Clin Rheumatol DOI 10.1007/s10067-015-3008-9
ORIGINAL ARTICLE
Smoking and the risk of systemic lupus erythematosus: an updated systematic review and cumulative meta-analysis Fan Jiang 1 & Suyun Li 1 & Chongqi Jia 1
Received: 12 April 2015 / Revised: 8 June 2015 / Accepted: 3 July 2015 # International League of Associations for Rheumatology (ILAR) 2015
Abstract Published articles reported controversial results about the association of smoking with the risk of systemic lupus erythematosus (SLE). A meta-analysis was performed to assess the aforementioned association and arrive at a more precise estimate of effect. A comprehensive search was performed to identify case–control or cohort studies (from 1990 to 2015) of the aforementioned association. The I2 statistic was used to examine between-study heterogeneity. Fixed or random effect model was selected based on heterogeneity test among studies. Publication bias was estimated using Egger’s regression asymmetry test. A total of 12 published articles with 13 studies were finally included in our meta-analysis. Results showed that the pooled odds ratio (OR) for SLE risk was 1.56 (95 % confidence interval (CI)=1.26–1.95) among current smokers compared with nonsmokers. For ex-smokers versus nonsmokers, the pooled OR for SLE risk was 1.23 (95 % CI=0.93–1.63). Subgroup analysis by geographic location and cumulative meta-analysis were also analyzed. In conclusion, our meta-analysis suggested that smoking increased the risk of SLE. Further studies are needed to confirm this result.
Keywords Meta-analysis . Risk . Smoking . Systemic lupus erythematosus
* Chongqi Jia [email protected] 1
Department of Epidemiology, Shandong University, Jinan 250012, Shandong, People’s Republic of China
Introduction Systemic lupus erythematosus (SLE) is a complex multisystem autoimmune disease. SLE is about 7–11 times more common in females than in males [1]. Although genetic factors and sex hormones are known to influence the development of SLE [2–4], environmental factors may also play an important role in SLE [5–7]. Smoking has been found to be an environmental risk factor for the development of autoimmune diseases, e.g., rheumatoid arthritis [8, 9] and Graves’ disease [10]. Smoking contains innumerable toxic chemicals that could cause genetic mutations and influence both cell-mediated and humoral immune responses harmfully [11]. These changes could eventually, in the course of years or decades, lead to the development of an autoimmune disease. Whether smoking is a risk factor for SLE has been controversial. Numerous studies have examined the relation of smoking to SLE risk [12–15]. A study by Nagata et al. in 1995 showed that smoking had a significantly increased risk for SLE [13]. In 1998, Hardy et al. also reported a positive effect of smoking on SLE [14]. However, some other studies showed no significant relationship between smoking and SLE [12, 15]. Thus far, a previous meta-analysis of nine studies by Costenbader et al. [16] revealed a 50 % increased risk of SLE among current smokers compared with nonsmokers but no significant difference for the risk of SLE between exsmokers and nonsmokers. A new study has found a strong association between smoking and discoid lupus and lupus tumidus but not systemic lupus erythematosus in 405 lupus erythematosus patients [17]. However, other studies have found that smoking was associated with increased risk of SLE [18–20]. In addition, a recent meta-analysis, examining the influence of smoking on the effectiveness of antimalarials in cutaneous lupus, has
2006 2006 2013 2014 2015 Washio Washio Ekblom-Kullberg Young Bockle
SLE systemic lupus erythematosus, case SLE patients, control healthy controls, current current smokers, ex ex-smokers, non nonsmokers, Na not available, No. cases/no. controls number of cases and number of controls in case–control and cohort studies
1.70 (0.69–4.18) 7.35 (1.62–33.23) 1.80 (1.15–2.83) 1.27 (1.06–1.51) Na 2.14 (1.31–3.49) 2.32 (1.15–4.67) 1.55 (1.00–2.40) 1.33 (1.07–1.64) 0.76 (0.31–1.87) 30.5/26 34.5/47 47.1/47.8 41.7/41.7 43.3/43.3 116/329 59/188 205/862 1,242/946 235/304
2001 2003 Cooper Formica
Japan Japan Finland USA Austria
1998 2001 Hardy Ghaussy
USA USA
Case–control Cohort (4 years follow-up period: 1995–1999) Case–control Case–control Case–control Case–control Case–control
265/355 67/53,924
39/39 Na/Na
1.10 (0.70–1.70) 1.60 (0.80–3.30)
0.60 (0.40–1.00) 1.60 (0.80–3.30)
Age, sex, and social class Age, sex, race, family history of SLE, education, past income Age, sex, state, education, race Age, sex, oral contraceptive use, education, BMI, and alcohol consumption Age, sex, drinking Age, sex, drinking Age, sex, geographic vicinity Age, sex, race Age and sex 1.23 (0.70–2.17) 3.62 (1.22–10.70) 1.95 (1.14–3.31) 6.69 (2.59–17.28) 47/47 44/44 150/300 125/125
1.13 (0.38–3.31) 0.61 (0.34–1.11) 1.07 (0.37–3.10) 0.91 (0.54–1.55) 1.80 (0.80–4.01) 0.91 (0.56–1.48) 2.31 (1.34–3.97) 1.09 (0.66–1.80) 46/Na 38/37 Na/Na 30–55 1990 1993 1995 1996 Benoni Reidenberg Nagata Sanchez-Guerrero
UK USA
Study design Geographic location Year
Two investigators (Jiang and Li) independently extracted the following data from each study: first author’s name, published year, geographic location, sample size, study design, mean age for both case (exposed) and control (unexposed) groups, adjusted OR (IRR) with 95 % CI for SLE risk (current smokers versus nonsmokers, exsmokers versus nonsmokers), as well as adjusted factors to evaluate the risk of SLE. In all eligible studies, two cohort studies [15, 23] provided IRRs with 95 % CIs to estimate the effect of smoking on SLE risk. Given the large sample sizes in the cohort studies, the IRRs and 95 % CIs reported are close to the ORs and 95 % CIs; therefore, we used IRRs in our meta-analyses. Additionally, only raw numbers (not ORs) were presented in the report by Reidenberg et al. [12]; thus, we calculated crude ORs with 95 % CIs for this study.
First author
Data extraction and processing
Table 1
The inclusion criteria were as follows: (1) case–control or cohort studies in which smoking was examined as a risk factor for the development of SLE and (2) OR or incident rate ratio (IRR) with 95 % CI or raw numbers which could be calculated as OR with 95 % CI should be provided. The diagnosis of SLE was confirmed in each subject using the American Rheumatism Association 1982 revised criteria [22].
Characteristic of smoking for SLE risk in studies included in the meta-analysis
Inclusion criteria
No. cases/no. controls
Mean age (case/control)
OR (95 % CI) current/non
We conducted a comprehensive search using the databases PubMed, ISI Web of Science, Scopus, EMBASE, and Cochrane in all languages and the search terms Bsmoking^ or Bcigarette^ or Btobacco^ or Bnicotine^ and Bsystemic lupus erythematosus^ or BSLE^ or Bautoimmune diseases^ or Bconnective tissue diseases^ in various combinations for relevant articles published between 1990 and 2015. Furthermore, we searched and identified studies not captured by our database through reviewing previous published meta-analysis and reference lists in retrieved articles.
56/99 195/143 282/292 85/106,391
OR (95 % CI) ex/non
Search strategy
Case–control Case–control Case–control Cohort (14 years follow-up period: 1976–1990) Case–control Case–control
Methods
Sweden USA Japan USA
Adjusted factors to evaluate the risk of SLE
shown a significant decrease (odds ratio (OR)=0.53, 95 % confidence interval (CI)=0.29–0.98) in the response to antimalarials for smokers compared with nonsmokers [21]. Hence, we performed an updated meta-analysis to examine a more reliable association of smoking with SLE risk.
Age, sex, geographic vicinity Age and sex Age, sex, geographic vicinity Age, sex
Clin Rheumatol
Clin Rheumatol Table 2 Studies
Pooled measures on the association of smoking with SLE risk All included studies
After sensitivity analysis
Current smoker versus nonsmoker Ex-smoker versus nonsmoker Current smoker versus nonsmoker Ex-smoker versus nonsmoker
Total
OR (95 % CI)
I2 (%)
OR (95 % CI)
I2 (%)
OR (95 % CI)
I2 (%)
OR (95 % CI)
I2 (%)
1.56 (1.26–1.95)**
56.3
1.23 (0.93–1.63)
62.3
1.42 (1.25–1.62)**
36.9
1.26 (1.10–1.45)**
43.4
Geographic location Europe 1.57 (1.18–2.09)**
7.8
1.51 (1.08–2.11)*
0.0
1.57 (1.18–2.09)**
7.8
1.51 (1.08–2.11)*
0.0
North America 1.37 (0.97–1.92)
66.4
1.04 (0.70–1.55)
73.9
1.23 (1.04–1.45)*
0.0
1.05 (0.74–1.51)
57.6
East Asia
0.0
2.06 (0.80–5.33)
53.0
2.24 (1.62–3.09)**
0.0
2.06 (0.80–5.33)
53.0
2.24 (1.62–3.09)**
SLE systemic lupus erythematosus *
p50 % as the criterion to assess the key studies with substantial impact on between-study heterogeneity. In the cumulative meta-analysis, studies were added one at a time in the order of published year, and the results were summarized sequentially. An influence analysis was conducted [27] to
Statistical analysis Pooled measure was calculated as the inverse varianceweighted mean of the logarithm of OR (IRR) with 95 % CI to assess the association of current smoking and ex-smoking with SLE risk. Heterogeneity among studies was assessed using the I2 statistic that describe the proportion of total variation attributable to between-study heterogeneity as opposed to random error or chance [24]. In the presence of substantial
% Author
Year
OR (95% CI)
Weight
Benoni
1990
1.80 (0.80, 4.01)
4.99
Reidenberg
1993
0.91 (0.56, 1.48)
8.76
Nagata
1995
2.31 (1.34, 3.97)
7.91
Sanchez−Guerrero
1996
1.09 (0.66, 1.80)
8.52
Hardy
1998
1.95 (1.14, 3.31)
8.06
Ghaussy
2001
6.69 (2.59, 17.28)
3.96
Cooper
2001
1.10 (0.70, 1.70)
9.44
Formica
2003
1.60 (0.80, 3.30)
5.90
Washio
2006
2.14 (1.31, 3.49)
8.70
Washio
2006
2.32 (1.15, 4.67)
5.98
Ekblom−Kullberg
2013
1.55 (1.03, 2.33)
10.04
Young
2014
1.33 (1.07, 1.64)
13.45
Bockle
2015
0.76 (0.31, 1.87)
4.29
1.56 (1.26, 1.95)
100.00
Overall (I−squared = 56.3%, p = 0.007)
NOTE: Weights are from random effects analysis .5
1
1.5 2 2.5 33.5
6.5
17.5
Fig. 1 Forest plot of ORs for the association of current smoking with risk of SLE. White diamond denotes the pooled OR. Black point indicates the OR in each study, with square size inversely proportional to the standard error of the OR. Horizontal line represents 95 % CI
Clin Rheumatol
of SLE, as well as adjusted factors to evaluate the risk of SLE in the published articles included in this meta-analysis were presented in Table 1. In 7 of the 13 studies [14, 15, 19, 23, 29–31], current smoking was defined as smoking at least one cigarette per day for at least 3 months or 1 year or unspecified time period. In 5 of the 13 studies [12, 17, 18, 20], current smoking was defined as smoking prior to the diagnosis of SLE. In the remainder of the studies [13], current smoking was not clearly defined. In 7 of the 12 studies [14, 15, 18, 19, 29, 31], ex-smoking was defined as having stopped smoking for at least 3 months or 1 year prior to the diagnosis of SLE. In one study [20], exsmoking was defined as ever smoked but did not smoke at the time of interview. In the remainder of the studies [12, 13, 23, 30], the definition of ex-smoking was not clearly stated.
describe how robust the pooled estimator is to removal of individual studies. An individual study is suspected of excessive influence if the point estimate of its omitted analysis lies outside the 95 % CIs of the combined analysis. Publication bias was estimated using Egger’s regression asymmetry test [28]. All statistical analyses were performed with STATA/SE version 13.1 (Stata Corporation, College Station, TX, USA). All p values were two-sided, and that less than 0.05 was considered statistically significant.
Results Study characteristics A total of 12 published articles with 13 studies (11 case–control studies [12–14, 17–20, 29–31] and two cohort studies [15, 23]) were finally included in our meta-analysis. The 13 studies examined the association of smoking with SLE risk in current smokers versus nonsmokers; 12 of the 13 studies [12–15, 18–20, 23, 29–31] examined this association in ex-smokers versus nonsmokers. General characteristics as geographic location, sample size, mean age for both case (exposed) and control (unexposed) groups, OR (IRR) with 95 % CI for risk
Quantitative synthesis Results of pooled analysis were summarized in detail in Table 2. For the odds of SLE in current smokers versus nonsmokers, the pooled OR using REM for the 13 studies was 1.56 (95 % CI=1.26–1.95) (Fig. 1). For the odds of SLE in ex-
% Author
Year
OR (95% CI)
Weight
Benoni
1990
1.13 (0.38, 3.31)
4.78
Reidenberg
1993
0.61 (0.34, 1.11)
9.54
Nagata
1995
1.07 (0.37, 3.10)
4.90
Sanchez−Guerrero
1996
0.91 (0.54, 1.55)
10.45
Hardy
1998
1.23 (0.70, 2.17)
9.90
Ghaussy
2001
3.62 (1.22, 10.70)
4.76
Cooper
2001
0.60 (0.40, 1.00)
11.49
Formica
2003
1.60 (0.80, 3.30)
8.05
Washio
2006
1.70 (0.69, 4.18)
6.12
Washio
2006
7.35 (1.62, 33.23)
2.85
Ekblom−Kullberg
2013
1.80 (1.15, 2.83)
11.61
Young
2014
1.27 (1.06, 1.51)
15.54
1.23 (0.93, 1.63)
100.00
Overall (I−squared = 62.3%, p = 0.002)
NOTE: Weights are from random effects analysis .3
.5
1
1.5 2
3
4
7
10
33
Fig. 2 Forest plot of ORs for the association of ex-smoking with risk of SLE. White diamond denotes the pooled OR. Black point indicates the OR in each study, with square size inversely proportional to the standard error of the OR. Horizontal line represents 95 % CI
Clin Rheumatol
nonsmokers until adding a 1998 study by Hardy et al. [14] (OR=1.48, 95 % CI=1.02–2.15), and thereafter, the significant difference remained stable. Figure 4 showed the results of the cumulative meta-analysis for the association of exsmoking with SLE risk. The aforementioned association tended to be significant with the accumulation of studies in the order of published year, though it was not significant adding each included study.
smokers versus nonsmokers, the pooled OR using REM for the 12 studies was 1.23 (95 % CI=0.93–1.63) (Fig. 2). In the subgroup analysis by geographic location (categorized as Europe, North America, and East Asia), results showed that among current smokers compared with nonsmokers, the association of smoking with SLE risk was significant in Europe (OR=1.57, 95 % CI=1.18–2.09) and East Asia (OR=2.24, 95 % CI=1.62–3.09); moreover, boundary significant difference for SLE risk was observed in North America (OR=1.37, 95 % CI=0.97–1.92). For ex-smokers versus nonsmokers, the relation of smoking to SLE risk was significant in Europe (OR=1.51, 95 % CI=1.08–2.11) but not significant in North America (OR=1.04, 95 % CI=0.70–1.55) and East Asia (OR=2.06, 95 % CI=0.80–5.33) (Table 2).
Sensitivity analysis In the Bleave one out^ sensitivity analysis, two studies by Ghaussy et al. [31] and Cooper et al. [30] were found to be the key contributors to between-study heterogeneity for the association of smoking with the risk of SLE. After excluding the two studies, the aforementioned association remained significant. All data were shown in Table 2.
Cumulative meta-analysis Cumulative meta-analysis was conducted to reflect the dynamic trend of results and evaluate the influence of individual study on the overall results. Figure 3 showed a forest plot for the cumulative meta-analysis for the relationship between current smoking and SLE risk. Results indicated that the risk of SLE was not significantly different in current smokers and
Influence and publication bias analysis Both before and after excluding studies contributing to between-study heterogeneity, no individual study was found to have excessive influence on the pooled effect, and no
Author
Year
OR (95% CI)
Benoni
1990
1.80 (0.80, 4.03)
Reidenberg
1993
1.18 (0.62, 2.27)
Nagata
1995
1.52 (0.81, 2.85)
Sanchez−Guerrero
1996
1.38 (0.88, 2.15)
Hardy
1998
1.48 (1.02, 2.15)
Ghaussy
2001
1.79 (1.12, 2.88)
Cooper
2001
1.64 (1.10, 2.44)
Formica
2003
1.62 (1.14, 2.31)
Washio
2006
1.67 (1.21, 2.31)
Washio
2006
1.72 (1.27, 2.32)
Ekblom−Kullberg
2013
1.68 (1.30, 2.19)
Young
2014
1.61 (1.29, 2.01)
Bockle
2015
1.56 (1.26, 1.95)
.6
.8
1
1.5
2
2.5
4
Fig. 3 Cumulative meta-analysis of the SLE risk among current smokers compared with nonsmokers. Open circle indicates the pooled OR. Horizontal line represents 95 % CI
Clin Rheumatol
Author
Year
OR (95% CI)
Benoni
1990
1.13 (0.38, 3.34)
Reidenberg
1993
0.70 (0.42, 1.18)
Nagata
1995
0.76 (0.48, 1.22)
Sanchez−Guerrero
1996
0.82 (0.58, 1.17)
Hardy
1998
0.92 (0.68, 1.24)
Ghaussy
2001
1.07 (0.72, 1.61)
Cooper
2001
0.96 (0.66, 1.39)
Formica
2003
1.02 (0.72, 1.46)
Washio
2006
1.07 (0.76, 1.50)
Washio
2006
1.20 (0.82, 1.76)
Ekblom−Kullberg
2013
1.26 (0.88, 1.81)
Young
2014
1.23 (0.93, 1.63)
Bockle
2015
1.23 (0.93, 1.63)
.3
.5
.7
1
1.2
1.5
3 3.5
Fig. 4 Cumulative meta-analysis of the SLE risk among ex-smokers compared with nonsmokers. Open circle indicates the pooled OR. Horizontal line represents the 95 % CI
significant publication bias was detected for studies on the association of current smoking with SLE risk and exsmoking with SLE risk (all p>0.05).
Discussion In line with the previous published meta-analysis [16], our meta-analysis of 12 published articles with 13 studies also indicated that current smoking and ex-smoking had significantly (OR=1.56, 95 % CI=1.26–1.95) and boundary significantly (OR=1.23, 95 % CI=0.93–1.63) increased risk for SLE, respectively. The mechanism of smoking on SLE risk may be quite complicated. Costenbader and Karlson had a review article [32] to explain in detail the biologic effect of smoking on the development of SLE. Here, we make a brief introduction to these mechanisms. Just as this article interpret: First, smoking results in increased apoptosis, with high concentrations of free radicals and increased expression of Fas (CD95) on B and CD4 T lymphocyte cell surfaces. Apoptotic defects and impaired clearance of cellular debris are considered key events in the development of autoimmunity. Second, smoking
is associated with increases in C-reactive protein and IL-6, which are the important markers of inflammation in autoimmune diseases. Third, smoking induces abnormalities in T cell function and reduces NK cell activity, which might lead to the development of SLE. Fourth, smoking has anti-estrogenic effects related to the development of autoimmune diseases. Readers interested in these mechanisms could consult this article. As mentioned in the paper [33] that the between-study heterogeneity is common in meta-analysis, our meta-analysis also showed the significant between-study heterogeneity in North America population, in which the two studies [30, 31] were found to be the key contributors to this heterogeneity. It is well-known that SLE has a complex etiology and pathophysiology generated by the combined effects of genes and environment factors. Thus, the genetic and environment variables as well as their possible interaction deserve to be considered as the potential contributors to this disease–effect unconformity. In this respect, the lack of relevant study-level covariates in the reported articles precluded our more robust assessment of sources of this heterogeneity. Other possibilities related to the disease–effect diversity, such as design quality, characteristics of the sample, variation of the covariate,
Clin Rheumatol
differences in cigarette products with respect to pesticides or fertilizers applied, ingredients, additives, filters, other components, etc., could not be ruled out. The disunity of definitions for current smoking and exsmoking among reported articles is the major limitation in this meta-analysis, which may lead to a misclassification bias. Thus, further high-quality studies are needed to confirm our results. In conclusion, this meta-analysis suggested that smoking increased the risk of SLE. Further studies are needed to confirm this result. Author contributions The authors’ contributions to the present study were as follows: Fan Jiang and Suyun Li contributed to data collection, systematic review, and data extraction; Fan Jiang did the data analyses and drafted the manuscript; and Chongqi Jia is responsible for the whole work.
13.
14.
15.
16.
17.
18. Disclosures None.
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Ghaussy NO, Sibbitt WL Jr, Qualls CR (2001) Cigarette smoking, alcohol consumption, and the risk of systemic lupus erythematosus: a case–control study. J Rheumatol 28(11):2449–2453 Costenbader KH, Karlson EW (2006) Cigarette smoking and autoimmune disease: what can we learn from epidemiology? Lupus 15(11):737–745 Munaafo MR, Flint J (2004) Meta-analysis of genetic association studies. Trends Genet 20(9):439–444
ORIGINAL ARTICLE
Smoking and the risk of systemic lupus erythematosus: an updated systematic review and cumulative meta-analysis Fan Jiang 1 & Suyun Li 1 & Chongqi Jia 1
Received: 12 April 2015 / Revised: 8 June 2015 / Accepted: 3 July 2015 # International League of Associations for Rheumatology (ILAR) 2015
Abstract Published articles reported controversial results about the association of smoking with the risk of systemic lupus erythematosus (SLE). A meta-analysis was performed to assess the aforementioned association and arrive at a more precise estimate of effect. A comprehensive search was performed to identify case–control or cohort studies (from 1990 to 2015) of the aforementioned association. The I2 statistic was used to examine between-study heterogeneity. Fixed or random effect model was selected based on heterogeneity test among studies. Publication bias was estimated using Egger’s regression asymmetry test. A total of 12 published articles with 13 studies were finally included in our meta-analysis. Results showed that the pooled odds ratio (OR) for SLE risk was 1.56 (95 % confidence interval (CI)=1.26–1.95) among current smokers compared with nonsmokers. For ex-smokers versus nonsmokers, the pooled OR for SLE risk was 1.23 (95 % CI=0.93–1.63). Subgroup analysis by geographic location and cumulative meta-analysis were also analyzed. In conclusion, our meta-analysis suggested that smoking increased the risk of SLE. Further studies are needed to confirm this result.
Keywords Meta-analysis . Risk . Smoking . Systemic lupus erythematosus
* Chongqi Jia [email protected] 1
Department of Epidemiology, Shandong University, Jinan 250012, Shandong, People’s Republic of China
Introduction Systemic lupus erythematosus (SLE) is a complex multisystem autoimmune disease. SLE is about 7–11 times more common in females than in males [1]. Although genetic factors and sex hormones are known to influence the development of SLE [2–4], environmental factors may also play an important role in SLE [5–7]. Smoking has been found to be an environmental risk factor for the development of autoimmune diseases, e.g., rheumatoid arthritis [8, 9] and Graves’ disease [10]. Smoking contains innumerable toxic chemicals that could cause genetic mutations and influence both cell-mediated and humoral immune responses harmfully [11]. These changes could eventually, in the course of years or decades, lead to the development of an autoimmune disease. Whether smoking is a risk factor for SLE has been controversial. Numerous studies have examined the relation of smoking to SLE risk [12–15]. A study by Nagata et al. in 1995 showed that smoking had a significantly increased risk for SLE [13]. In 1998, Hardy et al. also reported a positive effect of smoking on SLE [14]. However, some other studies showed no significant relationship between smoking and SLE [12, 15]. Thus far, a previous meta-analysis of nine studies by Costenbader et al. [16] revealed a 50 % increased risk of SLE among current smokers compared with nonsmokers but no significant difference for the risk of SLE between exsmokers and nonsmokers. A new study has found a strong association between smoking and discoid lupus and lupus tumidus but not systemic lupus erythematosus in 405 lupus erythematosus patients [17]. However, other studies have found that smoking was associated with increased risk of SLE [18–20]. In addition, a recent meta-analysis, examining the influence of smoking on the effectiveness of antimalarials in cutaneous lupus, has
2006 2006 2013 2014 2015 Washio Washio Ekblom-Kullberg Young Bockle
SLE systemic lupus erythematosus, case SLE patients, control healthy controls, current current smokers, ex ex-smokers, non nonsmokers, Na not available, No. cases/no. controls number of cases and number of controls in case–control and cohort studies
1.70 (0.69–4.18) 7.35 (1.62–33.23) 1.80 (1.15–2.83) 1.27 (1.06–1.51) Na 2.14 (1.31–3.49) 2.32 (1.15–4.67) 1.55 (1.00–2.40) 1.33 (1.07–1.64) 0.76 (0.31–1.87) 30.5/26 34.5/47 47.1/47.8 41.7/41.7 43.3/43.3 116/329 59/188 205/862 1,242/946 235/304
2001 2003 Cooper Formica
Japan Japan Finland USA Austria
1998 2001 Hardy Ghaussy
USA USA
Case–control Cohort (4 years follow-up period: 1995–1999) Case–control Case–control Case–control Case–control Case–control
265/355 67/53,924
39/39 Na/Na
1.10 (0.70–1.70) 1.60 (0.80–3.30)
0.60 (0.40–1.00) 1.60 (0.80–3.30)
Age, sex, and social class Age, sex, race, family history of SLE, education, past income Age, sex, state, education, race Age, sex, oral contraceptive use, education, BMI, and alcohol consumption Age, sex, drinking Age, sex, drinking Age, sex, geographic vicinity Age, sex, race Age and sex 1.23 (0.70–2.17) 3.62 (1.22–10.70) 1.95 (1.14–3.31) 6.69 (2.59–17.28) 47/47 44/44 150/300 125/125
1.13 (0.38–3.31) 0.61 (0.34–1.11) 1.07 (0.37–3.10) 0.91 (0.54–1.55) 1.80 (0.80–4.01) 0.91 (0.56–1.48) 2.31 (1.34–3.97) 1.09 (0.66–1.80) 46/Na 38/37 Na/Na 30–55 1990 1993 1995 1996 Benoni Reidenberg Nagata Sanchez-Guerrero
UK USA
Study design Geographic location Year
Two investigators (Jiang and Li) independently extracted the following data from each study: first author’s name, published year, geographic location, sample size, study design, mean age for both case (exposed) and control (unexposed) groups, adjusted OR (IRR) with 95 % CI for SLE risk (current smokers versus nonsmokers, exsmokers versus nonsmokers), as well as adjusted factors to evaluate the risk of SLE. In all eligible studies, two cohort studies [15, 23] provided IRRs with 95 % CIs to estimate the effect of smoking on SLE risk. Given the large sample sizes in the cohort studies, the IRRs and 95 % CIs reported are close to the ORs and 95 % CIs; therefore, we used IRRs in our meta-analyses. Additionally, only raw numbers (not ORs) were presented in the report by Reidenberg et al. [12]; thus, we calculated crude ORs with 95 % CIs for this study.
First author
Data extraction and processing
Table 1
The inclusion criteria were as follows: (1) case–control or cohort studies in which smoking was examined as a risk factor for the development of SLE and (2) OR or incident rate ratio (IRR) with 95 % CI or raw numbers which could be calculated as OR with 95 % CI should be provided. The diagnosis of SLE was confirmed in each subject using the American Rheumatism Association 1982 revised criteria [22].
Characteristic of smoking for SLE risk in studies included in the meta-analysis
Inclusion criteria
No. cases/no. controls
Mean age (case/control)
OR (95 % CI) current/non
We conducted a comprehensive search using the databases PubMed, ISI Web of Science, Scopus, EMBASE, and Cochrane in all languages and the search terms Bsmoking^ or Bcigarette^ or Btobacco^ or Bnicotine^ and Bsystemic lupus erythematosus^ or BSLE^ or Bautoimmune diseases^ or Bconnective tissue diseases^ in various combinations for relevant articles published between 1990 and 2015. Furthermore, we searched and identified studies not captured by our database through reviewing previous published meta-analysis and reference lists in retrieved articles.
56/99 195/143 282/292 85/106,391
OR (95 % CI) ex/non
Search strategy
Case–control Case–control Case–control Cohort (14 years follow-up period: 1976–1990) Case–control Case–control
Methods
Sweden USA Japan USA
Adjusted factors to evaluate the risk of SLE
shown a significant decrease (odds ratio (OR)=0.53, 95 % confidence interval (CI)=0.29–0.98) in the response to antimalarials for smokers compared with nonsmokers [21]. Hence, we performed an updated meta-analysis to examine a more reliable association of smoking with SLE risk.
Age, sex, geographic vicinity Age and sex Age, sex, geographic vicinity Age, sex
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Clin Rheumatol Table 2 Studies
Pooled measures on the association of smoking with SLE risk All included studies
After sensitivity analysis
Current smoker versus nonsmoker Ex-smoker versus nonsmoker Current smoker versus nonsmoker Ex-smoker versus nonsmoker
Total
OR (95 % CI)
I2 (%)
OR (95 % CI)
I2 (%)
OR (95 % CI)
I2 (%)
OR (95 % CI)
I2 (%)
1.56 (1.26–1.95)**
56.3
1.23 (0.93–1.63)
62.3
1.42 (1.25–1.62)**
36.9
1.26 (1.10–1.45)**
43.4
Geographic location Europe 1.57 (1.18–2.09)**
7.8
1.51 (1.08–2.11)*
0.0
1.57 (1.18–2.09)**
7.8
1.51 (1.08–2.11)*
0.0
North America 1.37 (0.97–1.92)
66.4
1.04 (0.70–1.55)
73.9
1.23 (1.04–1.45)*
0.0
1.05 (0.74–1.51)
57.6
East Asia
0.0
2.06 (0.80–5.33)
53.0
2.24 (1.62–3.09)**
0.0
2.06 (0.80–5.33)
53.0
2.24 (1.62–3.09)**
SLE systemic lupus erythematosus *
p50 % as the criterion to assess the key studies with substantial impact on between-study heterogeneity. In the cumulative meta-analysis, studies were added one at a time in the order of published year, and the results were summarized sequentially. An influence analysis was conducted [27] to
Statistical analysis Pooled measure was calculated as the inverse varianceweighted mean of the logarithm of OR (IRR) with 95 % CI to assess the association of current smoking and ex-smoking with SLE risk. Heterogeneity among studies was assessed using the I2 statistic that describe the proportion of total variation attributable to between-study heterogeneity as opposed to random error or chance [24]. In the presence of substantial
% Author
Year
OR (95% CI)
Weight
Benoni
1990
1.80 (0.80, 4.01)
4.99
Reidenberg
1993
0.91 (0.56, 1.48)
8.76
Nagata
1995
2.31 (1.34, 3.97)
7.91
Sanchez−Guerrero
1996
1.09 (0.66, 1.80)
8.52
Hardy
1998
1.95 (1.14, 3.31)
8.06
Ghaussy
2001
6.69 (2.59, 17.28)
3.96
Cooper
2001
1.10 (0.70, 1.70)
9.44
Formica
2003
1.60 (0.80, 3.30)
5.90
Washio
2006
2.14 (1.31, 3.49)
8.70
Washio
2006
2.32 (1.15, 4.67)
5.98
Ekblom−Kullberg
2013
1.55 (1.03, 2.33)
10.04
Young
2014
1.33 (1.07, 1.64)
13.45
Bockle
2015
0.76 (0.31, 1.87)
4.29
1.56 (1.26, 1.95)
100.00
Overall (I−squared = 56.3%, p = 0.007)
NOTE: Weights are from random effects analysis .5
1
1.5 2 2.5 33.5
6.5
17.5
Fig. 1 Forest plot of ORs for the association of current smoking with risk of SLE. White diamond denotes the pooled OR. Black point indicates the OR in each study, with square size inversely proportional to the standard error of the OR. Horizontal line represents 95 % CI
Clin Rheumatol
of SLE, as well as adjusted factors to evaluate the risk of SLE in the published articles included in this meta-analysis were presented in Table 1. In 7 of the 13 studies [14, 15, 19, 23, 29–31], current smoking was defined as smoking at least one cigarette per day for at least 3 months or 1 year or unspecified time period. In 5 of the 13 studies [12, 17, 18, 20], current smoking was defined as smoking prior to the diagnosis of SLE. In the remainder of the studies [13], current smoking was not clearly defined. In 7 of the 12 studies [14, 15, 18, 19, 29, 31], ex-smoking was defined as having stopped smoking for at least 3 months or 1 year prior to the diagnosis of SLE. In one study [20], exsmoking was defined as ever smoked but did not smoke at the time of interview. In the remainder of the studies [12, 13, 23, 30], the definition of ex-smoking was not clearly stated.
describe how robust the pooled estimator is to removal of individual studies. An individual study is suspected of excessive influence if the point estimate of its omitted analysis lies outside the 95 % CIs of the combined analysis. Publication bias was estimated using Egger’s regression asymmetry test [28]. All statistical analyses were performed with STATA/SE version 13.1 (Stata Corporation, College Station, TX, USA). All p values were two-sided, and that less than 0.05 was considered statistically significant.
Results Study characteristics A total of 12 published articles with 13 studies (11 case–control studies [12–14, 17–20, 29–31] and two cohort studies [15, 23]) were finally included in our meta-analysis. The 13 studies examined the association of smoking with SLE risk in current smokers versus nonsmokers; 12 of the 13 studies [12–15, 18–20, 23, 29–31] examined this association in ex-smokers versus nonsmokers. General characteristics as geographic location, sample size, mean age for both case (exposed) and control (unexposed) groups, OR (IRR) with 95 % CI for risk
Quantitative synthesis Results of pooled analysis were summarized in detail in Table 2. For the odds of SLE in current smokers versus nonsmokers, the pooled OR using REM for the 13 studies was 1.56 (95 % CI=1.26–1.95) (Fig. 1). For the odds of SLE in ex-
% Author
Year
OR (95% CI)
Weight
Benoni
1990
1.13 (0.38, 3.31)
4.78
Reidenberg
1993
0.61 (0.34, 1.11)
9.54
Nagata
1995
1.07 (0.37, 3.10)
4.90
Sanchez−Guerrero
1996
0.91 (0.54, 1.55)
10.45
Hardy
1998
1.23 (0.70, 2.17)
9.90
Ghaussy
2001
3.62 (1.22, 10.70)
4.76
Cooper
2001
0.60 (0.40, 1.00)
11.49
Formica
2003
1.60 (0.80, 3.30)
8.05
Washio
2006
1.70 (0.69, 4.18)
6.12
Washio
2006
7.35 (1.62, 33.23)
2.85
Ekblom−Kullberg
2013
1.80 (1.15, 2.83)
11.61
Young
2014
1.27 (1.06, 1.51)
15.54
1.23 (0.93, 1.63)
100.00
Overall (I−squared = 62.3%, p = 0.002)
NOTE: Weights are from random effects analysis .3
.5
1
1.5 2
3
4
7
10
33
Fig. 2 Forest plot of ORs for the association of ex-smoking with risk of SLE. White diamond denotes the pooled OR. Black point indicates the OR in each study, with square size inversely proportional to the standard error of the OR. Horizontal line represents 95 % CI
Clin Rheumatol
nonsmokers until adding a 1998 study by Hardy et al. [14] (OR=1.48, 95 % CI=1.02–2.15), and thereafter, the significant difference remained stable. Figure 4 showed the results of the cumulative meta-analysis for the association of exsmoking with SLE risk. The aforementioned association tended to be significant with the accumulation of studies in the order of published year, though it was not significant adding each included study.
smokers versus nonsmokers, the pooled OR using REM for the 12 studies was 1.23 (95 % CI=0.93–1.63) (Fig. 2). In the subgroup analysis by geographic location (categorized as Europe, North America, and East Asia), results showed that among current smokers compared with nonsmokers, the association of smoking with SLE risk was significant in Europe (OR=1.57, 95 % CI=1.18–2.09) and East Asia (OR=2.24, 95 % CI=1.62–3.09); moreover, boundary significant difference for SLE risk was observed in North America (OR=1.37, 95 % CI=0.97–1.92). For ex-smokers versus nonsmokers, the relation of smoking to SLE risk was significant in Europe (OR=1.51, 95 % CI=1.08–2.11) but not significant in North America (OR=1.04, 95 % CI=0.70–1.55) and East Asia (OR=2.06, 95 % CI=0.80–5.33) (Table 2).
Sensitivity analysis In the Bleave one out^ sensitivity analysis, two studies by Ghaussy et al. [31] and Cooper et al. [30] were found to be the key contributors to between-study heterogeneity for the association of smoking with the risk of SLE. After excluding the two studies, the aforementioned association remained significant. All data were shown in Table 2.
Cumulative meta-analysis Cumulative meta-analysis was conducted to reflect the dynamic trend of results and evaluate the influence of individual study on the overall results. Figure 3 showed a forest plot for the cumulative meta-analysis for the relationship between current smoking and SLE risk. Results indicated that the risk of SLE was not significantly different in current smokers and
Influence and publication bias analysis Both before and after excluding studies contributing to between-study heterogeneity, no individual study was found to have excessive influence on the pooled effect, and no
Author
Year
OR (95% CI)
Benoni
1990
1.80 (0.80, 4.03)
Reidenberg
1993
1.18 (0.62, 2.27)
Nagata
1995
1.52 (0.81, 2.85)
Sanchez−Guerrero
1996
1.38 (0.88, 2.15)
Hardy
1998
1.48 (1.02, 2.15)
Ghaussy
2001
1.79 (1.12, 2.88)
Cooper
2001
1.64 (1.10, 2.44)
Formica
2003
1.62 (1.14, 2.31)
Washio
2006
1.67 (1.21, 2.31)
Washio
2006
1.72 (1.27, 2.32)
Ekblom−Kullberg
2013
1.68 (1.30, 2.19)
Young
2014
1.61 (1.29, 2.01)
Bockle
2015
1.56 (1.26, 1.95)
.6
.8
1
1.5
2
2.5
4
Fig. 3 Cumulative meta-analysis of the SLE risk among current smokers compared with nonsmokers. Open circle indicates the pooled OR. Horizontal line represents 95 % CI
Clin Rheumatol
Author
Year
OR (95% CI)
Benoni
1990
1.13 (0.38, 3.34)
Reidenberg
1993
0.70 (0.42, 1.18)
Nagata
1995
0.76 (0.48, 1.22)
Sanchez−Guerrero
1996
0.82 (0.58, 1.17)
Hardy
1998
0.92 (0.68, 1.24)
Ghaussy
2001
1.07 (0.72, 1.61)
Cooper
2001
0.96 (0.66, 1.39)
Formica
2003
1.02 (0.72, 1.46)
Washio
2006
1.07 (0.76, 1.50)
Washio
2006
1.20 (0.82, 1.76)
Ekblom−Kullberg
2013
1.26 (0.88, 1.81)
Young
2014
1.23 (0.93, 1.63)
Bockle
2015
1.23 (0.93, 1.63)
.3
.5
.7
1
1.2
1.5
3 3.5
Fig. 4 Cumulative meta-analysis of the SLE risk among ex-smokers compared with nonsmokers. Open circle indicates the pooled OR. Horizontal line represents the 95 % CI
significant publication bias was detected for studies on the association of current smoking with SLE risk and exsmoking with SLE risk (all p>0.05).
Discussion In line with the previous published meta-analysis [16], our meta-analysis of 12 published articles with 13 studies also indicated that current smoking and ex-smoking had significantly (OR=1.56, 95 % CI=1.26–1.95) and boundary significantly (OR=1.23, 95 % CI=0.93–1.63) increased risk for SLE, respectively. The mechanism of smoking on SLE risk may be quite complicated. Costenbader and Karlson had a review article [32] to explain in detail the biologic effect of smoking on the development of SLE. Here, we make a brief introduction to these mechanisms. Just as this article interpret: First, smoking results in increased apoptosis, with high concentrations of free radicals and increased expression of Fas (CD95) on B and CD4 T lymphocyte cell surfaces. Apoptotic defects and impaired clearance of cellular debris are considered key events in the development of autoimmunity. Second, smoking
is associated with increases in C-reactive protein and IL-6, which are the important markers of inflammation in autoimmune diseases. Third, smoking induces abnormalities in T cell function and reduces NK cell activity, which might lead to the development of SLE. Fourth, smoking has anti-estrogenic effects related to the development of autoimmune diseases. Readers interested in these mechanisms could consult this article. As mentioned in the paper [33] that the between-study heterogeneity is common in meta-analysis, our meta-analysis also showed the significant between-study heterogeneity in North America population, in which the two studies [30, 31] were found to be the key contributors to this heterogeneity. It is well-known that SLE has a complex etiology and pathophysiology generated by the combined effects of genes and environment factors. Thus, the genetic and environment variables as well as their possible interaction deserve to be considered as the potential contributors to this disease–effect unconformity. In this respect, the lack of relevant study-level covariates in the reported articles precluded our more robust assessment of sources of this heterogeneity. Other possibilities related to the disease–effect diversity, such as design quality, characteristics of the sample, variation of the covariate,
Clin Rheumatol
differences in cigarette products with respect to pesticides or fertilizers applied, ingredients, additives, filters, other components, etc., could not be ruled out. The disunity of definitions for current smoking and exsmoking among reported articles is the major limitation in this meta-analysis, which may lead to a misclassification bias. Thus, further high-quality studies are needed to confirm our results. In conclusion, this meta-analysis suggested that smoking increased the risk of SLE. Further studies are needed to confirm this result. Author contributions The authors’ contributions to the present study were as follows: Fan Jiang and Suyun Li contributed to data collection, systematic review, and data extraction; Fan Jiang did the data analyses and drafted the manuscript; and Chongqi Jia is responsible for the whole work.
13.
14.
15.
16.
17.
18. Disclosures None.
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