Association of Concomitant Fibromyalgia With
Worse Disease Activity Score in 28 Joints, Health
Assessment Questionnaire, and Short Form 36
Scores in Patients With Rheumatoid Arthritis
ALINE RANZOLIN,1JOA˜O CARLOS TAVARES BRENOL,1MARKUS BREDEMEIER,1
JAIRO GUARIENTI,1MARCELE RIZZATTI,1DANIEL FELDMAN,2AND RICARDO MACHADO XAVIER1
Objective. To study the association of the presence of fibromyalgia (FM) with the Disease Activity Score in 28 joints
(DAS28), the Health Assessment Questionnaire (HAQ), and the Medical Outcomes Study Short Form 36 (SF-36) health
survey in patients with rheumatoid arthritis (RA).
Methods. A total of 270 outpatients with RA were enrolled in a prospective cross-sectional study. The patients underwent
clinical evaluation and application of the HAQ and SF-36 questionnaires. Disease activity was evaluated using the DAS28
score. FM and RA diagnoses were made according to American College of Rheumatology criteria.
Results. The overall prevalence of FM was 13.4%. This group of patients had a higher prevalence of female sex, older
mean age, higher functional class, and longer morning stiffness than patients with only RA. Mean ? SD DAS28 scores
were significantly higher in patients with RA and FM (5.36 ? 0.99) than in patients with RA only (4.03 ? 1.39; P < 0.001).
In a multivariable linear regression analysis, FM was an important predictor of the DAS28 score, even after adjusting for
the erythrocyte sedimentation rate, number of swollen joints, functional class, number of disease-modifying antirheu-
matic drugs currently in use, current dose of steroids, and articular erosions. HAQ and SF-36 scores were also worse in
patients with RA and associated FM.
Conclusion. FM is related to worse scores on the DAS28, HAQ, and SF-36 in patients with RA. The presence of FM may
have major implications in the interpretation of the DAS28 score because it is related to higher scores independently of
objective evidence of RA activity.
Fibromyalgia (FM) has a significant impact on health sta-
tus, functional capacity, and quality of life (1–5). In pa-
tients with rheumatoid arthritis (RA), concomitant FM has
been reported in 14–17% of cases (6,7), and may represent
an additional factor that worsens pain and physical, social,
and emotional limitations in these patients.
Several instruments are used to evaluate the outcomes
in RA. Among them, the Disease Activity Score in 28 joints
(DAS28) for disease activity, the Health Assessment Ques-
tionnaire (HAQ) for functional status, and the Medical
Outcomes Study Short Form 36 (SF-36) health survey for
quality of life are the most commonly used (8,9). There is
evidence showing that the presence of FM is associated
with a significant increase in the HAQ score in patients
with RA (7,10). One study showed that patients with FM
have DAS28 scores similar to patients with RA (11), which
is an interesting finding because this instrument was cre-
ated exclusively for the evaluation of RA (11,12). Wolfe
and Michaud showed lower SF-36 scores in patients with
RA and FM when compared with patients with RA only
(6). We are not aware of studies evaluating the association
of FM with the DAS28 score in patients with RA.
The aim of the present study was to analyze the associ-
ation of FM with the DAS28 score and to further study the
Supported in part by grants from the Fundo de Incentivo
a ` Pesquisa e Eventos do Hospital de Clı ´nicas de Porto
1Aline Ranzolin, MD, MSc, Joa ˜o Carlos Tavares Brenol,
MD, PhD, Markus Bredemeier, MD, PhD, Jairo Guarienti,
Marcele Rizzatti, Ricardo Machado Xavier, MD, PhD: Hos-
pital de Clı ´nicas de Porto Alegre, Universidade Federal do
Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil;
2Daniel Feldman, MD, PhD: Universidade Federal de Sa ˜o
Paulo, Sa ˜o Paulo, Brazil.
Address correspondence to Ricardo Machado Xavier, MD,
PhD, Servico de Reumatologia, Hospital de Clı ´nicas de Porto
Alegre, Rua Ramiro Barcelos, 2350 Sala 645, Porto Alegre,
Rio Grande do Sul, 90035-903, Brazil. E-mail: rmaxavier@
Submitted for publication June 2, 2008; accepted in re-
vised form February 2, 2009.
Arthritis & Rheumatism (Arthritis Care & Research)
Vol. 61, No. 6, June 15, 2009, pp 794–800
© 2009, American College of Rheumatology
association of FM with worse HAQ and SF-36 scores in
patients with RA.
PATIENTS AND METHODS
Patients. A prospective cross-sectional study was con-
ducted between March 2006 and June 2007. A total of 270
consecutive RA patients attending the outpatient clinic of
the Rheumatology Service of the Hospital de Clı ´nicas de
Porto Alegre were evaluated. To be included in the study,
the patients had to fulfill at least 4 of the 7 classification
criteria of the American College of Rheumatology (ACR;
formerly the American Rheumatism Association) for the
diagnosis of RA (13). Exclusion criteria consisted of refusal
to sign the written informed consent, missing results for
erythrocyte sedimentation rate (ESR) at the evaluation
visit, clinical or laboratory evidence of infection, and over-
lapping with other connective tissues diseases (except for
secondary Sjo ¨gren’s syndrome). However, patients ini-
tially excluded from the study (due to missing laboratory
results or active infection) could be included in another
visit if no exclusion criteria were present at that time.
Clinical and laboratory evaluations. The patients were
evaluated in 4 sequential stages that occurred during a
single visit. First, the SF-36 questionnaire validated for
Portuguese (in Brazil) (14) was applied. In the second
stage, the same interviewer carried out the specific proce-
dures of the study protocol. Demographic, clinical, and
therapeutic aspects of the patients were recorded by inter-
view and chart review. The presence of erosive joint dis-
ease was defined according to the evaluation of radio-
graphs of hands and feet performed by an experienced
radiologist or rheumatologist. Simple questions (yes or no
answers) about symptoms commonly associated with FM
were asked, including daytime fatigue (“Do you feel tired
during the day, even without physical effort?”), dry mouth
(“Do you have the feeling that your mouth is dry?”), dry
eyes (“Do you have the feeling that your eyes are dry or
that you have sand in them?”), paresthesias (“Do you usu-
ally feel tingling, burning, have pins and needles or body
numbness?”), headache (“Do you usually have head-
ache?”), mood alterations (“Do you have symptoms of
depression or feel anxious, nervous, worried or irri-
tated?”), and nonrefreshing sleep (“Do you wake up
tired?”). After that, the evaluation of the presence of dif-
fuse pain according to ACR criteria (15) was made.
In the third stage, the patients completed the HAQ,
which was validated for application to Brazilian patients
(16). Then a trained doctor, blinded to the SF-36, study
protocol, and HAQ data, counted the tender and swollen
joints to calculate the DAS28 and recorded his clinical
impression of disease activity using a visual analog scale
In the final step of the evaluation, the patients were
examined for the presence of pain in 18 FM tender points,
as recommended by the ACR criteria (15). This examina-
tion was performed by a single examiner (AR) who was
blinded for the results of all other previous tests. FM was
diagnosed according to the fulfillment of ACR criteria (15).
The ESR was measured in the first hour by the Wester-
gren method, using samples collected within 10 days of
the evaluation visit. Serum rheumatoid factor was mea-
sured by nephelometry, and a value ?40 IU/ml was con-
This study was approved by the Research Ethics Com-
mittee of the Hospital de Clı ´nicas de Porto Alegre, and all
patients signed a written informed consent before entering
Calculation of sample size. Estimating an FM preva-
lence of ?17% in patients with RA (6) and a mean ? SD
DAS28 score of 4.23 ? 1.5 in patients with RA without FM
(11), with a mean difference of 20% between RA and FM
patients being considered clinically significant, a sample
of 250 patients would have an 89.1% power to detect a
significant statistical difference (P ? 0.05) in the DAS28
between the groups.
Statistical analysis. The data were analyzed using Epi
Info, version 6 (17) and SPSS for Windows, version 11.0
(18). The association between categorical variables was
tested using Pearson’s chi-square test, Yates’ corrected chi-
square test, or Fisher’s exact test. Quantitative variables
were graphically and statistically tested (with the Kolmog-
orov-Smirnov goodness-of-fit test) for normality of distri-
bution. Variables with a normal distribution were pre-
sented as the mean ? SD, and the between-group
comparisons were performed using Student’s t-test. Non-
normal quantitative variables were presented as the me-
dian (25th, 75th percentiles), and the between-group com-
parisons were performed using the Mann-Whitney test. P
values less than or equal to 0.05 were considered statisti-
cally significant (all presented P values are 2-tailed).
A multivariable linear regression model was built to
evaluate the association of the presence of FM with the
DAS28 score, adjusting for confounding variables. The
selection of independent variables into the model was
based on the capacity of the variable to objectively repre-
sent disease activity and/or severity (no automatic method
of variable selection was used). Confounding variables that
were considered to be significantly influenced by the pa-
tient’s perception (and therefore directly related to FM
itself) were not included. The assumptions of the regres-
sion model were assessed by the Kolmogorov-Smirnov test
for normality of residuals, White’s test for heteroscedastic-
ity, the evaluation of variance inflation factors for detec-
tion of colinearity, and tests for nonlinear associations
with the aid of the Gretl software (19). Residual analysis
was performed to detect Y-dimension outliers, which were
defined as cases with studentized deleted residuals with
absolute values greater than 3.0. The presence of X-dimen-
sion outliers was evaluated by analyzing the weighted
leverage values (a value ?2p/n was considered high,
where n ? the number of cases and p ? the number of
parameters being estimated). Highly influential cases were
identified as those with Cook’s distances ?4/(n ? k ? 1),
where k ? the number of independent variables. The log-
arithmic transformation of independent variables was at-
tempted before exclusion of the case when an extreme
Concomitant FM and Worse Index Scores in RA Patients 795
outlier was detected. Partial regression coefficients and
95% confidence intervals (95% CIs) were estimated for the
independent variables included in the model.
Among 270 patients with RA, 32 (13.4%) fulfilled the
criteria for the diagnosis of FM. The demographic and
clinical characteristics of patients with and without FM
are shown in Table 1. The mean age was higher and
women were more prevalent in the group with RA and FM.
There was no statistically significant difference between
the groups concerning marital status or educational level.
Patients with RA and FM had higher functional classes
and longer morning stiffness than RA patients, and tended
to use prednisone more frequently.
Table 2 compares the prevalences of the most common
clinical symptoms of FM between the groups. All symp-
toms were more frequent in the patients with RA and FM.
The prevalence of diffuse pain was very low (?2%) in RA
patients without FM.
The DAS28 score was 1.33 (95% CI 0.82, 1.83) points
higher in the group with RA and FM when compared with
RA patients (Table 3). The difference was related to the
subjective components of the DAS28 (tender joints and
VAS for disease status), although there was no significant
difference in the ESR and the swollen joint count. High
disease activity was more prevalent in the group with RA
and FM. This group also had a very small prevalence of
low disease activity and did not have any patients in
remission. The median values of the HAQ, the patient’s
VAS for pain, and the physician’s VAS were also higher in
the group with RA and FM.
The values for the SF-36 scales are shown in Table 4.
There was a significantly worse quality of life in the group
Table 1. Demographic and clinical characteristics of rheumatoid arthritis (RA) patients
with and without fibromyalgia (FM)*
(n ? 238)
RA and FM
(n ? 32)
Age, mean ? SD years
Duration of RA diagnosis, median
(25th to 75th percentiles)
Duration of RA symptoms, median
(25th to 75th percentiles)
Number of DMARDs used, median
(25th to 75th percentiles)‡
Current use of prednisone
Rheumatoid factor positive
Presence of joint erosions
Morning stiffness for ?60 minutes
55.0 ? 12.4
60.2 ? 12.8
14.0 (10.0–21.0) 14.5 (8.2–22.7) 0.998
2.0 (2.0–3.0)2.5 (2.0–3.0)0.208
* Values are the number (percentage) unless otherwise indicated. ES ? elementary school; HS ? high
school; DMARDs ? disease-modifying antirheumatic drugs.
† Pearson’s chi-square test, Yates’ corrected chi-square test, Fisher’s exact test, Student’s t-test, or
Mann-Whitney test according to the nature and distribution of the data.
‡ Cumulative number of DMARDs used since diagnosis.
Table 2. Prevalence of common symptoms of
fibromyalgia (FM) in the 2 patient groups*
(n ? 238)
(n ? 32)
Number of tender points,
median (25th to 75th
91 (38.2) 24 (75.0)
113 (47.5) 28 (87.5)
94 (39.5) 25 (78.1)
100 (42.0) 23 (71.9)
108 (45.4) 28 (87.5)
98 (41.2) 28 (87.5)
122 (51.3) 24 (75.0)
? 0.00132 (100.0)
14 (13–16) ? 0.001
* Values are the number (percentage) unless otherwise indicated.
RA ? rheumatoid arthritis.
† Yates’ corrected chi-square test, Fisher’s exact test, or Mann-
Whitney test according to the nature and distribution of the data.
796Ranzolin et al
with RA and FM in all aspects except for emotional role,
where there was no difference between RA patients with
or without FM.
A model of multivariable linear regression with the
DAS28 score as the dependent variable is shown in Table
5. The results from this model indicated that FM is an
independent predictor of the DAS28 associated with a
mean adjusted increase of 0.885 points (95% CI 0.551,
1.219) in the DAS28 score. The inclusion of the variables
sex and age in the model produced virtually no change in
the overall coefficient of determination and partial regres-
sion coefficients. When 24 cases identified as outliers or
highly influential cases were removed from this model, the
multiple coefficient of determination (R2) increased to 0.72
(adjusted R2? 0.71), and the partial regression coefficient
of FM increased to 0.987 (95% CI 0.669, 1.305).
In the present study, we analyzed the association of the
coexistence of FM with the results of important instru-
ments of evaluation of patients with RA. Our analyses
have shown that FM is significantly associated with worse
DAS28, HAQ, and SF-36 scores in patients with RA. Al-
though the DAS28 is one of the main instruments of eval-
uation of RA activity in clinical trials, we found no previ-
ous studies evaluating the association of FM with the
results of this scale in patients with RA.
In our sample, 13.4% of patients met the ACR classifi-
cation criteria for RA and FM simultaneously, which is
similar to the previously reported prevalence (6,7). In con-
trast to published data, our concomitant FM patients had a
higher mean age than those without FM. However, as
Table 3. Values of the DAS28 (and related variables), HAQ, patient pain VAS, and
physician VAS in rheumatoid arthritis (RA) patients with and without
Evaluation measures of RA
(n ? 238)
RA and FM
(n ? 32)
DAS28, mean ? SD
Disease activity VAS
High (DAS28 ?5.1)
Moderate (DAS28 ?3.2 to ?5.1)
Low (DAS28 ?3.2)
Remission (DAS28 ?2.6)
Patient pain VAS
4.03 ? 1.39
5.36 ? 0.99
* Values are the median (25th to 75th percentiles) unless otherwise indicated. DAS28 ? Disease Activity
Score in 28 joints; HAQ ? Health Assessment Questionnaire; VAS ? visual analog scale; ESR ?
erythrocyte sedimentation rate.
† Student’s t-test, Fisher’s exact test, or Mann-Whitney test according to the nature and distribution of the
‡ Absolute number (percentage).
Table 4. Values of the Medical Outcomes Study Short Form 36 health survey scales in
patients with isolated rheumatoid arthritis (RA) and in patients with RA and
concomitant fibromyalgia (FM)*
(n ? 238)
RA and FM
(n ? 32)
* Values are the median (25th to 75th percentiles).
† Mann-Whitney test.
Concomitant FM and Worse Index Scores in RA Patients797
expected according to FM epidemiology, the group with
RA and FM had a greater prevalence of women (6,7,10).
Confirming the results of a previous study (7), we ob-
served an association between FM and a higher degree of
functional limitation. Patients with RA and FM had a
median HAQ score of 2.0 compared with 1.12 for patients
with isolated RA; this difference seems relevant because a
variation of 0.22 is considered clinically important (20).
FM per se has been described as being related to a reduc-
tion of the functional capacity similar to that observed in
RA (1,2,21). Interestingly, FM, which is not usually asso-
ciated with prolonged morning stiffness, was related to a
longer duration of this symptom in patients with RA.
Similar results were found by Wolfe et al (10). Perhaps
pain, fatigue, and sleep disturbance, which are present in
FM, can prolong the morning stiffness sensation typical of
RA in patients with both conditions.
Patients with FM and RA had a mean DAS28 score 1.33
(95% CI 0.82, 1.83) points higher than patients with iso-
lated RA. Analyzing the DAS28 components individually,
the objective ones (swollen joints and ESR) were not sig-
nificantly different between the groups. There were also no
significant differences in disease duration, number of dis-
ease-modifying antirheumatic drugs used, and rheumatoid
factor positivity between the groups. Articular erosions
tended to be more frequent in patients without FM. How-
ever, the ESR was slightly higher and the number of swol-
len joints tended to be greater in patients with RA and FM.
This may indicate that patients with RA and FM actually
have a more active disease than patients with RA, but we
were not able to (statistically) detect such a difference,
possibly due to the size of our sample. Patients with FM
also had higher functional class and tended to take pred-
nisone more frequently.
In contrast to the objective components, the subjective
components of the DAS28 score (number of tender joints
and patient’s VAS) showed a great disproportion between
the study groups. The small difference in objective com-
ponents and the large disproportion in the subjective com-
ponents suggest that the coexistence of FM is related to an
increase in the DAS28 score more than would be ex-
plained by the disease activity. Therefore, when FM is
present, it is probable that the DAS28 does not exclusively
reflect the inflammatory activity of RA. This conclusion
was corroborated by the results of the multiple linear
regression model, which observed an association of FM
with higher DAS28 scores independently of several vari-
ables that reflect the activity and severity (including the
ESR, number of swollen joints, functional status, and pred-
nisone dose) of the disease. This association was main-
tained at a clinically and statistically significant level (par-
tial regression coefficient 0.668 [95% CI 0.407, 0.907], P ?
0.001), even when the physician’s VAS of disease activity
and duration of morning stiffness were simultaneously
added to the model in Table 5.
In the multiple linear regression model, FM was related
to a mean increase of ?1.0 point in the DAS28 score when
outliers and highly influential cases were excluded. This
increase in the DAS28 score may have an important im-
pact on the classification of the patients. For example, in
the group with RA and FM in our study, initially 19
patients (59.4%) had a DAS28 indicative of high disease
activity (DAS28 ?5.1), whereas 21.8% of patients with
isolated RA had high disease activity. Excluding the esti-
mated increase in the DAS28 score related to FM (1.0
point), more than half of these patients (11 of 19) would
have been reclassified as having moderate disease activity
(DAS28 ?3.2 to ?5.1). Another patient, initially included
in the low disease activity group (DAS28 ?3.2), would
have achieved remission criteria for RA (DAS28 ?2.6) (9).
The DAS28 score is considered essential to evaluating
therapeutic response in clinical trials and is also useful in
Table 5. Multivariable linear regression model with the Disease Activity Score in 28
joints as the dependent variable*
coefficient (95% CI)
Logarithm of the ESR (log10ESR)‡
Number of swollen joints
(Number of swollen joints)2§
Functional class II or higher†
Number of DMARDs currently in use
Current dose of prednisone, mg
0.885 (0.551, 1.219)
1.615 (1.333, 1.896)
0.344 (0.268, 0.421)
?0.014 (?0.020, ?0.008)
0.398 (0.171, 0.626)
0.062 (?0.084, 0.209)
0.014 (?0.004, 0.032)
?0.088 (?0.376, 0.199)
0.789 (0.283, 1.294)
* Additional results from the multivariable linear regression model: R2? 0.64; adjusted R2? 0.63; n ?
270. Kolmogorov-Smirnov test of residuals ? 0.764, P ? 0.604. White’s test ? 54.461, P ? 0.090. 95% CI ?
95% confidence interval; ESR ? erythrocyte sedimentation rate; DMARDs ? disease-modifying antirheu-
† Variables defined numerically as follows: yes ? 1, no ? 0.
‡ The variable ESR was logarithmically transformed to reduce the influence of outliers and improve the
multiple coefficient of determination (R2).
§ A quadratic term of the number of swollen joints was suggested during the process of model construc-
tion by the nonlinearity test. The variance inflation factors of the variable number of swollen joints and
its quadratic term were 6.87 and 7.08, respectively. Other variables presented variance inflation factors
¶ Constant is the value of the dependent variable when all independent variables are equal to zero.
798Ranzolin et al
routine clinical care (22). In addition, the DAS28 is a
strong predictor of physical capacity and radiologic pro-
gression (23). Therefore, the possibility that FM affects the
interpretation of this score may have important implica-
tions. In routine clinical practice, misclassification of dis-
ease activity may lead to an unnecessary change in the
therapy of RA. It may affect the selection of patients in
clinical trials, because a high DAS28 score is frequently
used as one of the inclusion criteria. The interpretation of
results may also be affected, considering that FM symp-
toms are not expected to respond to therapeutics directed
Interesting results were related to the physician’s global
assessment of disease activity, which was higher in pa-
tients with FM and RA. The disproportion between objec-
tive evidence of disease activity and the physician’s eval-
uation raises the possibility that the presence of FM affects
not only the patient’s perception of his/her illness, but
may also influence the physician’s evaluation.
Studies using the SF-36 and other measures of quality of
life have found that FM has a negative impact similar to
that of RA (24–27). In the present study, all components of
the SF-36 were negatively affected by the presence of FM,
except for the impact on psychological aspects in well-
being (emotional role), indicating the worse quality of life
in this group. These results are similar to those obtained by
Wolfe and Michaud (6).
The data from this study demonstrated that the presence
of FM is related to higher DAS28 scores, and confirmed the
association of FM with worse HAQ and SF-36 scores in
patients with RA. The increase in the DAS28 score in
patients with RA and FM may lead to significant misclas-
sification of disease activity status. When evaluating and
monitoring patients with RA, the presence of associated
FM should be considered. In these cases, a more cautious
interpretation of the instruments of RA evaluation should
be given, and careful clinical judgment may be more ap-
propriate than relying exclusively on numbers when as-
sessing the activity of the disease.
Dr. Ranzolin had full access to all of the data in the study and
takes responsibility for the integrity of the data and the accuracy
of the data analysis.
Study design. Ranzolin, Brenol, Bredemeier, Feldman, Xavier.
Acquisition of data. Ranzolin, Brenol, Guarienti, Rizzatti, Xavier.
Analysis and interpretation of data. Ranzolin, Brenol, Brede-
Manuscript preparation. Ranzolin, Brenol, Bredemeier, Xavier.
Statistical analysis. Ranzolin, Brenol, Bredemeier, Xavier.
1. Hawley DJ, Wolfe F. Pain, disability, and pain/disability re-
lationships in seven rheumatic disorders: a study of 1,522
patients. J Rheumatol 1991;18:1552–7.
2. Martinez JE, Ferraz MB, Sato EI, Atra E. Fibromyalgia versus
rheumatoid arthritis: a longitudinal comparison of the quality
of life. J Rheumatol 1995;22:270–4.
3. Wolfe F, Anderson J, Harkness D, Bennett RM, Caro XJ, Gold-
enberg DL, et al. Health status and disease severity in
fibromyalgia: results of a six-center longitudinal study. Arthri-
tis Rheum 1997;40:1571–9.
4. Viitanen JV, Kautiainen H, Isomaki H. Pain intensity in pa-
tients with fibromyalgia and rheumatoid arthritis. Scand
J Rheumatol 1993;22:131–5.
5. Gustafsson M, Gaston-Johansson F. Pain intensity and health
locus of control: a comparison of patients with fibromyalgia
syndrome and rheumatoid arthritis. Patient Educ Couns 1996;
6. Wolfe F, Michaud K. Severe rheumatoid arthritis (RA), worse
outcomes, comorbid illness, and sociodemographic disadvan-
tage characterize RA patients with fibromyalgia. J Rheumatol
7. Naranjo A, Ojeda S, Francisco F, Erausquin C, Rua-Figueroa I,
Rodriguez-Lozano C. Fibromyalgia in patients with rheuma-
toid arthritis is associated with higher scores of disability
[letter]. Ann Rheum Dis 2002;61:660–1.
8. Bruce B, Fries JF. The Health Assessment Questionnaire
(HAQ). Clin Exp Rheumatol 2005;23 Suppl 39:14–8.
9. Fransen J, van Riel PL. The Disease Activity Score and the
EULAR response criteria. Clin Exp Rheumatol 2005;23 Suppl
10. Wolfe F, Cathey MA, Kleinheksel SM. Fibrositis (fibromyal-
gia) in rheumatoid arthritis. J Rheumatol 1984;11:814–8.
11. Leeb BF, Andel I, Sautner J, Nothnagl T, Rintelen B. The
DAS28 in rheumatoid arthritis and fibromyalgia patients.
Rheumatology (Oxford) 2004;43:1504–7.
12. Harth M, Pope J. The measure of our measures. Rheumatology
13. Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF,
Cooper NS, et al. The American Rheumatism Association
1987 revised criteria for the classification of rheumatoid ar-
thritis. Arthritis Rheum 1988;31:315–24.
14. Ciconelli RM, Ferraz MB, Santos W, Meinao I, Quaresma MR.
Traduc ¸a ˜o para a lı ´ngua portuguesa e validac ¸a ˜o do question-
a ´rio gene ´rico de avaliac ¸a ˜o de qualidade de vida SF-36 (Brasil
SF-36). Rev Bras Reumatol 1999;39:143–50.
15. Wolfe F, Smythe HA, Yunus MB, Bennett RM, Bombardier C,
Goldenberg DL, et al. The American College of Rheumatology
1990 criteria for the classification of fibromyalgia: report of
the Multicenter Criteria Committee. Arthritis Rheum 1990;33:
16. Ferraz MB, Oliveira LM, Araujo PM, Atra E, Tugwell P. Cross-
cultural reliability of the physical ability dimension of the
Health Assessment Questionnaire. J Rheumatol 1990;17:
17. Dean AG, Dean JA, Coulombier D, Brendel KA, Smith DC,
Burton AH, et al. Epi Info version 6: a word processing,
database, and statistics program for epidemiology on micro-
computers. Atlanta (GA): Centers for Disease Control and
18. Norusis MJ. SPSS 11.0 guide to data analysis. Upper Saddle
River (NJ): Prentice Hall; 2002.
19. Cottrell A. Gretl manual: gnu regression, econometrics and
University; 2003. URL: http://gretl.sourceforge.net/manual.
20. Wells GA, Tugwell P, Kraag GR, Baker PR, Groh J, Redelmeier
DA. Minimum important difference between patients with
rheumatoid arthritis: the patient’s perspective. J Rheumatol
21. Walker EA, Keegan D, Gardner G, Sullivan M, Katon WJ,
Bernstein D. Psychosocial factors in fibromyalgia compared
with rheumatoid arthritis. I. Psychiatric diagnoses and func-
tional disability. Psychosom Med 1997;59:565–71.
22. Pincus T, Sokka T. Complexities in the quantitative assess-
ment of patients with rheumatic diseases in clinical trials and
clinical care. Clin Exp Rheumatol 2005;23 Suppl 39:1–9.
23. Van der Heijde DM, van Leeuwen MA, van Riel PL, Koster
AM, van ’t Hof MA, van Rijswijk MH, et al. Biannual radio-
graphic assessments of hands and feet in a three-year prospec-
tive followup of patients with early rheumatoid arthritis. Ar-
thritis Rheum 1992;35:26–34.
Concomitant FM and Worse Index Scores in RA Patients 799
24. Ofluoglu D, Berker N, Guven Z, Canbulat N, Yilmaz IT, Kay-
han O. Quality of life in patients with fibromyalgia syndrome
and rheumatoid arthritis. Clin Rheumatol 2005;24:490–2.
25. Birrell FN, Hassell AB, Jones PW, Dawes PT. How does the
Short Form 36 health questionnaire (SF-36) in rheumatoid
arthritis (RA) relate to RA outcome measures and SF-36 pop-
ulation values? A cross-sectional study. Clin Rheumatol 2000;
26. Burckhardt CS, Clark SR, Bennett RM. Fibromyalgia and
quality of life: a comparative analysis. J Rheumatol 1993;
27. Martinez JE, Barauna Filho IS, Kubokawa K, Pedreira IS,
Machado LA, Cevasco G. Evaluation of the quality of life in
Brazilian women with fibromyalgia, through the Medical Out-
come survey 36 item short-form study. Disabil Rehabil 2001;
800 Ranzolin et al