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The Open Rheumatology Journal, 2012, 6, 303-309 303
1874-3129/12 2012 Bentham Open
The Effect of Stopping Smoking on Disease Activity in Rheumatoid
Arthritis (RA). Data from BARFOT, a Multicenter Study of Early RA
Maria L.E. Andersson*,1, Stefan Bergman1,2 and Maria K. Söderlin 1 for the BARFOT Study Group§
1R&D Center, Spenshult Rheumatology Hospital, 313 92 Oskarström, Sweden
2Department of Rheumatology, IKVL, Lund University, Lund, Sweden
Abstract: Objective: We studied the effect of stopping smoking on disease activity in patients with RA.
Methods: Between 1992 and 2005, 2,800 adult patients were included in the BARFOT early RA study in Sweden. Disease
Activity Score 28 joints (DAS28), C-reactive protein (CRP), Health Assessment Questionnaire (HAQ), rheumatoid factor
(RF), anti-CCP, general health and pain visual analog scales (VAS), EULAR response and treatment were registered at
inclusion and at follow-up 2, 5 and 8 years. In 2010, a self-completion postal questionnaire was sent to 2,102 patients,
enquiring about lifestyle factors, including cessation of smoking.
Results: A total of 1,460 adult RA patients with disease duration ? 2 years were included in this study. Seventeen percent
smoked in 2010. In total, 127 patients stopped smoking after inclusion in the study. Smoking cessation after inclusion in
the study was negatively associated with EULAR good outcome at 8 years (OR 0.44, 95% CI 0.22–0.86, p=0.02),
controlled for age, disease duration, sex, socioeconomic class, smoking status, RF, and DAS28 at inclusion.
Conclusion: Seventeen percent of the RA patients smoked in 2010 in this large Swedish RA cohort. Stopping smoking
after onset of RA did not change the poor prognosis of smokers with RA, but all RA patients need to stop smoking
because of the high risk of cardiovascular mortality and morbidity and the association of smoking with vasculitis and
noduli in RA.
Keywords: Smoking, cessation of smoking, stopping smoking, rheumatoid arthritis, epidemiology.
disease of the joints leading, if untreated, to permanent joint
destruction. Smoking has been identified as the major
environmental agent causing RA, interacting with anti-CCP
antibodies, shared epitope and the gene PTPN22 .
Smoking has also been shown to be a risk factor for poor
response in RA patients treated with disease-modifying anti-
rheumatic drugs (DMARDs) [2-7] and with anti-tumor
necrosis factor (anti-TNF) treatment [8-12].
Rheumatoid arthritis (RA) is a chronic inflammatory
in the US did not show any effect of stopping smoking after
inclusion in the registry . A study from the German
Early Arthritis Cohort showed that RA patients who stopped
smoking after onset of disease had highest DAS28 (Disease
Activity Score 28, joints; www.das-score.nl), highest
baseline CRP (C-reactive protein) levels, highest ESR
A recently published study from the CORRONA registry
*Address correspondence to this author at the R&D Center, Spenshult
Rheumatology Hospital, 313 92 Oskarström, Sweden;
Tel: +46-35-2635000; Fax: +46-35-2635255;
§Members of the BARFOT study group: Sofia Ajeganova, Maria
Andersson, Valentina Bala, Stefan Bergman, Kristina Forslind, Ingiäld
Hafström, Catharina Keller, Ido Leden, Bengt Lindell, Ingemar Petersson,
Christoffer Schaufelberger, Björn Svensson, Maria Söderlin, Annika
Teleman, Jan Theander, and Anneli Östenson.
(erythrocyte sedimentation rate) values, most severe pain,
and the highest number of comorbid conditions as compared
to current smokers, previous smokers, and those who had
never smoked . We have previously reported that 20% of
patients with early RA smoked in 2004, in this same cohort
, but the current prevalence of smoking in Swedish RA
patients is not known.
after onset of RA had any effect on disease activity in a large
multicenter longitudinal observational study of RA patients
in southern Sweden (the BARFOT study). Our hypothesis
was that the patients who stopped smoking after onset of RA
would have lower disease activity and better function than
patients who continued smoking. We also wanted to
determine whether the time point of stopping smoking before
inclusion in the study had any effect on disease activity at
Our aim was to determine whether stopping smoking
of age were enrolled in the BARFOT (Better Anti-
longitudinal observational study of patients with early RA in
southern Sweden [2, 15-17]. All the patients fulfilled the
American College of Rheumatology RA classification
criteria from 1987 .
During the period 1992–2005, 2,800 patients > 18 years
study, a multicenter
enrolment in the study) and at 2, 5 and 8 years. The number
Disease activity was evaluated at inclusion (i.e. at the
304 The Open Rheumatology Journal, 2012, Volume 6 Andersson et al.
of swollen joints (28-joint count) (SJC), number of tender
joints (28-joint count) (TJC), CRP, ESR, the Swedish
version of the Stanford Health Assessment Questionnaire
(HAQ) [19, 20], and visual analog scale (VAS) for pain and
general health were measured on every follow-up occasion.
The Disease Activity Score using 28-joint count (DAS28)
was calculated at inclusion and on every follow-up occasion
(www.das-score.nl). Anti-rheumatic treatment in this study
was recorded as DMARDs (disease-modifying antirheumatic
drugs, that is non-biologics), biologics and glucocorticoids
and was registered at each follow-up point. The disease
duration was calculated from the start of the symptoms. In
this study, patients had to have disease duration of ? 2 years
at inclusion to be enrolled in the study.
number of swollen joints (of 28), tender joints (of 28), ESR,
and the patient’s global assessment . EULAR (European
League Against Rheumatism) response was calculated from
the DAS28 scores . The patients were classified into one
of three EULAR response groups: no response, moderate
response, or good response. A EULAR good responder had
to demonstrate an improvement of at least 1.2 units and
achieve an absolute score of < 3.2. A non-responder should
show an improvement of < 0.6, or > 0.6 and ? 1.2, and have
a final DAS28 of > 5.1 (www.das-score.nl). EULAR
response was analysed at 1, 2, 5 and 8 years of follow-up.
The choice of DMARD treatment in the BARFOT study was
left to the discretion of the rheumatologist. Serum antibodies
to cyclic citrullinated peptide were analyzed using the
Immunoscan-RA ELISA CCP2 test (Euro-Diagnostica,
Malmö, Sweden). A titer above 25 units/ml was regarded as
The DAS28 is a composite score consisting of the
Self-Completion Postal Questionnaire in 2010
were still alive in the BARFOT study (n = 2102) received a
self-completion postal questionnaire assessing smoking
habits, smoking cessation, pack-year data, snuff use, second-
hand smoke exposure, alcohol use, diet, pain, medication,
comorbidities, height, weight, waist circumference, ADL
function, and physical activity. Demographics such as
occupation and immigrant status were also recorded. The
occupations were coded according to the latest version of the
socioeconomic status (Socioekonomisk indelning, SEI) in
Sweden. The socioeconomic status was assessed as manual
worker, lower white-collar worker, upper white-collar
worker, self-employed, and other according to the SEI.
Between March and September 2010, all patients who
to assess smoking retrospectively and also in a cross-
sectional manner in 2010, enabling us to calculate the current
prevalence of smoking in that year in the BARFOT study.
The questions “Are you a smoker?” “What year did you start
smoking?” “What year did you stop smoking?” “How many
cigarettes do you/did you smoke per day?” permitted the
calculation of pack-years (one pack-year is consumption of
20 cigarettes a day for one year). All the patients received
written information about the questionnaire in 2010, and the
ethical committee at Lund University approved the
BARFOT study and the postal questionnaire in 2010.
The 2010 self-completion postal questionnaire enabled us
response at inclusion and at 2, 5 and 8 years of follow-up,
Our primary objective in the study was to study EULAR
and our secondary objectives were to study the absolute
DAS28 values, the individual components of the DAS28,
and the HAQ stratified according to smoking class at the
same follow-up points.
as appropriate. The Kruskall-Wallis test was used to assess
demographics and disease activity between the patients who
had never been smokers, those who were current smokers,
and those who had stopped smoking before and after
inclusion in the study. Post hoc analyses using standardized
residuals were used to detect differences in EULAR
response, stratified for the different smoking categories.
Spearman’s correlation coefficient was used to assess
correlation between year of stopping smoking before
inclusion and disease activity at inclusion. For the EULAR
response at 2, 5 and 8 years, only the patients who had
stopped smoking before these time points in the “stopped
smoking after inclusion”
The Mann-Whitney U-test and chi-square test were used
category were analysed,
whether smoking cessation after inclusion in the study was
an independent factor for EULAR response. The outcome of
the regression analysis was good vs moderate or no EULAR
response at 8 years of follow-up. The following variables
were entered into the multiple logistic regression model at
inclusion: age, disease
socioeconomic class (manual worker, lower or upper white-
collar worker, self-employed, other), smoking class (never
smoker, current smoker, stopped smoking before or after
inclusion), RF, and DAS28 at inclusion. In this analysis,
patients who had stopped smoking > 7 years after inclusion
were excluded (n = 42). The variables entered in the
regression analysis were checked for colinearity.
A multiple logistic regression analysis was used to assess
duration (months), sex,
completion postal questionnaire in 2010. Of these, 1,460
patients were > 18 years of age and had disease duration of ?
2 years, and these patients were included in this study. The
demographic and disease activity data at inclusion in the
study for the 1,525 patients who answered the self-
completion postal questionnaire in 2010 and the 579 patients
who did not answer are shown in Table 1. In summary,
patients who did not answer the questionnaire had higher
DAS28, higher VAS global, and higher SJC at inclusion and
they were more often smokers but less often RF positive than
the patients who had answered the 2010 questionnaire.
A total of 1,524/2,102 (73%) patients answered the self-
response data, and the figures were 1,285, 1,342, 1,319,
1,295, and 795 for follow-up points 6 and 12 months and 1,
2, 5, and 8 years, respectively. A total of 160 patients (11%)
had EULAR response data at 15 years. Altogether,
659/1,460 patients (45%) had complete data on EULAR
response at each follow-up point up to 8 years of follow-up.
The 659 patients who had complete data did not differ
significantly from the 801 patients (55%) who did not have
complete EULAR response follow-up data at baseline
regarding HAQ (p = 0.59), VAS pain (p = 0.52), VAS global
At 3 months, 1,381 patients had complete EULAR
The Effect of Stopping Smoking on Disease Activity in RA The Open Rheumatology Journal, 2012, Volume 6 305
(p = 0.29), CRP (p = 0.37), ESR (p = 0.17), and SJC (p =
0.97), but the patients who had complete data had
significantly lower DAS28 at baseline (median 5.2 for
complete data vs 5.3 for incomplete data (p = 0.005)) and
had a lower median number of TJC (7 for complete vs 8 for
incomplete (p = 0.01)).
Fig. (1) shows the flow chart of the study.
Table 1. Disease Activity Variables and Demographics at Inclusion in the Study for the Patients who Answered and Did Not
Answer the 2010 Postal Questionnaire. Values are Median (Interquartile Range) Unless Otherwise Stated
Answered the 2010 Postal Questionnaire,
Baseline at Inclusion in the Study
Did Not Answer the 2010 Postal Questionnaire,
Baseline at Inclusion in the Study
Variable N = 1525 N = 579
Age, years 56 (47-65) 58 (42-70) 0.06
Female, % 70 68 0.32
HAQ 0.9 (0.5-1.4) 1.0 (0.5–1.5) 0.25
DAS28 5.3 (4.4-6.1) 5.4 (4.6-6.2) 0.01
VAS global, mm 46 (24–63) 49 (27–67) 0.008
VAS pain, mm 46 (28–65) 49 (29–68) 0.09
Number of swollen joints (of 28) 10 (6–14) 10 (6–15) 0.03
Number of tender joints (of 28) 7 (3–12) 8 (4–13) 0.06
ESR 28 (15–46) 28 (16–49) 0.49
CRP 16 (9–39) 17 (9–43) 0.13
Number of ongoing DMARDs, % 80% 80% 0.37
Ongoing glucocorticoids, % 36 39 0.14
Smoker,% 24 30 0.01
RF, % 63 58 0.02
HAQ = Health Assessment Questionnaire, VAS = visual analog scale, DMARDs = disease-modifying anti-rheumatic drugs, DAS28 = Disease Activity Score (28 joints), ESR =
erythrocyte sedimentation rate, CRP = C-reactive protein, RF = rheumatoid factor.
Fig. (1). The flow chart of the study.
n=490 (at inclusion)
n=15 (< 2 years after inclusion)
2 year follow up
n=490 (at inclusion)
n=54 (< 5 years after inclusion)
5 year follow up
n=490 (at inclusion)
n=84 (< 8 years after inclusion)
8 year follow up
306 The Open Rheumatology Journal, 2012, Volume 6 Andersson et al.
received glucocorticoids as compared to 43% of the patients
with complete data (p = 0.0001), and these differences
persisted for up to 2 years of follow-up (data not shown).
The patients with incomplete data had more often received
DMARDs at baseline and had more often received
combination treatment and biologics during the follow-up.
These differences persisted for up to 5 years (data not
At baseline, 31% of the patients with incomplete data
smoked, 490/1362 (36%) had smoked previously, and
231/1362 (17%) were current smokers in the questionnaire in
2010. 98 patients had missing data on smoking in 2010. A
total of 127 patients stopped smoking either during the year
of inclusion or after inclusion in the BARFOT study. Three
patients stopped smoking after 15 years of follow-up. There
were no differences in baseline disease activity variables
between the patients who stopped smoking before and after
inclusion in the study, current smokers, and those who had
never smoked (HAQ, p = 0.64; DAS28, p = 0.69; VAS pain,
p = 0.26; VAS global, p = 0.78; CRP, p = 0.07; ESR, p =
0.35; SJC, p = 0.06; TJC, p = 0.29).
A total of 514/1362 (38%) of the patients had never
Treatment with DMARDs and Biologics
biologics and glucocorticoids) was recorded at the follow-up
visits. The patients were mainly treated with DMARDs, that
is to say non-biologics. The proportion of patients with no
DMARD treatment ranged from 21% at inclusion to 34% at
15 years of follow-up. The proportion of patients with
DMARD monotherapy diminished from 77% at inclusion to
36% at 15 years, and the proportion of patients with
combination treatment varied from 1.6% at inclusion to 12%
at 15 years. The proportion of patients treated with biologics
increased from 0.4% at inclusion to 23% at 15 years. The
proportion of glucorticoid treatment varied from 23% to
Anti-rheumatic treatment (ie. DMARDs (non-biologics),
glucocorticoid treatment between the different smoking
categories for up to 15 years of follow-up, with 3 exceptions.
One exception was glucocorticoid treatment at 5 years,
where 19% of those who had never smoked did not receive
glucocorticoids as compared to 22% of current smokers,
25% of patients who had stopped smoking before inclusion,
and 29% who stopped smoking after inclusion (p = 0.04).
Another exception was DMARD treatment at 8 years, where
32% of never-smokers did not receive DMARDs as
compared to 19% of smokers, 19% of the patients who
stopped smoking before inclusion, and 27% of the patients
who stopped smoking after inclusion (p = 0.04). The third
exception was glucocorticoid treatment at 8 years;18% of
never-smokers did not receive glucocorticoids, as opposed to
24% of current smokers, 27% of the patients who had
stopped smoking before inclusion, and 32% of the patients
who stopped smoking after inclusion (p = 0.01).
There were no differences in DMARD treatment or
The Effect of Cessation of Smoking After Inclusion on
between never-smokers, current smokers, and patients who
had stopped smoking before or after inclusion—in HAQ, in
We could see no clear differences in disease activity
VAS pain, in DAS28 (Fig. 2), or in any of its individual
variables for up to 8 years of follow-up. Fig. (2). Looking
separately at the individual components of the DAS28, the
absolute DAS28 values and HAQ at 2, 5 and 8 years for
patients who had stopped smoking before these follow-up
points, respectively, as compared to the other smoking
classes, there was only a significant difference in CRP at 2
years of follow-up, where non-smokers had a CRP of 10,
smokers 11, patients having stopped smoking before
inclusion 11 and patients having stopped smoking < 2 years
after inclusion 12 (p=0.03).
Fig. (2). Mean DAS28 (with 95% CI) at up to 5 years of follow-up,
stratified according to smoking status.
at 2, 5 or 8 years of follow-up between the different smoking
categories (data not shown). This did not change after
stratification according to gender.
There were no statistical differences in EULAR response
Multiple Logistic Regression Analysis
was EULAR good vs no or moderate response at 8 years (n =
560). The patients who had stopped smoking >7 years from
inclusion were excluded in this analysis. Cessation of
smoking after inclusion in the study was independently
associated with a poor prognosis (OR 0.44, 95% CI 0.22–
0.86, p = 0.02) (Table 2). Male sex and higher DAS28 were
independently associated with a better prognosis, and RF
positivity and the SEI class “Other” were independently
associated with poorer prognosis. The results did not change
when including the patients who had stopped smoking > 7
years from inclusion as current smokers, with the exception
that SEI class “Other” was then no longer statistically
The outcome of the multiple logistic regression analyses
Stratification by Anti-CCP Antibody Status
were anti-CCP antibody negative and 226 were anti-CCP
antibody positive). Anti-CCP antibody data were available
for 51 patients who stopped smoking after inclusion in the
study (26 (51%) were anti-CCP negative and 25 (49%) were
anti-CCP positive). With stratification for anti-CCP antibody
status, there were no significant differences in EULAR
We had anti-CCP antibody data on 388 patients (162
Mean DAS 28 CI 95%
Stopped smoking before incl
Stopped smoking < 2 years after incl
The Effect of Stopping Smoking on Disease Activity in RA The Open Rheumatology Journal, 2012, Volume 6 307
response between the different smoking categories at up to 8
years of follow-up (data not shown).
Table 2. Multiple Logistic Regression Analysis with Outcome
EULAR Good vs No or Moderate at 8 Years N= 560
Variable OR 95% CI P
Current smokers 0.62 0.37-1.04 0.07
Smoking cessation before inclusion 0.73 0.48-1.10 0.13
Smoking cessation after inclusion 0.44 0.22-0.86 0.02
Age at inclusion 0.99 0.97-1.00 0.07
Disease duration (months) 0.99 0.94-1.03 0.53
DAS28 1.19 1.03-1.37 0.02
Male sex 2.20 1.44-3.36 0.0001
SEI lower white collar 0.97 0.67-1.41 0.87
SEI upper white collar 0.83 0.40-1.71 0.61
SEI self-employed 0.52 1.12-2.20 0.37
SEI Other 0.25 0.06-0.98 0.047
RF 0.60 0.41-0.87 0.007
The variables were baseline data for RF, age, sex, DAS28, and disease duration.
Smoking and socioeconomic status were assessed from the 2010 questionnaire. The
references for smoking class were never-smokers and for socioeconomic class, manual
workers. The patients who stopped smoking after 7 years after enrolment are excluded
in this analysis.
DAS28 = Disease Activity Score (28 joints), RF = rheumatoid factor, SEI=
Stratification for Pack-Year Status
previous smokers including the patients who had stopped
smoking after inclusion, and 195/231 (84%) of the current
smokers. Regarding EULAR response for heavy smokers (>
20 pack-years), at 2 years, 33% of the heavy smokers who
had stopped smoking after inclusion had no EULAR
response, as did 17% of current heavy smokers and 7% of
heavy smokers who had stopped smoking before inclusion (p
= 0.03). For heavy smokers, stopping smoking after
inclusion was thus associated with poorer prognosis at 2
years of follow-up. For the rest of the pack-year strata (<10
and 10–20 pack-years), there were no statistically significant
differences in EULAR response between the smoking
Pack-year data were available for 507/617 (82%)
Comparison of “Early Stoppers” and “Late Stoppers”
years from inclusion (n = 30) were compared with patients
who stopped smoking > 2 years from inclusion (n = 94).
There were no statistically significant differences in EULAR
response between these categories of smoking cessation up
to 8 years (data not shown). Stratification for pack-years did
not change these results. There was only a statistically
significant difference in absolute DAS28 values between
these two groups at 1 year: mean DAS28 for “early stoppers”
was 3.0 as compared to 3.6 for “late stoppers” (p = 0.04).
The patients who stopped smoking after inclusion but ? 2
The Effect of the Time Elapsed from Cessation of
Smoking Before Inclusion on Disease Activity at
cessation of smoking before inclusion on disease activity at
inclusion. We could not find any effect of the time point at
which the patients stopped smoking before inclusion into the
study on HAQ, VAS scores, DAS28 (Fig. 3), or the
individual variables of DAS28 at inclusion (DAS28: rs =
0.07, p = 0.13; HAQ: rs = 0.07, p=0.12; VAS pain: rs = 0.03,
p = 0.49; VAS global: rs = 0.06, p = 0.22; CRP: rs = 0.06, p =
0.17; ESR: rs = 0.08, p = 0.11; SJC: rs = -0.06, p = 0.21; and
TJC: rs = 0.04, p = 0.40).
We also studied the effect of time (in years) elapsed from
Fig. (3). Time between earlier cessation of smoking (in years) and
inclusion in the study, and its correlation with mean DAS28 at
inclusion (rs = 0.07, p = 0.13).
the effect of cessation of smoking on disease activity in early
and established RA in a large longitudinal observational
cohort. We could confirm the results from the CORRONA
study in the US , namely that stopping smoking after
inclusion in the study did not have a positive effect on
EULAR outcome, HAQ or the individual variables of the
DAS28. Stopping smoking after onset of RA was an
independent risk factor for poor EULAR response at 8 years.
We have previously reported from this same material that
current smokers did poorly in a one-year follow-up , and
others have reported similar results [3-12]. However, in this
study we could see no differences in EULAR response or
absolute DAS28 values, or the individual variables of the
DAS28 stratified for different smoking strata, with up to 15
years of follow-up. There may be several reasons for these
findings. The patients who stopped smoking may have been
a selected group, for example with more comorbidities or
other factors that we could not adjust for. We may also
possibly be measuring factors that are related to poor health
other than joint inflammation in RA patients who smoke .
We have previously reported that RA patients who smoke
and who are starting anti-TNF therapy have a poorer
This is to our knowledge the second study to investigate
308 The Open Rheumatology Journal, 2012, Volume 6 Andersson et al.
prognosis, but the results depended on the outcome measure
used and the time of follow-up, even during the first year of
anti-TNF treatment . The immunological process in RA
starts several years before the actual clinical onset of RA [22,
23]. In RA patients who smoke, this immunological disease
process may be irreversible even after they stop smoking, or
that smoking enhances this patho-immunological process in
some other way than by contributing to production of anti-
CCP antibodies. Ideally, combining shared epitope data and
anti-CCP serological data could be used to identify the
patients with RA that is triggered by smoking, and it might
be possible to study the effects of cessation of smoking
specifically in these patients. However, shared epitope did
not influence the poorer response of smokers to methotrexate
and biologics in another large Swedish RA study . The
present results clearly need to be verified using larger
material, preferably with adjustment for anti-CCP serology
and shared epitope.
early (? 2 years after inclusion) with patients who stopped
smoking later on, but we could not see any differences
between these groups either in EULAR outcome or absolute
DAS28 values. However, heavy smokers who stopped
smoking after inclusion had poorer EULAR response at 2
years. These heavy smokers were probably a selected patient
population and may have had more comorbidities and/or
worse general health status.
We also compared patients who had stopped smoking
smoking (in years) before inclusion in the study on disease
activity or function at inclusion. This latter finding is
consistent with our earlier results using the same material 
and those of others [3, 9] that previous smoking does not
influence disease activity initially.
We could not find any effect of the time of cessation of
smoking in RA and it should be stressed that all RA patients
need to stop smoking, in particular because of the high risk
of cardiovascular mortality and morbidity in RA patients
[24, 25] and the association of smoking with vasculitis and
noduli in RA [26, 27].
Our results obviously cannot be used to advocate
well-documented material, with a long follow-up of 15 years
and relatively frequent follow-up visits during the first 2
years. We also had extensive pack-year data and data on
socioeconomic class. Our patients were mainly treated with
DMARDs (ie. non-biologics), although the proportion of
patients on biologics increased to 23% at 15 years of follow-
up. As treatment with DMARDs and biologics was only
recorded at the follow-up visits in this study, further studies
are needed to analyze the effect of stopping smoking on
disease activity in RA patients being treated with biologics.
One of the major strengths of this study is the large and
patients stopped smoking after inclusion. There may also
have been a selection bias for these patients. This study was
started when smoking was not yet recognized as a poor
prognostic factor in RA, and it may be so that the patients
who were most actively encouraged to stop smoking may
have had more comorbidities. The deceased patients may
also have smoked more. However, there were no differences
in baseline data and there were few differences in DMARD
or glucocorticoid treatment in these patients as compared to
It is possible that our study lacked power, as only 127
the patients in the other smoking categories. We lacked data
on shared epitope and had anti-CCP antibody status in only a
minority of cases, so we could not adjust for these factors
fully. One of the limitations of this study was that the data on
smoking and ceasing smoking was retrospective, which may
have caused misclassification of some patients due to
problems with recall. There were some differences in
attrition; the patients with incomplete data at all follow-up
points had received less glucocorticoids than patients with
complete data. On the other hand, patients with incomplete
data had more often received DMARDs, combination
treatment, and biologics. A total of 34% of the patients did
not receive DMARD treatment at 15 years. Sixty-one per
cent not treated with DMARDs at 15 years had good
EULAR response, thus a majority of these patients had low
disease activity. Lack of response to the 2010 questionnaire
was associated with higher disease activity and smoking in
our study, thus confirming other studies on attrition and non-
response to questionnaires [28, 29]. We also attempted to
analyze disease activity over time by using mixed models,
but the assumption for this statistical model was not fulfilled
so this method could not be used.
effect of stopping smoking after onset of RA on disease
activity in RA. Cessation of smoking after onset of RA
disease did not influence the poor prognosis of smokers.
However, the patients who stopped smoking after onset of
RA may have been a selected patient population, and our
results must be verified in larger studies, preferably with
adjustment for shared epitope and anti-CCP serology. The
time in years from cessation of smoking before inclusion in
the study did not influence disease activity at inclusion. Our
results certainly cannot be used to advocate smoking in RA
and all RA patients should be encouraged to stop smoking.
Further studies on the effects of cessation of smoking on the
health of RA patients are needed.
In summary, this is the second study to investigate the
DMARDs = Disease-modifying anti-rheumatic drugs
DAS28 = Disease Activity Score (28 joints)
ESR = Erythrocyte sedimentation rate
CRP = C-reactive protein
RF = Rheumatoid factor
SEI = Socioeconomic class
= Health Assessment Questionnaire
= Visual analog scale
CONFLICTS OF INTEREST
educational events from Abbott (< $5,000) and MSD (<
$2,000) and speaking and consultation fees from Pfizer (<
$10,000). Dr. Stefan Bergman has received consultation fees
from Pfizer (< $5,000).
Dr. M.K. Söderlin has received speaking fees for
statistical analyses. We thank all the staff and hospitals in the
BARFOT study for provision of the data.
We thank Jan-Åke Nilsson for invaluable help with the
The Effect of Stopping Smoking on Disease Activity in RA The Open Rheumatology Journal, 2012, Volume 6 309 Download full-text
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Received: August 19, 2012
© Andersson et al.; Licensee Bentham Open.
This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/
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Revised: September 3, 2012 Accepted: September 5, 2012