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Relative contribution of cardiovascular risk factors and rheumatoid arthritis clinical manifestations to atherosclerosis.

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ARTHRITIS & RHEUMATISM
Vol. 52, No. 11, November 2005, pp 3413–3423
DOI 10.1002/art.21397
© 2005, American College of Rheumatology
Relative Contribution of Cardiovascular Risk Factors and
Rheumatoid Arthritis Clinical Manifestations
to Atherosclerosis
Inmaculada del Rincón,1 Gregory L. Freeman,1 Roy W. Haas,1 Daniel H. O’Leary,2
and Agustı́n Escalante1
Objective. To estimate the contribution of cardiovascular (CV) risk factors and rheumatoid arthritis
(RA) disease manifestations to atherosclerosis in RA.
Methods. We used high-resolution carotid ultrasound to measure the carotid intima-media thickness
(IMT) and plaque in 631 RA patients. Using R2 measures from multivariable models, we estimated the
contribution of demographic characteristics (age, sex,
and ethnic group), CV risk factors (diabetes mellitus,
hypercholesterolemia, cigarette smoking, hypertension,
and body mass index, and RA manifestations (joint
tenderness, swelling, and deformity, nodules, erythrocyte sedimentation rate [ESR], C-reactive protein, rheumatoid factor, the HLA–DRB1 shared epitope, and
cumulative glucocorticoid dose) to each of the outcomes.
Estimates were obtained in the full sample, and within
strata defined by age, sex, and ethnic group. We tested
for interaction between CV risk factors and RA manifestations.
Results. The contribution of demographic factors,
CV risk factors, and RA manifestations to IMT and
plaque R2 varied depending on the patients’ age stratum. Demographic features explained 11–16% of IMT
variance, CV risk factors explained 4%–12%, and RA
manifestations explained 1–6%. The greatest contribution of RA manifestations occurred in the youngest age
group, while that of CV risk factors occurred in the
older age groups. Results for carotid plaque were similar. There was a significant interaction between the
number of CV risk factors present and the ESR, suggesting that the ESR’s effect on IMT varied according to
the number of CV risk factors.
Conclusion. Both established CV risk factors and
manifestations of RA inflammation contribute significantly to carotid atherosclerosis in RA, and may modify
one another’s effects. These findings may have implications regarding the prevention of atherosclerosis in RA.
The mechanism underlying the high frequency of
cardiovascular (CV) morbidity that occurs in rheumatoid arthritis (RA) is not completely understood (1–16).
Earlier studies have indicated that the excess CV event
rate in RA is not explained by an excess of established
CV risk factors (17,18). Those studies did not address
whether these risk factors operate similarly in RA as
they do in the general population.
Diabetes mellitus, hypercholesterolemia, hypertension, cigarette smoking, and obesity are powerful
classifiers of CV risk (19). One or more established CV
risk factors are present in at least 80% of people with
symptomatic coronary artery disease in the general
population (20). The prevalence is even higher, approaching 100%, among persons with fatal myocardial
infarction (21).
People with and those without RA have similar
CV risk factor profiles (17,18,22). The resemblance
suggests that established CV risk factors may play an
important role in the CV morbidity that occurs in RA, as
they do in the general population. In earlier studies that
Supported by an Arthritis Investigator award and a Clinical
Science grant from the Arthritis Foundation, and by the NIH (grants
R01-HD-37151, K23-HL-04481, K24-AR-47530, and M01-RR-01346
from the Frederic C. Barter General Clinical Research Center).
1
Inmaculada del Rincón, MD, MS, Gregory L. Freeman, MD,
Roy W. Haas, PhD, Agustı́n Escalante, MD: University of Texas
Health Science Center at San Antonio; 2Daniel H. O’Leary, MD: New
England Medical Center, Boston, Massachusetts.
Address correspondence and reprint requests to Inmaculada
del Rincón, MD, MS, University of Texas Health Science Center at
San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900.
E-mail: delrincon@uthscsa.edu.
Submitted for publication March 10, 2005; accepted in revised
form August 2, 2005.
3413
3414
DEL RINCÓN ET AL
compared the extent of atherosclerosis or CV event
rates between RA patients and controls, there was
adjustment for the potential confounding effect of CV
risk factors (23–27). However, those investigations did
not include attempts to estimate the relative contribution of CV risk factors and RA clinical manifestations to
CV outcomes, nor did they examine how the two
interact. Such information is needed in order to select
the interventions most likely to succeed in retarding
atherosclerosis in RA. In the present study, we estimated the relative contribution to atherosclerosis of the
established CV risk factors and of the clinical manifestations of RA.
PATIENTS AND METHODS
Patients. Between January 1996 and April 2000, we
recruited consecutive patients with RA defined according to
the American College of Rheumatology (formerly, the American Rheumatism Association) 1987 criteria (28), from 6
rheumatology clinics in the San Antonio area. Patients were
enrolled into the Outcome of Rheumatoid Arthritis Longitudinal Evaluation (ÓRALE), a study of the disablement process
in RA. ÓRALE is the parent study from which we recruited
patients for the current analysis. After a baseline evaluation for
ÓRALE enrollment, annual followup assessments were conducted. Between February 2000 and February 2003, all patients were invited for an additional visit to undergo highresolution B-mode carotid ultrasound.
Cardiovascular risk factor assessment. We collected
information on CV risk factors at multiple visits from the time
patients were recruited into the ÓRALE study until the carotid
ultrasound was performed. Hypertension was considered to be
present if there was a physician’s diagnosis in the medical
record or an antihypertensive medication was prescribed, or
from the measured blood pressure throughout the study
(average systolic blood pressure ⱖ140 mm Hg). To assess for
obesity, we measured height and weight at the time of the
arterial assessments and calculated the current body mass
index (BMI) (kg/m2). Diabetes mellitus was considered to be
present if a physician had recorded the diagnosis in the medical
record, if the patient had taken antidiabetic medications
during the course of the study, or if the fasting blood sugar
level at a study visit was ⱖ126 mg/dl. Hypercholesterolemia
was considered to be present if a physician recorded the
diagnosis in the medical record, the patient had ever been
prescribed lipid-lowering medication, or the fasting plasma
cholesterol level measured during a study visit was ⱖ200 mg/dl.
Persons who had ever smoked cigarettes were classified as
current smokers if they continued to smoke, and as former
smokers if they had quit.
Manifestations of rheumatoid arthritis. We assessed
48 joints in each patient for the presence or absence of
tenderness or pain on motion, swelling or deformity, and
subcutaneous nodules (29). Tender and swollen joint counts
obtained during the current and earlier study visits were
averaged in order to capture the effect of these variables over
time. For the deformed joint count, which reflects the extent
of damage accrued over time (29), we used the count obtained
at the time of the arterial assessments. We also noted the
cumulative dose of glucocorticoids received by the patient, as
reported previously (30). Patients were asked whether they
were receiving glucocorticoids and, if so, were asked for the
date they were first prescribed and the dosage currently in use.
Information provided by patients was confirmed from pharmacy and medical records. We estimated the cumulative oral
glucocorticoid dose by multiplying the current daily dosage by
the number of days since glucocorticoid treatment was initiated (30).
Laboratory studies. The erythrocyte sedimentation
rate (ESR) was measured by the Westergren technique.
C-reactive protein (CRP) was measured by nephelometry
(Quest Diagnostics, San Juan Capistrano, CA). Serum rheumatoid factor (RF) was measured by the latex agglutination
technique; patients were considered to be seropositive if any
determination during the study was positive. Total plasma,
high-density lipoprotein, low-density lipoprotein, and very
low-density lipoprotein cholesterol were measured using a
Synchron LX automated system (Beckman Coulter, Fullerton,
CA). Patients were asked to fast overnight before laboratory
testing. Values obtained the same day of the arterial measurements were averaged with values obtained during earlier study
visits, to capture the effect of these variables on the arteries
over time.
HLA–DRB1 typing. We determined whether patients
were positive or negative for the HLA–DRB1 shared epitope
(SE); certain genotypes containing the SE are associated with
RA susceptibility and severity (31–33). DRB1 genotyping was
performed at Bio-Synthesis (Lewisville, TX) using sequencespecific primer–polymerase chain reaction amplification with
Fastype kits (Bio-Synthesis) (34). HLA–DRB1 types were
classified using the 1996 World Health Organization Nomenclature Committee for Factors of the HLA System update (35).
Subjects were classified as being SE positive if they had any of
the following DRB1 subtypes: *0101, *0102, *0401, *0404,
*0405, *0408, *0409, *0410, *1001, *1402, or *1406. The
methods used for DRB1 typing have been described in detail
previously (33).
Carotid ultrasound. One technician performed a duplex scan of the carotid arteries in all patients, according to a
standardized vascular protocol developed for the Multi-Ethnic
Study of Atherosclerosis (36). We used an ATL HDI-3000 high
resolution imaging machine with a L7-4 transducer (Philips,
Bothell, WA). The technician acquired 4 standardized B-mode
images and a Doppler flow measurement from both sides of
the neck. The first image was of the distal common carotid
artery, and the 3 others were centered on the site of maximum
near and far wall thickening in the proximal internal carotid
artery or carotid bulb.
Results were recorded on Super VHS tape and mailed
to a central facility (Ultrasound Reading Center, New England
Medical Center, Boston, MA) for grading of the carotid artery
intima-media thickness (IMT) and carotid plaque. At the
reading center, the images were digitized at 30 frames per
second, and arterial diameter fluctuations with the cardiac
RELATIVE CONTRIBUTION OF CV RISK FACTORS TO ATHEROSCLEROSIS IN RA
Table 1.
3415
Characteristics of 631 RA patients grouped by presence or absence of carotid plaque*
Characteristic
Demographic characteristics
Current age, years
Age at RA diagnosis, years
Women, no. (%)
White, no. (%)
Black, no. (%)
Hispanic, no. (%)
RA manifestations
Disease duration, years
Tender joint count
Swollen joint count
Deformed joint count
Subcutaneous nodules, no. (%)
ESR, mm/hour
CRP, mg/liter
RF positive, no. (%)
HLA–DRB1 SE positive, no. (%)
Cumulative glucocorticoid dose, gm
CV risk factors
Diabetes mellitus, no. (%)
Hypercholesterolemia, no. (%)
Smoking, no. (%)
Never
Past smoker
Current smoker
Hypertension, no. (%)
Systolic blood pressure, mm Hg
Diastolic blood pressure, mm Hg
BMI, kg/m2
Carotid plaque present
(n ⫽ 328)
Carotid plaque absent
(n ⫽ 303)
P
64.5 ⫾ 9.9
48 ⫾ 13
206 (63)
137 (42)
24 (7)
160 (49)
52.1 ⫾ 12.0
40 ⫾ 13
250 (82)
75 (25)
21 (7)
197 (65)
ⱕ0.001
ⱕ0.001
ⱕ0.001
ⱕ0.001
0.8
ⱕ0.001
16.0 ⫾ 11.4
14.5 ⫾ 13.4
4.1 ⫾ 5.0
17.4 ⫾ 12.8
158 (48)
43.4 ⫾ 27.6
17.7 ⫾ 27.0
273 (83)
239 (73)
11.5 ⫾ 15.6
12.0 ⫾ 8.8
13.7 ⫾ 12.3
4.3 ⫾ 4.9
13.9 ⫾ 11.4
135 (45)
38.9 ⫾ 24.3
14.0 ⫾ 17.7
246 (81)
216 (71)
8.7 ⫾ 15
ⱕ0.001
0.5
0.6
ⱕ0.001
0.4
0.03
0.05
0.4
0.6
0.02
79 (24)
213 (65)
42 (14)
137 (45)
0.001
ⱕ0.001
ⱕ0.001
102 (31)
159 (48)
67 (20)
249 (76)
144.0 ⫾ 21.6
76.0 ⫾ 12.2
28.4 ⫾ 5.4
156 (51)
97 (32)
50 (16)
147 (49)
134.2 ⫾ 19.9
74.9 ⫾ 10.9
29.6 ⫾ 7.1
ⱕ0.001
ⱕ0.001
0.2
0.02
* Except where indicated otherwise, values are the mean ⫾ SD. RA ⫽ rheumatoid arthritis; ESR ⫽
erythrocyte sedimentation rate; CRP ⫽ C-reactive protein; RF ⫽ rheumatoid factor; SE ⫽ shared
epitope; BMI ⫽ body mass index.
cycle were observed. Images were selected and read by a single,
certified reader who was blinded with regard to subject characteristics. Carotid plaque was identified as a discrete projection of ⱖ50% from the adjacent wall into the vessel lumen. For
the IMT, we measured end diastole at each of the near and far
walls of the right and left common carotid arteries, and the
anterior oblique, lateral, and posterior oblique views of the
internal carotid artery, for a total of 16 IMT measurements per
subject. The maximal IMT of the common and internal carotid
arteries was obtained by averaging the maximal measurement
from the near and far walls at each projection, from the right
and left sides. Then the composite maximal IMT was calculated by averaging the common and internal carotid maximal
IMT values. The result was 1 IMT value per subject, expressed
in millimeters. The study measurements were made by a single
ultrasonographer and a single reader. However, to assess the
technique’s reliability, the study reader reread 50 images, and
a different reader reread a separate set of 50 images. The
intrareader intraclass correlation coefficient for carotid IMT
was 0.99, and the interreader coefficient was 0.94. For plaque,
the intrareader and interreader kappa statistics were 1.0 and
0.94, respectively.
Statistical analysis. Distributional plots and histograms were examined for abnormal distributions. It was noted
that the carotid IMT distribution was skewed (mean 1.102 mm,
median 0.927, skewness 1.78). Therefore, we conducted a
parallel series of analyses in which the IMT was logtransformed. We compared demographic and clinical characteristics between patients grouped according to the presence of
carotid plaque, using t-tests or chi-square tests. Multivariable
ordinary least squares (OLS) and logistic regression analyses
were used to estimate the association between the measured
variables and the carotid abnormalities.
To measure the relative contribution of demographic
characteristics, CV risk factors, and RA clinical manifestations
to carotid IMT or plaque, we built hierarchical regression
models and examined the coefficient of determination (R2),
adjusted for the number of variables in the model. The initial
model included the demographic variables (age, sex, ethnic
group). We then added alternatively the CV risk factors
(diabetes mellitus, hypercholesterolemia, cigarette smoking
[grouped as current, past, or never], hypertension, and BMI) or
the RA clinical manifestations (disease duration, tender, swollen, and deformed joint counts, subcutaneous nodules, ESR,
RF status, HLA–DRB1 SE status, and cumulative glucocorticoid dose). We used the R2 after dropping variables not
significantly related to the outcome. The increment in R2
(for OLS models) or McFadden’s pseudo-R2 (logistic models)
was tested using Wald’s chi-square (37). The above analyses
were repeated after stratification of the cohort according to
3416
DEL RINCÓN ET AL
Table 2. Multivariable model of factors associated with carotid intima-media thickness in 631 RA patients*
Variable
Linear regression
coefficient
95% confidence
interval
Beta coefficient
P
0.172
0.168
⫺0.235
⫺0.040
⫺0.085
0.141, 0.203
0.136, 0.199
⫺0.311, ⫺0.158
⫺0.116, 0.034
⫺0.216, 0.045
0.431
0.450
⫺0.209
⫺0.040
⫺0.043
ⱕ0.001
ⱕ0.001
ⱕ0.001
0.3
0.2
0.204
0.000
⫺0.002
0.002
⫺0.049
0.015
0.031
⫺0.036
0.010
0.160, 0.248
⫺0.000, 0.003
⫺0.009, 0.005
⫺0.001, 0.004
⫺0.117, 0.019
0.001, 0.029
⫺0.053, 0.117
⫺0.107, 0.033
⫺0.017, 0.037
0.425
0.008
⫺0.023
0.039
⫺0.050
0.078
0.024
⫺0.032
0.016
ⱕ0.001
0.8
0.5
0.3
0.2
0.03
0.4
0.3
0.4
0.153
0.067
0.094
0.185
0.086
⫺0.007
0.068, 0.236
0.002, 0.132
0.021, 0.168
0.092, 0.277
0.012, 0.161
⫺0.34, 0.019
0.119
0.067
0.093
0.143
0.083
⫺0.019
ⱕ0.001
0.04
0.01
ⱕ0.001
0.02
0.5
Demographic characteristics
Age (per 10 years)
Age at RA onset (per 10 years)
Female sex (1 ⫽ yes; 0 ⫽ no)
Hispanic versus white
Black versus white
RA manifestations
RA disease duration (per 10 years)
Tender joint count
Swollen joint count
Deformed joint count
Nodules
ESR (per 10 mm/hour)
RF positive
HLA–DRB1 SE positive
Cumulative glucocorticoid dose (per quartile)
CV risk factors
Diabetes
Hypercholesterolemia
Past smoker (versus never smoker)
Current smoker (versus never smoker)
Hypertension
BMI (per 5 kg/m2)
* Model R2 ⫽ 0.421. Age at onset and RA duration were omitted from the models that included age, and age was omitted from
the models that included age at onset and RA duration. See Table 1 for definitions.
tertiles of age distribution. We also performed stratified analyses according to sex and race/ethnicity, to determine the
extent to which the effect of individual risk factors varied
according to sex or ethnic group. To explore interactions
between the number of CV risk factors and RA manifestations, we generated a variable that contained the number of
CV risk factors present. We then generated product terms
between the number of CV risk factors present and individual
clinical manifestations of RA. We computed variance inflation factor after each multivariable model to determine if
multicolinearity was present (38). All analyses were performed using the Stata 8.2 software package (Stata, College
Station, TX).
RESULTS
The ÓRALE sample included 779 RA patients
recruited into the parent study of the disablement
process in RA. We began the arterial assessments in
February 2000. Sixty-six patients died and 32 moved
away from the San Antonio area before an appointment
could be scheduled. This left 681 patients still eligible to
participate in the arterial assessments. Of these, we
could not establish contact with 17, and 19 declined to
participate. We could not perform the carotid ultrasound on 13 because they were evaluated at their
residence. High-resolution carotid ultrasound was performed on 632 patients (93% of eligible patients). In 1 of
these patients, the carotid image was not of sufficient
quality to obtain an IMT measurement, and this patient
was thus omitted from the analysis. The ÓRALE study
visit at which the carotid ultrasound was performed was
the fifth visit in 3 patients, the fourth in 44, the third in
214, the second in 366, and the first in 4. Joint counts
included in these analyses were averaged per patient
over a mean of 2.5 measurements (range 1–5), ESR was
averaged over a mean of 2.4 measurements (range 1–5),
CRP over a mean of 1.4 measurements (range 1–3), and
blood pressure over a mean of 2.5 measurements (range
1–6). The median amount of time since enrollment in
the ÓRALE longitudinal study of the disablement process in RA was 3.25 years (range 0–7.08 years).
The patients’ characteristics at the time of the
carotid ultrasound are shown in Table 1. Patients were
grouped according to the presence or absence of carotid
plaque. In an unadjusted comparison, the patients with
plaque were significantly older and the frequencies of
male sex and white race were higher. Among the manifestations of RA, longer disease duration, higher deformed joint count, and increased ESR or CRP were
associated with an increased likelihood of carotid
plaque. The cumulative glucocorticoid dose was significantly higher among patients with plaque as well.
RELATIVE CONTRIBUTION OF CV RISK FACTORS TO ATHEROSCLEROSIS IN RA
Table 3.
3417
Multivariable models of factors associated with carotid plaque in 631 RA patients*
Variable
Demographic characteristics
Age (per 10 years)
Age at RA onset (per 10 years)
Female sex (1 ⫽ yes; 0 ⫽ no)
Hispanic (versus white)
Black (versus white)
RA manifestations
RA disease duration (per 10 years)
Tender joint count
Swollen joint count
Deformed joint count
Nodules
ESR (per 10 mm/hour)
RF positive
HLA–DRB1 SE positive
Cumulative glucocorticoid dose (per quartile)
CV risk factors
Diabetes mellitus
Hypercholesterolemia
Past smoker (versus never smoker)
Current smoker (versus never smoker)
Hypertension
BMI (per 5 kg/m2)
Odds ratio
95% confidence Standardized
interval
coefficient
P
2.43
2.39
0.55
0.78
0.97
1.94, 3.05
1.90, 3.00
0.34, 0.89
0.48, 1.24
0.43, 2.21
0.644
0.665
⫺0.150
⫺0.069
⫺0.003
ⱕ0.001
ⱕ0.001
0.01
0.3
0.9
2.90
1.01
0.93
1.00
0.76
1.12
1.22
0.84
1.27
2.10, 3.98
0.99, 1.03
0.92, 1.02
0.97, 1.01
0.49, 1.17
1.02, 1.22
0.71, 2.06
0.53, 1.32
1.06, 1.51
0.613
0.095
⫺0.070
⫺0.014
⫺0.074
0.164
0.041
⫺0.043
0.154
ⱕ0.001
0.1
0.3
0.8
0.2
0.009
0.4
0.4
0.007
1.70
1.65
1.75
2.83
1.98
0.89
1.00, 2.89
1.10, 2.47
1.10, 2.78
1.57, 5.09
1.24, 3.13
0.75, 1.06
0.109
0.136
0.152
0.228
0.182
⫺0.078
0.04
0.01
0.01
0.001
0.004
0.2
* Model McFadden’s pseudo-R2 ⫽ 0.269; receiver operating characteristic area under the curve ⫽ 0.83.
Age at onset and RA duration were omitted from the models that included age, and age was omitted from
the models that included age at onset and RA duration. See Table 1 for definitions.
Among the established CV risk factors, diabetes mellitus, hypercholesterolemia, smoking, and hypertension
were all associated with carotid plaque. Of note, BMI
was inversely associated with plaque in this bivariate
analysis (Table 1).
We tested two groups of multivariable models,
one for the IMT and the other for carotid plaque.
Because of colinearity between them, we included the
ESR and CRP in separate models. Results of the IMT
analysis, obtained using OLS regression, are shown in
Table 2. In this model, age and sex were significantly
associated with the dependent variable. All of the established CV risk factors were associated with the IMT,
with the exception of BMI. Among the RA manifestations, disease duration and ESR were also significantly
associated with the IMT in the multivariable model
(Table 2).
Table 3 displays the results of the second group of
multivariable models, using logistic regression to analyze
the presence of carotid plaque. Factors significantly
associated with plaque in this model closely mirrored
those found in the OLS model for IMT. However, the
cumulative glucocorticoid dose was also associated with
plaque (Table 3).
To estimate the relative contribution of demo-
graphic characteristics, CV risk factors, and RA clinical
manifestations to carotid atherosclerosis, we reapplied
the above models according to a predefined, hierarchical
sequence. The results are shown in Table 4. The initial
models included only demographic factors (age, sex, and
ethnic group). The R2 for this group of variables was
0.36 for IMT and 0.21 for plaque. Next, we added RA
clinical manifestations. This increased the R2 by 0.02 for
IMT and 0.03 for plaque; both of these increases were
statistically significant. We also tested a model that
included demographic characteristics and CV risk factors without RA manifestations. The incremental R2
associated with CV risk factors was 0.05 for IMT and
0.04 for plaque, both statistically significant (Table 4).
The final model included all 3 groups of variables,
(demographic features, CV risk factors, and RA manifestations). The final R2 measures from this “full” model
were 0.42 for IMT and 0.27 for plaque. After the
addition of RA manifestations to a model that included
only demographic features and CV risk factors, the
incremental R2 associated with manifestations of RA
was 0.01 for IMT and 0.02 for plaque (Table 4).
Age in this patient sample ranged from 20 to 90
years, an interval that includes most of the adult lifespan,
and during which most atherosclerosis accrues. This was
3418
DEL RINCÓN ET AL
Table 4. Hierarchical regression models of carotid intima-media thickness and plaque in 631 RA
patients*
Dependent variable
Intima-media
thickness
R2
P†
Pseudo-R2
P†
manifestations
0.36
0.38
0.41
0.42
–
ⱕ0.001
ⱕ0.001
ⱕ0.001
0.21
0.24
0.25
0.27
–
ⱕ0.001
ⱕ0.001
ⱕ0.001
manifestations
0.145
0.205
0.181
0.236
–
ⱕ0.001
0.003
ⱕ0.001
0.063
0.177
0.098
0.189
–
ⱕ0.001
0.01
ⱕ0.001
manifestations
0.109
0.158
0.231
0.265
–
ⱕ0.001
ⱕ0.001
ⱕ0.001
0.028
0.049
0.097
0.108
–
0.008
ⱕ0.001
ⱕ0.001
manifestations
0.159
0.168
0.234
0.240
–
0.005
ⱕ0.001
ⱕ0.001
0.050
0.096
0.084
0.131
–
0.03
0.03
0.01
Model
All ages
Demographics
Demographics ⫹ RA manifestations
Demographics ⫹ CV risk factors
Demographics ⫹ CV risk factors ⫹ RA
Age 21–54 years (lower tertile)
Demographics
Demographics ⫹ RA manifestations
Demographics ⫹ CV risk factors
Demographics ⫹ CV risk factors ⫹ RA
Age 55–65 years (middle tertile)
Demographics
Demographics ⫹ RA manifestations
Demographics ⫹ CV risk factors
Demographics ⫹ CV risk factors ⫹ RA
Age 66–90 years (upper tertile)
Demographics
Demographics ⫹ RA manifestations
Demographics ⫹ CV risk factors
Demographics ⫹ CV risk factors ⫹ RA
Plaque
* Demographics ⫽ age, sex, and ethnic group. RA manifestations ⫽ disease duration, tender, swollen, and
deformed joint counts, nodules, ESR, RF status, HLA–DRB1 SE status, and cumulative glucocorticoid
dose. CV risk factors ⫽ diabetes, hypercholesterolemia, smoking, hypertension, and BMI. See Table 1 for
definitions.
† Statistical significance of the increase in R2 or pseudo-R2 from the baseline model (demographics
alone).
reflected in the large proportion of variance in atherosclerosis explained by the demographic variables. We
thus stratified the sample according to tertiles of age and
repeated the above series of hierarchical models within
the individual age strata. The findings are shown in
Table 4. With age restriction, the variance in IMT
explained by demographic characteristics was between
0.109 and 0.159. Adding CV risk factors without RA
manifestations raised the R2 by 0.036–0.122. Adding RA
manifestations in the absence of CV risk factors raised
the model R2 by 0.009–0.06; in the presence of CV risk
factors, the contribution of RA decreased slightly, to
0.006–0.055. Thus, in these age-stratified models, the
contribution of demographic characteristics declined to
less than half that in the unstratified sample, while the
contribution of CV risk factors and RA manifestations
increased. The logistic regression models for plaque
revealed a pattern similar to that observed in the IMT
models, with RA manifestations explaining up to 0.114
of the variance in plaque in the youngest age group
(Table 4).
Because of the heterogeneity between the sexes
in CV risk factor effects observed in the population, we
were also interested in the extent to which CV risk factor
effects varied between men and women in our RA study
group. These findings are shown in Table 5. Age,
cigarette smoking, and diabetes mellitus displayed a
significantly stronger association with IMT in men than
in women. The effect of RA disease duration, ESR,
hypercholesterolemia, and hypertension did not vary
significantly between men and women. The models for
plaque did not reveal any significant heterogeneity by
sex in the CV risk factor effect. Explained variance of
the multivariable models was similar in men and women
(Table 5).
Hispanic patients were significantly less likely to
have carotid plaque in the unadjusted comparison (Table 1). However, this difference was no longer significant
after age adjustment (Table 3). We sought evidence of
heterogeneity by race/ethnicity in the effect of CV risk
factors. We found that among whites, smoking was
associated with significantly greater IMT than it was
among nonwhites (regression coefficient 0.241 [95%
confidence interval 0.125, 0.358] versus 0.060 [95%
RELATIVE CONTRIBUTION OF CV RISK FACTORS TO ATHEROSCLEROSIS IN RA
3419
Table 5. Association between markers of atherosclerosis and individual risk factors in 631 RA patients grouped by sex*
Men
Dependent variable, risk factor
Intima-media thickness (model R2 0.353 for
men, 0.344 for women)
Age, per 10 years
Age at RA onset, per 10 years
Duration of RA, per 10 years
ESR, per 10 mm/hour
Cumulative glucocorticoid dose, per quartile
Former smoker versus never smoker
Current smoker versus never smoker
Diabetes mellitus versus nondiabetic
Hypercholesterolemia present versus absent
Hypertension
Plaque (model pseudo-R2 0.245 for men, 0.254
for women)
Age, per 10 years
Age at RA onset, per 10 years
Duration of RA, per 10 years
ESR, per 10 mm/hour
Cumulative glucocorticoid dose, per quartile
Former smoker versus never smoker
Current smoker versus never smoker
Diabetes mellitus versus nondiabetic
Hypercholesterolemia present versus absent
Hypertension
Women
Regression
coefficient
or odds ratio†
95%
confidence
interval
Regression
coefficient
or odds ratio†
95%
confidence
interval
P for
interaction‡
0.282
0.260
0.209
0.011
0.005
0.318
0.351
0.264
0.136
0.110
0.233, 0.332
0.210, 0.309
0.151, 0.268
⫺0.010, 0.033
⫺0.004, 0.005
0.150, 0.485
0.163, 0.539
0.109, 0.419
0.020, 0.251
⫺0.063, 0.283
0.144
0.144
0.205
0.016
0.11
0.043
0.142
0.083
0.053
0.098
0.114, 0.175
0.113, 0.175
0.165, 0.246
0.001, 0.030
⫺0.021, 0.042
⫺0.038, 0.123
0.038, 0.245
⫺0.009, 0.176
⫺0.023, 0.127
0.027, 0.170
ⱕ0.001
ⱕ0.001
0.9
0.7
0.8
0.004
0.055
0.049
0.2
0.6
2.64
2.71
2.62
1.11
1.21
4.46
3.91
0.70
1.46
2.18
1.81, 3.84
1.88, 3.89
1.71, 4.02
0.96, 1.28
0.89, 1.66
1.56, 12.83
1.23, 12.40
0.26, 1.87
0.69, 3.08
0.94, 5.07
2.57
2.42
3.10
1.11
1.29
1.42
2.64
1.87
1.88
1.70
2.03, 3.26
1.93, 3.03
2.32, 4.14
1.02, 1.21
1.06, 1.57
0.87, 2.32
1.46, 5.22
1.06, 3.29
1.19, 2.96
1.07, 2.71
0.9
0.6
0.5
0.9
0.7
0.055
0.6
0.09
0.6
0.9
* Multivariable linear or logistic regression models that included a sex ⫻ risk factor product term were tested. One model was tested per risk factor.
Age at onset and RA duration were omitted from the models that included age, and age was omitted from the models that included age at onset
and RA duration. All other models included ESR, cumulative glucocorticoid dose, smoking status, diabetes, hypercholesterolemia, and hypertension
as covariates. See Table 1 for definitions.
† Values for intima-media thickness are regression coefficients; values for carotid plaque are odds ratios.
‡ Statistical significance of the difference between men and women in the size and direction of the regression coefficient or odds ratio.
confidence interval ⫺0.018, 0.137]), and diabetes mellitus was associated with a greater difference in IMT in
whites than in nonwhites (regression coefficient 0.382
[95% confidence interval 0.210, 0.554] versus 0.072 [95%
confidence interval ⫺0.018, 0.162]). In the case of
carotid plaque, we found similar variation between
whites and nonwhites in the effect of cigarette smoking,
but not in the effect of diabetes mellitus. The effect of
other CV risk factors on IMT or plaque did not vary
significantly between whites and nonwhites. The R2 of
the IMT model in whites was 0.368; in nonwhites, it was
0.415. In the plaque models, the pseudo-R2 was 0.297 in
whites and 0.250 in nonwhites.
We estimated the effect of the presence of multiple CV risk factors in combination with the 2 RA
manifestations that were found to be significantly associated with carotid ultrasound findings in the multivariable models of both plaque and IMT, i.e., ESR and
disease duration. First, we generated a variable for the
number of CV risk factors associated with the carotid
outcomes that were present in each patient. These
included diabetes mellitus, hypercholesterolemia, hypertension, and current or past smoking (Tables 2 and 3).
We chose these variables because they were significantly
associated with both carotid outcomes. We then generated product terms for the number of CV risk factors
present ⫻ ESR or disease duration. We found that the
product term for the number of CV risk factors ⫻ ESR
was significantly associated with the carotid IMT (P ⫽
0.03). This suggested that the effect of ESR on IMT
varied according to the number of CV risk factors. We
then tested the ESR–IMT association within strata
defined by the number of CV risk factors. This revealed
that the association of ESR with IMT was significant
only when CV risk factors were present, and not in the
absence of CV risk factors. Figure 1 shows the age- and
sex-adjusted mean IMT and plaque probabilities, with
stratification by ESR quartile and number of CV risk
factors. Variance inflation factors were ⬍10 for all
variables tested in the multivariable models, indicating
3420
DEL RINCÓN ET AL
Figure 1. Age- and sex-adjusted mean carotid intima-media thickness
(IMT) and probability of carotid plaque, as functions of the number of
cardiovascular (CV) risk factors and erythrocyte sedimentation rate
(ESR) quartiles (mm/hour). The number of CV risk factors and the
ESR were each significantly associated with both dependent variables
(P for trend ⱕ 0.001 for each). There was a significant interaction
between the ESR and the number of CV risk factors (P for the product
term ESR ⫻ number of CV risk factors ⱕ 0.001). The interaction
suggested that the ESR’s effect on IMT varied according to the
number of CV risk factors. In the case of carotid plaque, the ESR’s
effect was significant, without evidence of interaction.
that there was no significant multicolinearity between
the variables we tested.
DISCUSSION
CV morbidity and mortality in RA occur at rates
greater than would be expected from the profile of
established CV risk factors (17,18,39). This has stimulated interest in identifying the additional risk factors
that may explain the excess seen in RA. A number of
potential markers have indeed been linked to atherosclerosis and CV events in RA, including molecules
involved in the immune response, markers of inflammation, and therapeutic agents (23–27,40–42). However, it
should be noted that the great majority of CV events in
the general population are attributable to established
CV risk factors (20,21). A similar connection between
the established risk factors and CV disease may prevail
in RA, with novel risk factors accounting only for the
proportion that exceeds the expected risk. An important
first step in evaluating this possibility is to establish the
extent to which the atherosclerotic burden in RA is
explained by the established CV risk factors.
We used a hierarchical modeling approach to
address this question. We focused on the coefficient of
determination, or R2, as a measure of the proportion of
variance in atherosclerosis explained by the independent
variables or predictors. We tested variables grouped a
priori as demographic variables (age, sex, and ethnic
group), CV risk factors (diabetes mellitus, hypercholesterolemia, smoking, hypertension, and obesity), and RA
clinical manifestations (RA duration, joint examination
findings, subcutaneous nodules, RF, ESR, CRP, HLA–
DRB1 SE, and cumulative glucocorticoid dose). This
technique permitted us to model these variables
grouped according to our predefined criteria, rather
than through an automatic stepwise approach. Thus, we
were able to estimate the aggregate contribution of the
established CV risk factors separately from that of the
RA manifestations. The disadvantage of this approach is
that the contribution of individual variables can be
considered only in combination with other variables in
the group being tested.
We found that most of the variability in carotid
atherosclerosis was explained by demographic characteristics. This should not be surprising. Age is the major
contributor to the extent of atherosclerosis in the population (43,44). Our sample included patients whose age
varied from 20 years, when little or no atherosclerosis
would be expected, to 90 years, when maximal accrual of
atherosclerosis would be expected. In the general population, the difference in IMT between young and old
persons is greater than the difference between old
persons with and those without coronary artery disease
(45,46).
Results of the age-stratified models shown in
Table 4 suggested that a substantial portion of the
variance in atherosclerosis is explained by risk factors
that may be potentially modifiable. The RA manifestations were most strongly associated with atherosclerosis
in the youngest age group, where they explained 6% of
RELATIVE CONTRIBUTION OF CV RISK FACTORS TO ATHEROSCLEROSIS IN RA
IMT variance and 11.4% of plaque variance over that
explained by demographic characteristics. In this age
group, CV risk factors explained only 3.6% and 3.5% of
the variance in IMT and plaque, respectively, over
demographic factors. After accounting for demographic
and CV risk factors, RA manifestations still explained
5.5% of the IMT variance and 9.1% of that of plaque.
The proportion of atherosclerosis explained by RA
manifestations decreased in the older age groups, suggesting that the systemic inflammation of RA exerts its
effect early. This notion is supported by the observation
of an increased CV event rate in RA patients prior to
disease diagnosis (39). In contrast, the proportion of
atherosclerosis variance explained by the established CV
risk factors was greater in the older age groups, surpassing the effect of the RA manifestations. Thus, the
established CV risk factors seemed to lag behind systemic inflammation in the time course of their effect, but
ultimately had effects that were quantitatively stronger.
It is noteworthy that the number of CV risk
factors present in each patient had an additive effect on
carotid atherosclerosis, displaying a biologic gradient, or
“dose-response” effect: the greater the number of CV
risk factors, the greater the extent of atherosclerosis
(Figure 1). We also noted a potentially important effect
modification: higher ESR values were associated with
greater IMT only in the presence of CV risk factors. In
the patients who did not have any CV risk factors, the
ESR was not significantly associated with IMT. This
suggests that inflammation provides positive modulation
of the established risk factors, but is likely not sufficient
to cause the disease independently. It was not possible to
discern the biologic substrate of this interaction in the
present study. It is possible that fibrinogen, the concentration of which primarily determines the ESR, may
accelerate the atherogenic effects of the other CV risk
factors (47). In vitro studies targeting these interactions
would be of great interest.
Of interest, body mass was not associated with
the IMT or plaque in this RA cohort. In the general
population, obesity is a major predictor of atherosclerosis and CV events (48). Its lack of association with the
carotid IMT or plaque in the present study is consistent
with the finding of a paradoxical effect of body mass on
CV and all-cause mortality in RA (49,50).
Some caution in interpreting our findings is warranted. The outcome measures we used, obtained with
high-resolution carotid ultrasound, are markers of subclinical atherosclerosis, not of clinically verified disease
(51). However, their clinical relevance is underscored by
3421
their ability to identify individuals at high risk of atherosclerotic complications such as myocardial infarction or
stroke (43,52). Moreover, carotid and coronary atherosclerosis are highly correlated, and thus, findings in the
carotid arteries likely reflect findings in the coronary
arteries (53). Ultrasound and histologic images of the
IMT correlate highly as well (54). When performed by a
single sonographer using an established protocol, and
read by a single expert reader, as in this study, the
technique is reliable. Thus, our findings likely reflect
clinically significant CV risk.
Atherosclerosis is a process that takes place over
time, as is the effect of the risk factors we tested. The
cross-sectional nature of this study may have limited our
ability to fully capture the temporal relationships in the
atherosclerosis process. To counteract this potential
limitation, we used time-averaged values for the ESR, in
an effort to capture the effect of this variable over time.
With certain exposure variables, it was also possible to
generate indicators that reflected a change in status over
time. Thus, we considered current cigarette smokers
separately from those who had smoked in the past but
quit. We found that indeed, current smokers had a
greater IMT than did past smokers, consistent with the
notion that those who stop smoking ultimately develop
less atherosclerosis. Both smoker groups, however, had
worse findings on carotid ultrasound than did nonsmokers.
We also disaggregated chronological age into two
variables, age at RA onset and disease duration. This
avoids counting the disease duration twice, as would
occur if the full chronological age is included together
with disease duration in the same model. It is of interest
that both the regression coefficient and the odds ratio
for disease duration were greater than those for age at
disease onset. This could suggest that the slope for
increase of atherosclerosis over time was steeper during
the years that patients had RA. Longitudinal data are
needed to thoroughly explore this possibility.
Our findings suggest that, after accounting for
the effects of age and sex, both established CV risk
factors and RA manifestations account for a significant
proportion of atherosclerosis in RA. Factors related to
RA may have a greater influence on the extent of
atherosclerosis in young patients. The presence of established CV risk factors may be necessary for systemic
inflammation to promote atherosclerosis. Further research is needed to understand the mechanisms whereby
established CV risk factors and inflammation markers
interact in the atherogenic process.
3422
DEL RINCÓN ET AL
ACKNOWLEDGMENTS
We thank Drs. Ramón Arroyo, Dan Battafarano, Rita
Cuevas, Michael Fischbach, John Huff, Alex de Jesus, Rodolfo
Molina, Matthew Mosbacker, Fred Murphy, Carlos Orces,
Christopher Parker, Thomas Rennie, Jon Russell, Joel Rutstein, and James Wild for allowing us to study their patients.
20.
21.
22.
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