Introduction
The possible influence of gender and gender-related variables on the phenotype, severity, and prognosis of rheumatoid arthritis (RA) appears to be of considerable interest
Analyses of gender differences of RA include a study that indicates less favorable status in men
Gender differences in disease activity and other measures may reflect the properties of measures
Materials and methods
The Quantitative Standard Monitoring of Patients with RA (QUEST-RA) program was established in 2005 to promote quantitative assessment in usual clinical care at multiple sites and to develop a database of RA patients seen outside of clinical trials in regular care in many countries. The initial design was to assess 100 patients with RA at each of three or more sites in 10 different countries, with data collection beginning in January 2005. The program has since been expanded to include 6,004 patients from 70 sites in 25 countries as of April 2008. This report
Clinical evaluation
All patients were assessed according to a standard protocol to evaluate RA (SPERA)
Patient self-report
Patients completed a four-page expanded self-report questionnaire that included the standard Health Assessment Questionnaire (HAQ)
Gender and disease activity measures
DAS28 was calculated for current disease activity
The proportion of patients who met DAS28 criteria for remission (<2.6) was analyzed in females and males with 0, 1, 2, 3, 4, and 5 swollen joints on a 28-joint count. Levels of individual disease activity measures were calculated for females and males according to SJC28 in arbitrary categories of 0 to 1, 2 to 3, 4 to 6, and 7 or more swollen joints. Swollen joint count was chosen as the standard, although a 'gold standard' measure for disease activity does not exist.
Gender and disease characteristics
Gender differences in disease characteristics, including the prevalence of RF+, nodules, and erosive disease, were studied separately in two groups of countries: 'low' prevalence and 'high' prevalence countries. For example, the prevalence of RF+ ranges between 52% and 92% among countries, with a median of 73.5%. Thus, all countries with a 'low' prevalence of RF+ of between 52% and 73.5% were analyzed together for gender differences of RF+, and countries with a 'high' prevalence of RF+ of between 73.5% and 92% were analyzed together for gender differences of RF+. Two groups of countries ('low' versus 'high' prevalence) were formed similarly to analyze nodules (cut point for prevalence = 20%) and erosive disease (cut point for prevalence = 63%).
Gender and therapies for rheumatoid arthritis
The percentage of patients who were taking prednisone, methotrexate, and biologic agents for RA differed considerably between countries. To study whether females were treated differently from males, countries were studied in two groups, such as for disease characteristics, divided at the median among the 25 countries. Thus, countries with 'low use of a drug' and 'high use of a drug' were analyzed separately. Medians were 50% for prednisone, 62% for methotrexate, and 18% for biologic agents. The delay between the first RA symptoms and initiation of the first DMARDs was calculated and compared between men and women.
Statistical methods
Results for continuous variables are presented as mean, standard deviation, median, and percentages. Statistical significance was tested with the Student
Results
Demographic and clinical characteristics
In April 2008, the QUEST-RA database included 6,004 patients from 70 sites in 25 countries. The demographic characteristics are those of a typical RA cohort with 79% females, more than 90% Caucasians, and a mean age of 57 years (Table
Patient demographic and clinical characteristics in the QUEST-RA Study by country
Country
Sites
Patients
Female, percentage
Age, years
Disease duration, years
DMARD delay, months
RF+, percentage
Smoking now, percentage
DAS28
SJC28
ESR
Pain
Patient global
HAQ
Taking now, percentage
Pred
MTX
Any biologic
Netherlands
3
317
66.3
59.2
9.2
6.0
68.8
22.9
3.1
1.0
15.0
2.5
2.7
0.8
16.1
74.1
19.6
Finland
3
304
72.4
58.5
13.5
7.0
74.8
15.5
3.3
1.0
13.0
2.8
2.8
0.6
51.3
61.5
12.5
USA
3
301
72.9
57.5
9.3
9.0
70.9
20.5
3.3
2.0
14.0
3.2
2.6
0.6
60.1
71.8
27.6
Greece
3
300
75.7
58.1
11.8
7.0
52.1
15.8
3.4
0.0
23.0
2.3
2.0
0.3
70.7
71.3
47.0
Denmark
3
301
76.7
57.8
12.0
11.0
73.3
31.6
3.4
1.0
14.0
2.6
2.8
0.6
14.6
71.1
21.3
Spain
3
302
73.5
59.8
10.6
14.0
72.5
17.8
3.5
1.0
17.0
3.1
3.6
0.9
46.7
56.3
23.2
France
4
389
77.9
55.3
12.8
8.0
75.3
19.1
3.7
1.0
16.0
3.9
3.6
0.9
60.9
57.1
44.2
Sweden
3
260
71.8
59.4
12.5
12.0
81.6
19.2
3.8
2.0
19.0
3.3
3.3
0.9
41.2
65.8
26.9
UK
3
145
77.9
59.6
15.0
16.0
81.4
19.4
4.0
1.0
19.0
4.1
3.6
0.9
28.3
70.3
14.5
Ireland
3
240
64.3
56.4
11.3
11.0
79.6
24.6
4.1
3.0
18.0
3.4
2.9
0.8
31.7
71.7
32.1
Canada
1
100
78.8
57.9
12.4
11.0
82.8
30.0
4.1
2.0
21.0
4.6
4.0
1.0
25.0
49.0
23.0
Turkey
3
309
85.6
52.2
11.6
12.0
67.6
14.1
4.2
0.0
30.0
4.2
4.6
0.9
57.3
69.3
5.8
Brazil
3
115
88.6
52.3
8.5
8.0
79.6
13.3
4.2
3.0
28.0
3.2
3.5
0.6
53.9
80.0
25.2
UAE
2
199
85.8
45.3
6.4
11.7
75.4
6.3
4.3
3.0
23.5
3.7
2.8
0.6
35.2
53.3
7.5
Germany
3
225
83.6
58.8
13.4
15.0
60.9
13.5
4.4
3.0
20.0
5.0
4.9
0.8
26.7
45.8
22.7
Italy
4
336
78.2
61.0
10.5
9.0
71.4
15.9
4.5
2.0
28.0
4.9
5.0
1.0
51.8
53.3
12.5
Estonia
3
168
85.5
55.8
11.8
12.0
68.1
14.0
4.7
4.0
24.0
4.3
4.8
1.1
43.5
53.6
0.6
Russia
3
73
84.5
54.2
6.2
10.0
74.6
15.4
5.0
5.0
24.0
3.6
4.5
1.1
38.4
46.6
16.4
Hungary
3
153
87.4
57.9
12.6
12.0
92.8
25.3
5.1
5.0
26.0
5.2
5.1
1.4
36.6
62.7
12.4
Latvia
1
79
79.7
53.2
13.2
32.1
84.6
19.2
5.2
4.0
26.0
5.1
5.7
1.4
63.3
70.9
21.5
Poland
7
642
86.7
53.2
11.5
4.0
70.3
11.9
5.3
6.0
31.0
5.0
4.8
1.4
58.9
65.0
6.1
Argentina
2
246
90.2
51.4
9.9
13.0
90.5
21.4
5.3
9.0
30.0
5.0
4.7
1.0
63.4
48.8
2.8
Lithuania
2
300
82.9
54.1
10.7
15.0
78.4
7.1
5.5
3.0
29.0
5.2
5.3
1.4
82.7
55.7
9.3
Serbia
1
100
88.0
59.2
10.1
11.1
71.4
18.4
5.9
6.0
28.0
5.1
5.3
1.6
54.0
54.0
0.0
Kosovo
1
100
84.0
55.0
7.8
3.0
80.6
10.4
6.0
6.0
45.0
5.1
5.0
1.6
90.0
71.0
1.0
Total
70
6,004
79.2
56.2
11.2
10.0
73.6
17.4
4.2
2.0
22.0
4.1
4.2
0.9
49.1
62.5
18.3
Mean values are presented for age, disease duration, and disease activity score using 28 joint counts (DAS28). Median values are presented for other continuous variables. DMARD, disease-modifying antirheumatic drug; ESR, erythrocyte sedimentation rate; HAQ, Health Assessment Questionnaire; MTX, methotrexate; Pred, prednisone; QUEST-RA, Quantitative Standard Monitoring of Rheumatoid Arthritis; RF, rheumatoid factor; SJC, swollen joint count; UAE, United Arab Emirates.
Gender differences in disease activity in the entire group
Women had higher scores (indicating poorer status) than men in all Core Data Set measures. The mean values for females and males were SJC28 of 4.5 versus 3.8, TJC28 of 6.9 versus 5.4, ESR of 30 versus 26, HAQ (0 to 3) of 1.1 versus 0.8, visual analog scales (0 to 10) for physician global estimate of 3.0 versus 2.5, pain of 4.3 versus 3.6, and patient global estimate of 4.2 versus 3.7 (
Differences according to gender among clinical variables in the QUEST-RA Study, adjusted for age, disease duration, and country
Differences according to gender among clinical variables in the QUEST-RA Study, adjusted for age, disease duration, and country. DAS28, disease activity score using 28 joint counts; ESR, erythrocyte sedimentation rate; HAQ, Health Assessment Questionnaire; MDglobal, doctor global assessment; QUEST-RA, Quantitative Standard Monitoring of Rheumatoid Arthritis; SJC28, swollen joint count-28; TJC28, tender joint count-28.
Among the disease activity measures that were studied, SJC28 levels appeared to be most similar between genders. Therefore, other disease activity measures were compared on different SJC28 levels. Among patients who had 0 to 1 swollen joints, women had statistically significantly higher mean values compared with men for all other disease activity measures (
Differences in disease activity measures between females and males in the QUEST-RA Study according to the number of swollen joints
Number of swollen joints
Mean (standard deviation)
DAS28
TJC28
ESR
MD global
Pain
Patient global
Fatigue
HAQ
0–1
Female
3.2 (1.2)
3.2 (5.3)
24 (19)
1.6 (1.8)
3.3 (2.6)
3.3 (2.5)
3.9 (2.9)
0.83 (0.75)
Male
2.7 (1.2)
2.0 (3.9)
20 (21)
1.2 (1.5)
2.6 (2.5)
2.9 (2.6)
2.9 (2.7)
0.52 (0.62)
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
2–3
Female
4.2 (1.1)
5.2 (5.4)
29 (22)
2.8 (1.9)
4.1 (2.6)
4.1 (2.4)
4.5 (2.8)
1.1 (0.71)
Male
3.8 (1.2)
4.7 (5.7)
25 (26)
2.4 (1.8)
3.6 (2.4)
3.6 (2.3)
3.7 (2.6)
0.74 (0.62)
<0.001
0.26
0.11
0.013
0.010
0.010
0.001
<0.001
4–6
Female
4.8 (1.1)
7.3 (6.0)
31 (23)
3.5 (2.0)
4.7 (2.5)
4.6 (2.4)
5.0 (2.7)
1.2 (0.71)
Male
4.6 (1.3)
6.8 (6.2)
32 (27)
3.4 (2.0)
4.1 (2.5)
4.4 (2.4)
4.2 (2.7)
0.91 (0.64)
0.071
0.28
0.63
0.041
0.017
0.29
<0.001
<0.001
≥ 7
Female
6.0 (1.2)
13 (8.0)
38 (25)
5.1 (2.1)
5.6 (2.5)
5.2 (2.5)
5.6 (2.6)
1.4 (0.75)
Male
5.8 (1.3)
12 (7.8)
38 (28)
4.9 (2.1)
5.2 (2.3)
4.9 (2.4)
5.0 (2.6)
1.2 (0.68)
0.016
0.064
0.99
0.21
0.024
0.082
<0.001
<0.001
More men (30.0%) than women (16.7%) were in DAS28 remission (
The proportion of males and females with 0 to 5 swollen joints in the QUEST-RA Study who meet DAS28 criteria for remission
The proportion of males and females with 0 to 5 swollen joints in the QUEST-RA Study who meet DAS28 criteria for remission. CI, confidence interval; DAS28, disease activity score using 28 joint counts; QUEST-RA, Quantitative Standard Monitoring of Rheumatoid Arthritis; SJC, swollen joint count.
Gender differences in disease activity measures according to country
Standardized units of difference between genders were calculated for each variable according to country and are shown as an example for two variables: HAQ (Table
Health Assessment Questionnaire: differences between females and males by country
Female,
mean (SD)
Male,
mean (SD)
Difference,
mean (95% CI)
Effect sizea
(95% CI)
Netherlands
0.89 (0.69)
0.62 (0.61)
0.27 (0.12 to 0.43)
0.42 (0.16 to 0.62)
Finland
0.84 (0.76)
0.60 (0.64)
0.24 (0.06 to 0.42)
0.33 (0.07 to 0.56)
USA
0.81 (0.68)
0.52 (0.67)
0.29 (0.12 to 0.46)
0.43 (0.16 to 0.67)
Greece
0.61 (0.71)
0.29 (0.45)
0.32 (0.15 to 0.50)
0.49 (0.29 to 0.68)
Denmark
0.85 (0.75)
0.59 (0.66)
0.26 (0.07 to 0.46)
0.36 (0.09 to 0.60)
Spain
1.10 (0.84)
0.75 (0.69)
0.35 (0.14 to 0.56)
0.44 (0.21 to 0.70)
France
0.99 (0.69)
0.67 (0.62)
0.32 (0.16 to 0.48)
0.48 (0.24 to 0.74)
Sweden
0.97 (0.65)
0.82 (0.63)
0.16 (-0.02 to 0.33)
0.25 (-0.02 to 0.54)
UK
1.06 (0.74)
0.80 (0.75)
0.26 (-0.04 to 0.55)
0.35 (-0.08 to 0.78)
Ireland
0.98 (0.71)
0.79 (0.75)
0.19 (-0.01 to 0.38)
0.26 (-0.04 to 0.55)
Canada
1.04 (0.72)
1.07 (0.73)
-0.03 (-0.40 to 0.34)
-0.04 (-0.58 to 0.44)
Turkey
1.01 (0.77)
0.70 (0.71)
0.31 (0.07 to 0.56)
0.41 (0.11 to 0.73)
Brazil
0.84 (0.74)
0.68 (0.72)
0.15 (-0.28 to 0.59)
0.21 (-0.45 to 0.72)
UAE
0.74 (0.63)
0.42 (0.46)
0.32 (0.07 to 0.56)
0.53 (0.19 to 0.81)
Germany
0.94 (0.70)
0.74 (0.65)
0.20 (-0.04 to 0.45)
0.29 (-0.04 to 0.65)
Italy
1.23 (0.82)
0.72 (0.71)
0.51 (0.30 to 0.71)
0.64 (0.40 to 0.89)
Estonia
1.18 (0.74)
1.08 (0.76)
0.11 (-0.22 to 0.43)
0.14 (-0.29 to 0.59)
Russia
1.24 (0.73)
1.33 (0.59)
-0.09 (-0.56 to 0.37)
-0.13 (-0.77 to 0.43)
Hungary
1.45 (0.66)
0.97 (0.73)
0.48 (0.15 to 0.82)
0.72 (0.08 to 1.23)
Latvia
1.52 (0.66)
1.14 (0.64)
0.38 (0.01 to 0.74)
0.58 (0.03 to 1.16)
Poland
1.40 (0.79)
1.27 (0.68)
0.14 (-0.04 to 0.31)
0.17 (-0.04 to 0.38)
Argentina
1.18 (0.86)
0.97 (0.66)
0.22 (-0.14 to 0.57)
0.26 (-0.11 to 0.58)
Lithuania
1.41 (0.67)
1.21 (0.59)
0.20 (0.00 to 0.40)
0.31 (0.04 to 0.59)
Serbia
1.63 (0.71)
1.24 (0.80)
0.40 (-0.04 to 0.84)
0.55 (-0.24 to 1.18)
Kosovo
1.58 (0.53)
1.34 (0.68)
0.25 (-0.06 to 0.55)
0.44 (-0.13 to 1.15)
All
1.09 (0.78)
0.76 (0.70)
0.33 (0.28 to 0.38)
0.43 (0.37 to 0.49)
aCohen's D with bias-corrected 95% confidence intervals (CIs) from bootstrapping (1,000 replications). SD, standard deviation; UAE, United Arab Emirates.
DAS28: differences between females and males by country
Female,
mean (SD)
Male,
mean (SD)
Difference,
mean (95% CI)
Effect sizea
(95% CI)
Netherlands
3.07 (1.19)
3.03 (1.37)
0.03 (-0.26 to 0.33)
0.03 (-0.23 to 0.29)
Finland
3.37 (1.35)
3.01 (1.60)
0.37 (0.01 to 0.73)
0.26 (-0.03 to 0.55)
USA
3.59 (1.56)
2.65 (1.61)
0.94 (0.54 to 1.35)
0.60 (0.31 to 0.85)
Greece
3.52 (1.49)
2.72 (1.37)
0.79 (0.40 to 1.19)
0.55 (0.28 to 0.80)
Denmark
3.49 (1.41)
3.05 (1.53)
0.44 (0.05 to 0.83)
0.31 (0.03 to 0.60)
Spain
3.59 (1.38)
3.33 (1.31)
0.26 (-0.10 to 0.62)
0.19 (-0.07 to 0.45)
France
3.69 (1.41)
3.56 (1.74)
0.13 (-0.24 to 0.49)
0.09 (-0.22 to 0.36)
Sweden
3.83 (1.58)
3.80 (1.62)
0.04 (-0.40 to 0.48)
0.02 (-0.24 to 0.30)
UK
4.09 (1.41)
3.56 (1.34)
0.53 (-0.04 to 1.11)
0.39 (-0.05 to 0.74)
Ireland
4.16 (1.51)
4.03 (1.86)
0.13 (-0.32 to 0.57)
0.08 (-0.25 to 0.34)
Canada
4.13 (1.57)
4.17 (1.88)
-0.04 (-0.88 to 0.79)
-0.03 (-0.60 to 0.57)
Turkey
4.16 (1.43)
4.12 (1.27)
0.05 (-0.44 to 0.54)
0.03 (-0.28 to 0.37)
Brazil
4.25 (1.41)
3.66 (1.52)
0.59 (-0.25 to 1.42)
0.42 (-0.20 to 1.08)
UAE
4.33 (1.72)
3.83 (1.90)
0.50 (-0.25 to 1.24)
0.29 (-0.20 to 0.72)
Germany
4.47 (1.63)
3.84 (1.97)
0.64 (0.03 to 1.25)
0.38 (-0.00 to 0.79)
Italy
4.51 (1.24)
4.38 (1.37)
0.13 (-0.22 to 0.48)
0.10 (-0.17 to 0.42)
Estonia
4.70 (1.43)
4.53 (1.83)
0.16 (-0.50 to 0.83)
0.11 (-0.37 to 0.63)
Russia
4.89 (1.46)
5.33 (0.86)
-0.44 (-1.40 to 0.51)
-0.32 (-0.82 to 0.19)
Hungary
5.13 (1.23)
4.51 (1.24)
0.61 (0.00 to 1.23)
0.50 (0.02 to 1.07)
Latvia
5.24 (1.59)
5.11(1.41)
0.13 (-0.78 to 1.03)
0.08 (-0.49 to 0.68)
Poland
5.32 (1.44)
5.20 (1.43)
0.12 (-0.22 to 0.45)
0.08 (-0.15 to 0.32)
Argentina
5.35 (1.68)
5.36 (1.95)
-0.02 (-0.76 to 0.72)
-0.01 (-0.48 to 0.54)
Lithuania
5.49 (1.30)
5.51 (1.30)
-0.02 (-0.43 to 0.38)
-0.02 (-0.34 to 0.30)
Serbia
5.93 (1.30)
5.93 (0.97)
-0.01 (-0.78 to 0.77)
-0.00 (-0.45 to 0.51)
Kosovo
6.08 (0.95)
5.83 (0.99)
0.25 (-0.26 to 0.77)
0.27 (-0.32 to 0.91)
All
4.30 (1.64)
3.76 (1.76)
0.54 (0.43 to 0.65)
0.33 (0.25 to 0.39)
aCohen's D with bias-corrected 95% confidence intervals (CIs) from bootstrapping (1,000 replications). DAS28, disease activity score using 28 joint counts; SD, standard deviation; UAE, United Arab Emirates.
Gender and disease characteristics
RF was equally prevalent among females and males, including 'low' (females 67.2% versus males 69.5%;
Gender and therapies for rheumatoid arthritis
In 'low use' countries, similar percentages of women and men were currently taking prednisone (30.0% versus 31.0%), methotrexate (54.1% versus 54.7%), and biologic agents (7.9% versus 8.1%). Similar proportions of women and men were taking these drugs in 'high use' countries; the percentages were 60.6% versus 61.5% for prednisone, 68.4% versus 72.0% for methotrexate, and 29.1% versus 30.8% for biologic agents, respectively. Similar percentages of women and men had ever taken these drugs over the course of RA (data not shown). The delay between the first RA symptoms and initiation of DMARDs was 10 months in the entire group, with considerable variation between countries (Table
Discussion
Obvious differences between genders exist in the prevalence, age at onset, and autoantibody production of RA
As noted before, the natural history of RA when limited treatment options were available involved severe outcomes in most patients without major gender differences. However, occasional reports of gender differences in RA with unexpected results or interpretations appear to have gained more attention than reports of no gender differences. Ten years ago, a study from the Mayo Clinic
Our results are consistent with the results of recent studies that indicate major gender differences in DAS28 remission rates: overall, 30% of men and 17% of women in QUEST-RA were in DAS28 remission. Differences were striking in patients who had no swollen joints: much fewer women than men (42% versus 58%) met DAS28 remission. At SJC28 levels of 0 to 1, which indicate no or very little clinical disease activity, gender differences were significant both clinically and statistically in all other American College of Rheumatology (ACR) Core Data Set measures and fatigue. On the other hand, gender differences in measures were less pronounced or nonexistent on higher disease activity levels (that is, higher SJC28 counts) (Table
Self-report performance in activities of daily living is a strong predictor of further functional loss, work disability, and mortality in RA, in other conditions, and in the general population
Possible reasons for gender differences in RA have been sought on the basis of sex hormones. Disease activity is ameliorated in 75% of women in pregnancy, and after delivery, flares occur in up to 90%
Radiographs provide a permanent measure of the structural damage of RA, radiographic scores are associated with certain disease activity measures
There is a concern that women might be less likely to be treated aggressively for RA compared with men. A report from The Netherlands indicates a longer delay of referral of females to an early arthritis clinic compared with men
Although QUEST-RA represents a unique program, several limitations are recognized. All data were collected as part of clinical care in different clinical environments and traditions to examine and treat patients, which may vary greatly in the participating countries. First, a central laboratory was not used for blood samples, which instead were analyzed locally. Therefore, for example, normal CRP was reported as '<10' in many clinics and DAS28-CRP cannot be calculated for all patients; CRP values of 0 to 9.9 provide DAS28 results different from CRP = 10, especially on low DAS28 levels approaching criteria for remission. Second, although radiographs were taken of most patients, they were analyzed by treating rheumatologists for erosive or nonerosive disease only, and quantitative scoring was not performed. Third, a cross-sectional database may not be ideal to study gender differences, and longitudinal observations might provide a more accurate picture of gender differences in RA, with follow-up of all long-term outcomes, including mortality. Men tend to die earlier than women and may therefore be 'left-censored' in cross-sectional databases, rendering outcomes for men apparently better. Finally, the QUEST-RA data may not be generalizable in all included (or nonincluded) countries.
Conclusion
QUEST-RA data indicate that currently used disease activity measures are higher in women than in men. Gender differences for DAS28, fatigue, and ACR Core Data Set measures are most pronounced in patients with low swollen joint counts, suggesting that (especially at low levels of disease activity) one has to be cautious about interpretations of gender differences since disease activity measures themselves may be contaminated by gender.
Abbreviations
ACR: American College of Rheumatology; CRP: C-reactive protein; DAS28: disease activity score using 28 joint counts; DMARD: disease-modifying antirheumatic drug; ESR: erythrocyte sedimentation rate; HAQ: Health Assessment Questionnaire; QUEST-RA: Quantitative Standard Monitoring of Rheumatoid Arthritis; RA: rheumatoid arthritis; RF: rheumatoid factor; SJC28: swollen joint count-28; TJC28: tender joint count-28.
Competing interests
One or more authors of this manuscript have received reimbursements, fees, or funding from pharmaceutical companies. The article-processing charge was not received from any of these companies: Abbott (Abbott Park, IL, USA), Allergan (Irvine, CA, USA), Amgen (Thousand Oaks, CA, USA), Bristol-Myers Squibb Company (Princeton, NJ, USA), Chelsea Therapeutics (Charlotte, NC, USA), GlaxoSmithKline (Uxbridge, Middlesex, UK), Jazz Pharmaceuticals (Palo Alto, CA, USA), Merrimack Pharmaceuticals (Cambridge, MA, USA), MSD (Whitehouse Station, NJ, USA), Pfizer Inc (New York, NY, USA), Pierre Fabre Médicament (Boulogne Cedex, France), Roche (Basel, Switzerland), Schering-Plough Corporation (Kenilworth, NJ, USA), sanofi-aventis (Paris, France), UCB (Brussels, Belgium), and Wyeth (Madison, NJ, USA).
Authors' contributions
The QUEST-RA Study was designed and conducted by TS and TPincus. All authors participated in data collection concerning their clinical patients. Analyses for the present report were designed and coordinated by TS and HK. All authors read and approved the final manuscript.
Authors' information
The QUEST-RA Group is composed of the following members: Argentina: Sergio Toloza, Santiago Aguero, Sergio Orellana Barrera, Soledad Retamozo, Hospital San Juan Bautista, Catamarca; Paula Alba, Cruz Lascano, Alejandra Babini, Eduardo Albiero, Hospital of Cordoba, Cordoba; Brazil: Geraldo da Rocha Castelar Pinheiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro; Licia Maria Henrique da Mota, Hospital Universitário de Brasília; Ines Guimaraes da Silveira, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre; Francisco Airton Rocha, Universidade Federal do Ceará, Fortaleza; Ieda Maria Magalhães Laurindo, Universidade Estadual de São Paulo, São Paulo; Canada: Juris Lazovskis, Riverside Professional Center, Sydney, NS; Denmark: Merete Lund Hetland, Lykke Ørnbjerg, Copenhagen Univ Hospital at Hvidovre, Hvidovre; Kim Hørslev-Petersen, King Christian the Xth Hospital, Gråsten; Troels Mørk Hansen, Lene Surland Knudsen, Copenhagen University Hospital at Herlev, Herlev; Estonia: Raili Müller, Reet Kuuse, Marika Tammaru, Riina Kallikorm, Tartu University Hospital, Tartu; Tony Peets, East-Tallinn Central Hospital, Tallinn; Ivo Valter, Center for Clinical and Basic Research, Tallinn; Finland: Heidi Mäkinen, Jyväskylä Central Hospital, Jyväskylä; Kai Immonen, Sinikka Forsberg, Jukka Lähteenmäki, North Karelia Central Hospital, Joensuu; Reijo Luukkainen, Satakunta Central Hospital, Rauma; France: Laure Gossec, Maxime Dougados, University René Descartes, Hôpital Cochin, Paris; Jean Francis Maillefert, Dijon University Hospital, University of Burgundy, Dijon; Bernard Combe, Hôpital Lapeyronie, Montpellier; Jean Sibilia, Hôpital Hautepierre, Strasbourg; Germany: Gertraud Herborn, Rolf Rau, Evangelisches Fachkrankenhaus, Ratingen; Rieke Alten, Christof Pohl, Schlosspark-Klinik, Berlin; Gerd R Burmester, Bettina Marsmann, Charite-University Medicine Berlin, Berlin; Greece: Alexandros A Drosos, Sofia Exarchou, University of Ioannina, Ioannina; H M Moutsopoulos, Afrodite Tsirogianni, School of Medicine, National University of Athens, Athens; Fotini N Skopouli, Maria Mavrommati, Euroclinic Hospital, Athens; Hungary: Pál Géher, Semmelweis University of Medical Sciences, Budapest; Bernadette Rojkovich, Ilona Újfalussy, Polyclinic of the Hospitaller Brothers of St. John of God in Budapest, Budapest; Ireland: Barry Bresnihan, St. Vincent's University Hospital, Dublin; Patricia Minnock, Our Lady's Hospice, Dublin; Eithne Murphy, Claire Sheehy, Edel Quirke, Connolly Hospital, Dublin; Joe Devlin, Shafeeq Alraqi, Waterford Regional Hospital, Waterford; Italy: Massimiliano Cazzato, Stefano Bombardieri, Santa Chiara Hospital, Pisa; Gianfranco Ferraccioli, Alessia Morelli, Catholic University of Sacred Heart, Rome; Maurizio Cutolo, University of Genova, Genova, Italy; Fausto Salaffi, Andrea Stancati, University of Ancona, Ancona; Kosovo: Sylejman Rexhepi, Mjellma Rexhepi, Rheumatology Department, Pristine; Latvia: Daina Andersone, Pauls Stradina Clinical University Hospital, Riga; Lithuania: Sigita Stropuviene, Jolanta Dadoniene, Institute of Experimental and Clinical Medicine at Vilnius University, Vilnius; Asta Baranauskaite, Kaunas University Hospital, Kaunas; The Netherlands: Suzan MM Verstappen, Johannes WG Jacobs, University Medical Center Utrecht, Utrecht; Margriet Huisman, Sint Franciscus Gasthuis Hospital, Rotterdam; Monique Hoekstra, Medisch Spectrum Twente, Enschede; Poland: Stanislaw Sierakowski, Medical University in Bialystok, Bialystok; Maria Majdan, Medical University of Lublin, Lublin; Wojciech Romanowski, Poznan Rheumatology Center in Srem, Srem; Witold Tlustochowicz, Military Institute of Medicine, Warsaw; Danuta Kapolka, Silesian Hospital for Rheumatology and Rehabilitation in Ustron Slaski, Ustroñ Slaski; Stefan Sadkiewicz, Szpital Wojewodzki im. Jana Biziela, Bydgoszcz; Danuta Zarowny-Wierzbinska, Wojewodzki Zespol Reumatologiczny im. dr Jadwigi Titz-Kosko, Sopot; Russia: Dmitry Karateev, Elena Luchikhina, Institute of Rheumatology of Russian Academy of Medical Sciences, Moscow; Natalia Chichasova, Moscow Medical Academy, Moscow; Vladimir Badokin, Russian Medical Academy of Postgraduate Education, Moscow; Serbia: Vlado Skakic, Aleksander Dimic, Jovan Nedovic, Aleksandra Stankovic, Rheumatology Institut, Niska Banja; Spain: Antonio Naranjo, Carlos Rodríguez-Lozano, Hospital de Gran Canaria Dr. Negrin, Las Palmas; Jaime Calvo-Alen, Hospital Sierrallana Ganzo, Torrelavega; Miguel Belmonte, Hospital General de Castellón, Castellón; Sweden: Eva Baecklund, Dan Henrohn, Uppsala University Hospital, Uppsala; Rolf Oding, Margareth Liveborn, Centrallasarettet, Västerås; Ann-Carin Holmqvist, Hudiksvall Medical Clinic, Hudiksvall; Turkey: Feride Gogus, Gazi Medical School, Ankara; Recep Tunc, Meram Medical Faculty, Konya; Selda Celic, Cerrahpasa Medic Faculty, Istanbul; United Arab Emirates: Humeira Badsha, Dubai Bone and Joint Center, Dubai; Ayman Mofti, American Hospital Dubai, Dubai; UK: Peter Taylor, Catherine McClinton, Charing Cross Hospital, London; Anthony Woolf, Ginny Chorghade, Royal Cornwall Hospital, Truro; Ernest Choy, Stephen Kelly, Kings College Hospital, London; USA: Theodore Pincus, Vanderbilt University, Nashville, TN; Yusuf Yazici, NYU Hospital for Joint Diseases, New York, NY; Martin Bergman, Taylor Hospital, Ridley Park, PA; Christopher Swearingen, Medical University of South Carolina, Charleston, SC; Study Center: Tuulikki Sokka, Jyväskylä Central Hospital, Jyväskylä, Medcare Oy, Äänekoski, Finland; Hannu Kautiainen, Medcare Oy, Äänekoski, Finland; Theodore Pincus, New York University Hospital for Joint Diseases, New York, NY, USA.