the PMR-AS.
Replacing the CRP by the ESR to calculate the PMR-AS,
using ESR60.1 as a marker of the acute phase response,
resulted in slightly higher values. Regression analysis showed
good correlations between the original PMR-AS and the
composite score including the ESR (r = 0.9636, 0.9594,
0.9867). This analysis was performed in the international
cohort only. Removal of the acute phase response markers
from the calculation of the composite score led to insignif-
icant changes of Cronbach’s a in both patient groups and
likewise to high correlations between the original PMR-AS
and the four item construct (r = 0.9651, 0.9408, 0.9962 in the
international cohort; r = 0.8214 at baseline and r = 0.9700 at
the control visits of the Austrian patients).
Patient response assessment
Patient response was compared by correlating the percentage
response of patients, as described by the PMR response
criteria with the percentage change based on the PMR-AS. In
the international cohort an impressive correlation between
the response rates, as expressed by 20%, 50%, 70%, and 90%
response, respectively, could be demonstrated (r = 0.9058 at
week 4 and r = 0.8870 at the final control). In the Austrian
cohort at week 4 a good correlation was also seen between
the two response rates (r = 0.8789). At the final control
(week 33.6) the correlation was shown to be moderate
(r = 0.6868).
At week 4 in 24/57 patients in the international cohort and
in 4/24 patients in the Austrian cohort differences in the stage
of response occurred. At the final control these were,
respectively, 20/57 patients and 7/24 patients. In general,
the response rate was higher when calculated by the PMR-AS
Figure 2 Patient responses to treatment according to the PMR response
criteria
11
in the international and Austrian cohort.
Figure 3 Patient responses to treatment as calculated by percentage
changes of the PMR-AS in the international and Austrian patients.
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change, as no differences of more than one stage of response
were noticed. Figures 2 and 3 show the number of patients of
both cohorts achieving 20, 50, 70, and 90% responses at the
control visits according to both ways of calculating.
PMR-AS in daily routine
The PMR-AS was applied cross sectionally in 53 regular
outpatients, resulting in 64 determinations between March
and July 2003, to evaluate its correlation with the standard of
care in patients with PMR—namely, ESR and patient’s global
assessment. Moreover, patient satisfaction was recorded. In
this cohort PMR-AS values were not normally distributed;
the median was 3.7. The median ESR was 15 mm/1st h,
patient’s global assessment 19, and patient satisfaction 2.
Patient satisfaction, global assessment, and ESR correlated
significantly with one another, with the highest correlation
for patient satisfaction and global assessment (r
s
= 0.799;
p,0.0001) and the lowest correlation for ESR and patient
assessment (r
s
= 0.376; p,0.002). The PMR-AS was found to
be significantly correlated with ESR (r
s
= 0.477; p,0.001),
with patient’s global assessment (r
s
= 0.749; p,0.0001), and
with patient satisfaction ( r
s
= 0.764; p,0.0001) (figs 4A–C).
Disease activity categorising
One other goal of this study was to establish disease activity
categories based on the PMR-AS. To this end a primary
hypothesis was proposed that patients at baseline had high
disease activity and patients with 20 and 50% response
according to the PMR response criteria at the following visits
were regarded as having medium disease activity. Patients
with 70 and 90% responses were assumed to be patients with
low disease activity. Consecutively, the mean values of PMR-
AS and the 95% confidence intervals were calculated and
were found to be as follows: high disease activity 27.89 (95%
CI ¡3.07); medium disease activity 11.85 (CI ¡2.29); low
disease activity 3.54 (CI ¡0.59); PMR-AS was found to be
significantly different between these three groups
(p,0.0001).
As given by the means plus two confidence intervals the
upper and lower limit for medium disease activity was
established, which indeed reflects the 99.9% CI. A PMR-AS
between 17 and 7 can be regarded as the range for medium
disease activity, .17 for high, and ,7 for low disease activity.
To prove this assumption disease activity categories of the
regular outpatients were determined in the way described—
stage 1 resembling high activity and 3 low activity. The
median disease stage was 3. The disease activity category was
shown to be highly significantly correlated with patient
satisfaction (r
s
= 0.712), patient’s assessment (r
s
= 0.566),
and ESR (r
s
= 0.492); all (p,0.01).
It follows that PMR-AS values ,7 can be regarded as
indicating low disease activity, between 7 and 17 medium
disease activity can be assumed, whereas PMR-AS values
.17 reflect high PMR activity.
DISCUSSION
A primary requirement for the creation of composite indices,
in general, is proof of their internal consistency and
reliability. The PMR-AS, comprising five items of proven
sensitivity to change in PMR, is much higher than 0.7, as
indicated by Cronbach’s a, which is regarded as the threshold
of high reliability. The reliability not only of the PMR-AS but
also of the recently published PMR response criteria should
be confirmed in that way. In contrast with the response
criteria, the contribution of the single items to the composite
score varies to a much smaller extent, as expressed by factor
analysis. Even the internal relationship of the weighting of
the single items was identical in both patient groups, with
the highest weight for VAS ph and VAS p and the lowest for
EUL. Therefore, it was decided to retain the acute phase
measurements as part of the PMR-AS, although its reliability
remains the same when CRP or the ESR is removed.
Moreover, because most physicians believe that PMR in
which acute phase parameters are not raised is less active,
this belief is accommodated more specifically by the five item
PMR-AS.
16 17
There was some discussion on how to include MST in the
score, because counting in minutes would have resulted in a
far higher weighting of this symptom and counting in hours
in a much smaller one. Removal of MST from the score
resulted in smaller values of Cronbach’s a (0.67 in the
Austrian cohort), indicating loss of reliability. Thus multi-
plication by 0.1 was proposed to reconcile the criteria of item
weighting, one the one hand, and the requirements of easy
calculation, on the other. This also applies to the use of the
sedimentation rate as ESR60.1, instead of CRP values, which
does not interfere with validity and sensitivity to change of
the PMR-AS.
Currently, measurement of the acute phase response and
patient’s global assessment are the standard procedures for
monitoring patients with PMR. The PMR-AS was shown to
be highly correlated not only with the acute phase response
and patient’s global assessment but also with patient
satisfaction. Thus the PMR-AS has proved its ability to
describe disease activity in the same way as the present
standard and also takes patient satisfaction into account.
In various cohorts of patients with RA of the Lower
Austrian Centre of Rheumatology, Cronbach’s a for the SDAI
and for DAS28, which constitutes the most commonly
applied disease activity score in RA, varied from 0.66 to
0.75. Thus the reliability of the PMR-AS can be regarded as
Figure 4 Regression analysis between the PMR-AS, patient satisfaction, patient’s global assessment, and ESR in the cohort of regular outpatients.
1282 Leeb, Bird
www.annrheumdis.com
considerably higher than that of both the composite scores
for RA activity measurement.
As was expected, the PMR-AS proved its sensitivity to
change as well as, or even better than, the PMR response
criteria, probably owing to the use of absolute numbers
rather than percentage changes, as can be seen for the EUL.
Categorising the patient’s response according to the PMR
response criteria and with respect to percentage changes of
the PMR-AS showed substantial correlations at all times of
evaluation. Differences in response categories of more than
one stage did not occur. Thus the PMR response criteria may
be applied in the future either by calculating them in the way
originally described or by assessing changes of the PMR-AS.
Establishing disease activity categories according to the
development of disease activity indices is a crucial task. It
was felt to be somewhat easier for PMR, as the components
of the PMR-AS had already proved their sensitivity to change
during the response criteria evaluation, and the rapid and
sustained improvement of the disease after initiation of
corticosteroids is clearly evident. The primary hypothesis was
applied that low, medium, and high disease activity can be
assumed for patients showing 70 and 90% response, 20 and
50% response, and for patients at baseline or showing no
response, respectively. This hypothesis was proved by the
considerable significance of the differences between the
groups, on the one hand, and, on the other, by significant
correlation between the disease activity category and patient
satisfaction, the ESR, and patient global health measured by
a VAS in the daily routine. Thus the ranges of low and
medium disease activity seem to correctly describe the clinical
situation.
However, further investigations are necessary to confirm
these disease activity categories, and should also evaluate to
what extent fluctuations of the PMR-AS can be regarded as
clinically relevant. This should also lead to a better definition
of relapses, which occur frequently during the course of the
disease.
18
Composite disease activity indices should clearly describe
the clinical situation and should be easily applied. The PMR-
AS undoubtedly meets these demands. The validity of the
score, its sensitivity to change, and its comparability with
the current standard of monitoring are well confirmed by the
results stated above. Moreover, its calculation can be easily
performed at the physician’s desk and even in the absence of
laboratory values a relevant description of the patient’s actual
status can be achieved by calculating the four item score. In
addition, scores giving absolute numbers make it possible to
compare patients much more easily than using response
criteria, for which the baseline situation has to be known,
which is often not the case in daily practice. However, it
seems to be also appropriate to describe the extent of the
treatment response—for example, for comparison and
assessment of treatment regimens other than corticosteroids.
Thus, in conclusion, the PMR-AS is an easily applicable
and valid tool for disease activity monitoring in patients with
PMR. In combination with the PMR response criteria it
provides a better description of response, enabling evaluation
of new treatments. We expect that better monitoring of
disease activity and treatment responses in PMR will improve
clinical decision making and, ultimately, patient care.
ACKNOWLEDGEMENTS
We cordially tha nk the members of the EULAR Polymyalgia
Rheumatica collaborating group: Gideon Nesher, Wolfgang Hueber,
Dusan Logar, Carlomaurizio Montecucco, Josef Rovensky, and Moshe
Sonnenblick, and Ingrid Andel and Judith Sautner from the Lower
Centre for Rheumatology, for their collaboration and support.
Authors’ affiliations
.....................
B F Leeb, 2nd Department of Medicine; Lower Austrian Centre for
Rheumatology, Humanisklinikum Lower Austria, Stockerau, Austria
H A Bird, Pharmacological Rheumatology, University of Leeds, Leeds, UK
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