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Erschienen in: BMC Psychiatry 1/2017

Open Access 01.12.2017 | Research article

Prevalence of depression and anxiety in systemic lupus erythematosus: a systematic review and meta-analysis

verfasst von: Lijuan Zhang, Ting Fu, Rulan Yin, Qiuxiang Zhang, Biyu Shen

Erschienen in: BMC Psychiatry | Ausgabe 1/2017

Abstract

Background

Systemic lupus erythematosus (SLE) patients are at high risk for depression and anxiety. However, the estimated prevalence of these disorders varies substantially between studies. This systematic review aimed to establish pooled prevalence levels of depression and anxiety among adult SLE patients.

Methods

We systematically reviewed databases including PubMed, Embase, PsycINFO, and the Cochrane database library from their inception to August 2016. Studies presenting data on depression and/or anxiety in adult SLE patients and having a sample size of at least 60 patients were included. A random-effect meta-analysis was conducted on all eligible data.

Results

A total of 59 identified studies matched the inclusion criteria, reporting on a total of 10828 adult SLE patients. Thirty five and thirteen methods of defining depression and anxiety were reported, respectively. Meta-analyses revealed that the prevalence of major depression and anxiety were 24% (95% CI, 16%-31%, I2 = 95.2%) and 37% (95% CI, 12%–63%, I2 = 98.3%) according to clinical interviews. Prevalence estimates of depression were 30% (95% CI, 22%–38%, I2 = 91.6%) for the Hospital Anxiety and Depression Scale with thresholds of 8 and 39% (95% CI, 29%–49%, I2 = 88.2%) for the 21-Item Beck Depression Inventory with thresholds of 14, respectively. The main influence on depression prevalence was the publication years of the studies. In addition, the corresponding pooled prevalence was 40% (95% CI, 30%–49%, I2 = 93.0%) for anxiety according to the Hospital Anxiety and Depression Scale with a cutoff of 8 or more.

Conclusions

The prevalence of depression and anxiety was high in adult SLE patients. It indicated that rheumatologists should screen for depression and anxiety in their patients, and referred them to mental health providers in order to identify effective strategies for preventing and treating depression and anxiety among adult SLE patients.

Trial registration

Current Meta-analysis PROSPERO Registration Number: CRD 42016044125. Registered 4 August 2016.

Background

Systemic lupus erythematosus (SLE) is a multisystem, autoimmune, connective-tissue disorder with frequent psychological comorbidities, of which depression and anxiety are two common manifestations [1, 2]. It has been reported that there were 2 times higher prevalence of depression in SLE patients compared to the general population [3]. In addition, previous study has reported that the anxiety disorders were twice as prevalent among SLE patients as compared to the controls [4]. Depression and anxiety often have profound impacts on SLE patients’ health and well-being including increased incidence of cardiovascular diseases [5], myocardial infarction [6], suicidal ideation [7], physical disability [8], decreased quality of life [9, 10], and a higher risk of premature mortality [11]. Therefore, depression and anxiety may be useful targets for interventions aimed at improving subjective health and quality of life in individuals with SLE. However, current epidemiological evidence found that the prevalence of depression and/or anxiety in SLE patients ranged widely from 2% to 91.7% in different studies [12, 13]. This vast inter-study difference was previously attributed to multiple factors, including study quality, unclear definition of depression or anxiety, diverse screening strategies used across studies [14]. Reliable estimates of depression and anxiety prevalence are important for informing efforts to prevent, treat, and identify causes of depression and anxiety among SLE patients. Recent meta-analyses have estimated the overall prevalence of depression and/or anxiety in rheumatoid arthritis and osteoarthritis patients [14, 15]. There has only been one previous systematic review of psychiatric symptoms in SLE [16]; however, no systematic review was conducted to quantify the prevalence of depression and anxiety in SLE using meta-analysis techniques. Our goal was to address this limitation. The objectives of this systematic review were (i) to establish pooled prevalence levels of depression and anxiety among adult SLE patients; (ii) to provide a summary of the methods used to define depression and anxiety in SLE; and (iii) to explore the impacts of study characteristics on prevalence estimates.

Methods

This systematic review was conducted within the Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement [17] and followed a predetermined registered protocol (PROSPERO: CRD42016044125).

Search strategy

A systematic review of published literature in scientific journals that reported on the prevalence of depression and/or anxiety among SLE patients was conducted by two independent reviewers using the following databases from their inception to August 2016: PubMed, Embase, PsycINFO, and the Cochrane database library. The computer-based searches combined terms related to SLE patients and study design with those related to depression or anxiety (see Additional file 1). We conducted citation chasing search strategy with all reference lists of included articles and relevant review papers were considered to identify potentially omitted articles. Finally, we corresponded with the authors for further information if we encountered articles just provided the mean and standard deviation of the depression and/or anxiety assessment scale.

Inclusion and exclusion criteria

Studies were included if they met the following criteria: (i) cross-sectional design, baseline cross-sectional data from a longitudinal study or baseline cross-sectional data from a trial, before group allocation; (ii) used validated methods (clinical interviews or self-report instruments) to assess depression or anxiety; and (iii) the sample size was no less than 60.
Case reports, review articles, animal studies, studies investigating neuropsychiatric syndromes, studies in languages other than English and papers not dealing with SLE patients were excluded. For this meta-analysis, studies using pediatrics sample or screening tools without stating the cut-off thresholds used to detect depression or anxiety were also excluded. Table 2 and Table 3 presented a full list of the eligible methods of detecting depression and anxiety, alongside the numbers of articles utilizing each method and the number of participants assessed.

Data extraction and quality assessment

Two researchers read the relative studies independently by the titles and abstracts to exclude the references which did not met the inclusion criteria. Then, they read full texts in the remaining studies as mentioned above, and determined whether these references included were final studies or not. When multiple publications spanned the years of longitudinal studies, baseline prevalence levels were reported. The following information was independently extracted from each article by other two trained investigators using a standardized form: year, country, mean disease duration, percentage of female participants, sample size, average age of participants, criteria for detection of depression and anxiety, and reported prevalence of depression and/or anxiety. If we encountered multiple publications from the same cohort, we used the data from the most recent or the paper reporting data from the largest number of participants. The methodological quality of each study included in the present meta-analysis was assessed using a modified version of the Newcastle-Ottawa Scale [18]. Studies were judged to be at low risk of bias (≥3 points) or high risk of bias (<3 points). Any disagreements in data extraction and quality assessment were resolved through discussion between the two reviewers or adjudication with a third reviewer.

Outcome measures

The outcomes were major/minor depression and affective/dysthymic/adjustment/anxiety disorder diagnosed with a structured clinical assessment [e.g., Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV or International Classification of Diseases (ICD)-10] or depression and/or anxiety assessed with validated assessment tools [e.g., the Hospital Anxiety and Depression Scale (HADS), the Centre for Epidemiologic Studies Depression Scale (CES-D)] (see Additional file 2).

Statistical analyses

Because random-effects models tended to provide wider confidence intervals (CI) and were preferable in the presence of between-study heterogeneity, we used a random-effects meta-analysis to pool studies reporting the prevalence of depression and/or anxiety in SLE patients [19]. Between-study heterogeneity was assessed by the I2 with thresholds of ≥25%, ≥50% and ≥75% indicating low, moderate and high heterogeneity, respectively [20]. The influence of individual study on the overall prevalence estimate was explored by serially excluding each study in sensitivity analyses. Wherever possible, subgroup analyses were planned by overall study quality, sample size, country of origin and publication year, if there was more than one study in the subgroup. Pearson’s and Spearman’s correlation analyses were used to assess the association between variables and prevalence of depression and anxiety in people with SLE. Funnel plots and Egger’s test were combined to explore the potential publication bias in this meta-analysis [21, 22]. Statistical analyses were performed with STATA version 12.0. Statistical tests were 2-sided and used a significance threshold of P < 0.05.

Results

Search results

Fig. 1 provided the details of the study selection process. The initial search identified a total of 3347 potentially relevant articles. After removal of duplicates, titles and then abstracts were screened for potential eligibility. From this, 121 were considered in the full-text review, of which 59 articles met the inclusion criteria, and a full reference list was presented in Additional file 3. Inter-rater reliability of reviewers regarding study relevancy was high (Kappa = 0.87).

Study characteristics

A summary of the included study characteristics was shown in Table 1. A total of 59 identified studies matched the inclusion criteria, reporting on a total of 10828 adult SLE patients. Twenty took place in North America, 18 in Asia, 12 in Europe, 6 in South America, 1 in Oceania, and 1 in Africa. The median of mean ages was 39 years (range, 30.0-50.1), and the median percentage of females represented in the sample was 93% (range, 75%–100%). In addition, the median number of participants per study was 100 (range, 60–1827), and the median of mean disease duration was 9 years (range, 0.22–16.3). Depression was defined in 35 different ways (Table 2). Seventeen studies assessed for depression using the 21 Item-Beck Depression Inventory (BDI), with sixteen different thresholds were presented in the articles. Thirteen articles used the CES-D; six different cut-off points were presented, and the most commonly used being 16. Twelve used the HADS with a cutoff of 8 or more, and 6 used other screening tools. Ten studies assessed for major depression using diagnostic criteria (DSM or ICD). The most commonly used screening questionnaire to assess anxiety was the HADS, with 10 studies using this screening tool with thresholds of 8. The methods employed to assess depression and anxiety and the frequency of their use were presented in Table 2 and Table 3. When evaluated by Newcastle-Ottawa quality assessment criteria, out of 5 possible points, 2 studies received 5 points, 7 received 4 points, 13 received 3 points, 36 received 2 points, and 1 received 1 point. The details of the assessment of individual studies were shown in Additional file 4.
Table 1
Overview of prevalence studies of mood in SLE patients (N ≥ 60)
Study ID
Country
Disease duration, mean ± SD/median (range)
Women, %
Sample size
Age, mean ± SD/median (range), years
Criteria for detection of anxiety (cutoff)
Anxiety prevalence, %
Criteria for detection of depression (cutoff)
Depression prevalence, %
NOS
Abdul-Sattar 2015
Egypt
10.0 ± 4.6 years
95%
80
30.9 ± 11.7
  
CES-D (>16.7)
43.75
2
Appenzeller 2009
Brazil
64.5 ± 48.5 months
94.6%
167
32.1 ± 11.0
  
21 Item-BDI (≥10)
20.9
2
Bachen 2009
USA
15.4 ± 9.7 years
100%
326
47.9 ± 11.3
DSM-IV
64
DSM-IV
Major depressive disorder: 42.4, dysthymic disorder: 2.9
5
Bogdanovic 2015
Serbia
6.8 ± 2.9 years
100%
60
43.4 ± 12.8
  
21 Item-BDI (≥16/≥20/≥30)
91.7/70/3.3
2
Calderon 2014
Chile
Median: 32.0 (0–243.0) months
100%
82
Median: 36.0 (17.0–64.0)
  
HADS (≥8)
37
2
Cho 2014
South Korea
NS
90.1%
201
41.3 ± 13.2
  
CES-D (≥16)
39.3
3
Chin 1993
Malaysia
4.1 ± 3.5 years
95%
79
31.1 ± 9.1
ICD-9 and DSM-III
7.6
ICD-9 and DSM-III
Major depressive disorder: 6.3, dysthymic disorder: 32.9
2
Da Costa 2005
Canada
13.8 ± 10.1 years
100%
100
45.4 ± 14.0
  
CES-D (≥16)
31
3
Doria 2004
Italy
9.9 ± 6.3 years
87.3%
126
38.9 ± 11.9
HAS (≥6/≥15)
74.6/27
HDS (≥8/≥16)
40.5/2.4
2
Duvdevany 2011
Israel
11.4 ± 9.1 years
88%
100
37.0 ± 11.8
HADS (≥8)
20
HADS (≥8)
37
4
García-Carrasco 2011
Mexico
106.5 ± 85.5 months
100%
106
40.5 ± 12.0
  
CES-D (≥16)
38.8
2
García-Carrasco 2013
Mexico
10.5 ± 7.4 years
100%
105
43.6 ± 11.3
  
CES-D (≥16)
33
2
Greco 2009
USA
16.3 ± 7.0 years
100%
161
50.1 ± 10.0
  
CES-D (≥16)
27
2
Hanly 2015
Canada
5.6 ± 4.8 years
88.9%
1827
35.1 ± 13.3
  
DSM-IV
12.7
4
Harrison 2006
USA
15.3 ± 3.2 years
100%
93
43.3 ± 13.7
  
CES-D (>27)
16.1
2
Huang 2007
China
7.5 ± 6.9 years
91.5%
129
37.4 ± 10.7
HADS (≥8)
32
HADS (≥8)
20
2
Iverson 2002
Canada
NS
NS
103
NS
  
21 Item-BDI (≥17)
39.8
1
Jarpa 2011
Chile
Median: 5.0 (0.1–40.0) years
90.8%
87
Median: 39.0 (16.0–27.0)
DSM-IV
18.1
DSM-IV
Major depressive disorder: 21.7, dysthymic disorder: 4.8
2
Julian 2011
USA
15.8 ± 9.3 years
93%
150
48.8 ± 12.3
  
ICD-10 and DSM-IV
Major depressive disorder: 17, dysthymic disorder: 4, minor depression: 6
3
Jung 2015
Korea
6.8 ± 4.4 years
93%
100
40.6 ± 10.3
  
21 Item-BDI (≥21)
13
2
Katz 2011
USA
13.6 ± 8.5 years
100%
716
48.1 ± 12.6
  
CES-D (≥24)
25
3
Karol 2013
USA
NS
93%
127
38.1 ± 12.3
  
21 Item-BDI (≥18)
41.7
2
Karimifar 2013
Iran
4.1 ± 0.5 years
80%
100
34.8 ± 10.9
  
21 Item-BDI (≥14)
60
2
Kheirandish 2015
Iran
9.0 ± 7.7 years
92.2%
166
33.1 ± 11.1
Cattell questionnaire (≥21)
84.9
21 Item-BDI (≥5/≥30)
64.5/9
2
Kotsis 2014
Greece
13.2 ± 9.1 years
84%
75
44.1 ± 13.3
  
PHQ-9 (≥10)
29.3
2
Kim 2015
USA
12.0 ± 8.0 years
93%
89
39.0 ± 15.0
  
CES-D (≥16)
63
3
Lapteva 2006
USA
13.8 ± 10.2 years
75%
60
41.0 ± 13.0
  
DSM-IV
Major depressive disorder: 16.6
2
Lisitsyna 2014
NS
134.9 ± 8.8 months
85.6%
180
34.6 ± 0.93
  
ICD-10
Major depressive disorder: 24.4, dysthymic disorder: 25.6, adjustment disorders: 18.9
2
Mak 2011
Singapore
54.9 ± 70.7 months
88%
60
40.5 ± 12.9
HADS (≥8)
38
HADS (≥8)
22
2
Maneeton 2013
Thailand
6.1 ± 4.8 years
98%
62
31.8 ± 9.0
HAS (≥14)
37.1
HDS (≥11)
45.2
2
Mirbagher 2016
Iran
8.3 ± 3.8 years
100%
77
36.5 ± 10.1
HADS (≥8)
71.4
HADS (≥8)
46.1
3
Monaghan 2007
Australia
10.2 ± 8.7 years
97%
60
44.4 ± 12.2
HADS (≥8)
44
HADS (≥8)
36
3
Montero-Lo’pez 2016
Spain
0.2 ± 0.7 years
100%
97
38.6 ± 9.3
SCL-90-R
4.1
SCL-90-R
5.2
2
Nery 2008
Brazil
9.8 ± 6.5 years
100%
71
34.8 ± 10.1
SCID for DSM-IV
46.5
SCID for DSM-IV
Major depressive disorder: 40.8
2
Neville 2014
Canada
10.2 ± 9.5 years
92.4%
612
46.8 ± 16.7
  
PHQ-2 (≥3)
28.1
4
Palagini 2014
Italy
15.0 ± 8.0 years
100%
81
43.6 ± 11.2
SAS (>44)
17.3
21 Item-BDI (≥11)
34.6
3
Panopalis 2010
USA
13.8 ± 8.9 years
91%
807
47.6 ± 13.1
  
CES-D (≥16)
38.5
5
Pettersson 2015
Sweden
Median: 12.0 years
92%
305
Median: 48
HADS (≥8)
34
HADS (≥8)
51
4
Postal 2016
Brazil
Median: 9.0 (0–33.0) years
96.7%
153
Median: 30.0 (10.0–62.0)
21 Item-BAI (≥8/≥16/≥26)
60.7/43.1/18.3
21 Item-BDI (≥14/≥20/≥29)
45.7/30.7/18.9
2
Radhakrishan 2011
India
NS
100%
100
18-60
SCID for DSM-IV
51
SCID for DSM-IV
Major depressive disorder: 46, adjustment disorder: 21, dysthymic disorder: 9
2
Roebuck-Spencer 2006
USA
13.8 ± 10.2 years
80%
60
41.3 ± 12.8
  
21 Item-BDI (≥14)
20
2
Segal 2012
USA
12.0 ± 2.3 years
93%
71
41.7 ± 1.5
  
CES-D (≥16)
39
2
Sehlo 2013
Saudi Arabia
6.9 ± 4.2 years
100%
80
34.8 ± 11.2
  
SCID for DSM-IV
Major depressive disorder: 11.25
2
Sfikakis 1998
Greece
7.8 ± 6.4 years
91.5%
71
37.0 ± 13.0
HAS (>17)
23.9
HDS (>17)
19.7
2
Shakeri 2015
Iran
NS
92.5%
160
30.1 ± 6.2
21 Item-BAI (≥8/≥16/≥26)
81.2/51.9/18.1
21 Item-BDI (≥21/≥31/>40)
69.3/38.7/20.6
2
Shen 2015
China
NS
91.2%
156
32.9 ± 10.2
Zung SAS (≥50)
20.51
Zung SDS (≥53)
33.33
3
Skare 2014
Brazil
8.2 ± 6.9 years
93%
100
39.2 ± 12.5
  
21 Item-BDI
(≥19/≥ 30)
21/2
2
Shorta1l 1995
England
11.0 ± 7.1 years
95%
80
41.0 ± 11.2
HADS (≥8)
39
HADS (≥8)
26
2
Stoll 2001
Switzerland
11.4 ± 9.0 years
90%
60
44.5 ± 15.4
  
HADS (≥8)
16
3
Tam 2008
China
9.7 years
95.9%
291
42.0 ± 12.0
HADS (≥8)
22
HADS (≥8)
18.2
3
Tay 2015
Singapore
72.3 ± 81.1 months
86.4%
110
38.7 ± 12.6
HADS (≥8)
40.9
HADS (≥8)
15.5
2
Tench 2000
England
Median: 36.0 (12.0–79.5) months
100%
120
Median: 38.0 (32.0–45.0)
HADS (≥8)
60
HADS (≥8)
37
2
Tjensvoll 2010
Norway
12.3 ± 8.6 years
87%
63
43.4 ± 13.3
  
21 Item-BDI
(≥13)
23.8
2
Utset 2014
USA
Median: 9 years
95%
344
>18
  
CES-D (>10)
54.5
4
van Exel 2013
Netherlands
7.8 ± 7.0 years
88.2%
102
44.4 ± 12.5
  
21 Item-BDI
(≥14)
27
3
Vina 2015
USA
143.2 ± 117.8 months
93%
343
44.4 ± 12.9
  
CES-D (≥17)
47.2
4
Weder-Cisneros 2004
USA
Mean: 97.0 (6–348) months
91.4%
81
31.2 ± 9.7
  
21 Item-BDI
(≥14)
40.7
3
Xie 2012
China
Median: 1.3 years
93.7%
285
34.0 ± 13.0
  
21 Item-BDI
(≥5/14/≥21)
59.3/40.7/19.3
4
Zakeri 2012
Iran
NS
90.5%
71
>18
  
21 Item-BDI
(≥16/≥32)
60/9.4
2
NS not stated, CES-D Centre for Epidemiological Studies Depression Scale, BDI Beck Depression Inventory, BAI Beck Anxiety Inventory, DSM-III/IV Diagnostic and Statistical Manual of Mental Disorders, Third/Fourth Edition, HADS Hospital Anxiety and Depression Scale, ICD International Classification of Diseases, HAS the Hamilton Anxiety Scale, HDS the Hamilton Depression Scale, PHQ Patient Health Questionnaire, SCID Structured Clinical Interview for Diagnostic and Statistical Manual, SCL-90-R Symptoms Checklist-90-Revised, Zung SAS Zung Self-rating Anxiety Scale, Zung SDS Zung Self-rating Depression Scale
Table 2
Methods of detecting depression and summary of prevalence and heterogeneity findings
Tool
Definition/cutoff
No. of studies
No. of participants
Prevalence, % (95% CI)
Heterogeneity I2, %
DSM and/or ICD
     
Major depressive disorder
 
10
2960
24 (16, 31)
95.2
Dysthymic disorder
 
6
922
12 (5, 18)
93.4
Adjustment disorder
 
2
280
20 (15, 24)
0.0
Minor depression
 
1
150
6 (2, 10)
-
HADS
≥8
12
1474
30 (22, 38)
91.6
CES-D
>10
1
344
55 (49, 60)
-
 
≥16
8
1640
38 (32, 44)
81.3
 
>16.7
1
80
44 (33, 55)
-
 
≥17
1
343
47 (42, 52)
-
 
≥24
1
716
25 (22, 28)
-
 
>27
1
93
16 (9, 24)
-
21 Item-BDI
≥5
2
451
61 (56, 66)
17.7
 
≥10
1
167
21 (15, 27)
-
 
≥11
1
81
35 (24, 45)
-
 
≥13
1
63
24 (13, 34)
-
 
≥14
6
781
39 (29, 49)
88.2
 
≥16
2
131
76 (45, 107)
95.4
 
≥17
1
103
40 (30, 49)
-
 
≥18
1
127
42 (33, 50)
-
 
≥19
1
100
21 (13, 29)
-
 
≥20
2
213
50 (12, 89)
96.8
 
≥21
3
545
34 (2, 65)
98.8
 
≥29
1
153
19 (13, 25)
-
 
≥30
3
326
5 (0, 9)
72.1
 
≥31
1
160
39 (31, 46)
-
 
≥32
1
71
9 (3, 16)
-
 
>40
1
160
21 (14, 27)
-
HDS
≥8
1
126
41 (32, 49)
-
 
≥11
1
62
45 (33, 58)
-
 
≥16
1
126
2 (0, 5)
-
 
>17
1
71
20 (10, 29)
-
PHQ-9
≥10
1
75
29 (19, 40)
-
PHQ-2
≥3
1
612
28 (25, 23)
-
SCL-90-R
 
1
97
5 (1, 10)
-
Zung SDS
≥53
1
156
33 (26, 41)
-
DSM Diagnostic and Statistical Manual of Mental Disorders, ICD International Classification of Diseases, HADS Hospital Anxiety and Depression Scale, CES-D Centre for Epidemiological Studies Depression Scale, BDI Beck Depression Inventory, HDS Hamilton Depression Scale, PHQ Patient Health Questionnaire, SCL-90-R Symptoms Checklist-90-Revised, Zung SDS Zung Self-rating Depression Scale
Table 3
Methods of detecting anxiety and summary of prevalence and heterogeneity findings
Tool
Definition/cutoff
No. of studies
No. of participants
Prevalence, % (95% CI)
Heterogeneity I2, %
DSM and/or ICD for anxiety disorder
 
5
663
37 (12, 63)
98.3
HADS
≥8
10
1332
40 (30, 49)
93.0
21 Item-BAI
≥8
2
313
71 (51, 91)
94
 
≥16
2
313
48 (39, 56)
59.2
 
≥26
2
313
18 (14, 22)
0
HAS
≥6
1
126
75 (67, 82)
-
 
≥14
1
62
37 (25, 49)
-
 
≥15
1
126
27 (19, 35)
-
 
>17
1
71
24 (14, 34)
-
Cattell questionnaire
≥21
1
166
85 (79, 90)
-
SCL-90-R
 
1
97
4 (0, 8)
-
Zung SAS
>44
1
81
17 (9, 26)
-
 
≥50
1
156
21 (14, 27)
-
DSM Diagnostic and Statistical Manual of Mental Disorders, ICD International Classification of Diseases, HADS Hospital Anxiety and Depression Scale, BAI Beck Anxiety Inventory, HAS Hamilton Anxiety Scale, SCL-90-R Symptoms Checklist-90-Revised, Zung SAS Zung Self-rating Anxiety Scale

Prevalence of depression among SLE patients

Prevalence estimates of depression ranged from 2% to 91.7% in individual studies (Table 1). Table 2 indicated the summary of meta-analyses and heterogeneity assessments. Meta-analyses revealed the prevalence of major depressive disorder to be 24% (95% CI, 16%–31%) according to the DSM and/or ICD diagnostic criteria, with high heterogeneity (I2 = 95.2%). Prevalence estimates of depression were 30% (95% CI, 22%–38%, I2 = 91.6%) for the HADS with thresholds of 8 and 38% (95% CI, 32%–44%, I2 = 81.3%) for the CES-D with thresholds of 16, respectively. Prevalence of depression according to the 21 Item-BDI with a cutoff of 14 or more was 39% (95% CI, 29%–49%), with high heterogeneity (I2 = 88.2%) (Fig. 2).

Prevalence of anxiety among SLE patients

Prevalence of anxiety alone ranged between 4% and 85% in individual studies (Table 1). Table 3 presented the summary of meta-analyses and heterogeneity assessments. Meta-analyses pooled the prevalence of anxiety to be 40% (95% CI, 30%–49%, I2 = 93.0%) and 37% (95% CI, 12%–63%, I2 = 98.3%) according to the HADS with thresholds of 8 and the DSM and/or ICD diagnostic criteria, respectively (Fig. 3).

Sensitivity and subgroup analyses

Table 4 suggested depression and anxiety prevalence estimates according to each sensitivity and subgroup analysis, in comparison with the primary analysis. Sensitivity analyses revealed that the exclusion of studies with less sample representativeness tended to decrease dysthymic disorder prevalence estimates according to DSM and/or ICD. The removal of studies with less comparable respondent and non-respondent comparability tended to increase depression prevalence estimates according to the HADS with a cutoff of 8 or more. According to DSM and/or ICD, anxiety prevalence estimates had a trend to decrease by exclusion of studies only using female sample. The subgroup analyses were conducted according to sample size, overall quality, publication year, and country of origin. The results showed that studies with sample size <200 had higher anxiety estimates [43% (95% CI, 31%–55%) vs 28% (95% CI, 16%–40%)] according to the HADS with a cutoff of 8 or more. When evaluated by Newcastle-Ottawa criteria, studies with lower total overall quality scores yielded higher dysthymic disorder estimates [18% (95% CI, 6%–29%) vs 3% (95% CI, 2%–25%)] according to DSM and/or ICD. In contrast with clinical interviews (DSM and/or ICD), more recent publications tended to yield higher depression and anxiety prevalence estimates according to self-report instruments. The subgroup analyses for country of origin showed no clear patterns. There was no particular trend or pattern in any other sensitivity analyses or subgroup analyses.
Table 4
Impact of study characteristics on prevalence estimates for depression and anxiety in SLE: sensitivity and subgroup analyses
Depression definition (cutoff)
Anxiety definition (cutoff)
 
Major depressive disorder (DSM and/or ICD)
Dysthymic disorder (DSM and/or ICD)
HADS (≥8)
CES-D (≥16)
21 Item-BDI (≥14)
21 Item-BDI (≥21)
21 Item-BDI (≥30)
HADS (≥8)
Anxiety disorder
(DSM and/or ICD)
Primary analysis
24 (16, 31)
I2 = 95.2%
10 studies
2960 patients
12 (5, 18)
I2 = 93.4%
6 studies
922 patients
30 (22, 38)
I2 = 91.6%
12 studies
1474 patients
38 (32, 44)
I2 = 81.3%
8 studies
1640 patients
39 (29, 49)
I2 = 88.2%
6 studies
781 patients
34 (2, 65)
I2 = 98.8%
3 studies
545 patients
5 (0, 9)
I2 = 72.1%
3 studies
326 patients
40 (30, 49)
I2 = 93.0%
10 studies
1332 patients
37 (12, 63)
I2 = 98.3%
5 studies
663 patients
Sensitivity analyses
 
Excluding studies with less sample representativeness
24 (6, 42)
I2 = 98.2%
3 studies
2303 patients
3 (2, 5)
I2 = 0%
2 studies
476 patients
29 (15, 44)
I2 = 82.7%
3 studies
220 patients
-
36 (27, 45)
I2 = 72.4%
3 studies
468 patients
-
-
31 (8, 55)
I2 = 90.1%
2 studies
160 patients
-
Excluding studies with less comparable respondent and non-respondent comparability
-
-
45 (37, 54)
I2 = 68.1%
3 studies
482 patients
44 (29, 59)
I2 = 91.9%
3 studies
996 patients
-
-
-
42 (17, 66)
I2 = 96.9%
3 studies
482 patients
-
Excluding studies
only using female sample
16 (11, 21)
I2 = 79.8%
6 studies
2383 patients
16 (4, 28)
I2 = 95.0%
4 studies
496 patients
27 (17, 36)
I2 = 92.9%
9 studies
1195 patients
44 (35, 54)
I2 = 85.6%
4 studies
1168 patients
39 (29, 49)
I2 = 88.2%
6 studies
781 patients
34 (2, 65)
I2 = 98.8%
3 studies
545 patients
5 (−2, 12)
I2 = 85.9%
2 studies
266 patients
33 (27, 39)
I2 = 79.4%
8 studies
1135 patients
12 (2, 23)
I2 = 76.5%
2 studies
166 patients
Subgroup analyses
 
Sample size
 
<200
22 (14, 31)
I2 = 90.5%
8 studies
807 patients
14 (5, 23)
I2 = 93.3%
5 studies
596 patients
29 (22, 36)
I2 = 81.1%
10 studies
878 patients
38 (28, 48)
I2 = 86.3%
6 studies
1008 patients
39 (25, 52)
I2 = 90.5%
5 studies
496 patients
41 (−14, 96)
I2 = 99.2%
2 studies
260 patients
5 (0, 9)
I2 = 72.1%
3 studies
326 patients
43 (31, 55)
I2 = 91.8%
8 studies
736 patients
30 (9, 52)
I2 = 96.0%
4 studies
337 patients
≥200
27 (2, 57)
I2 = 99.1%
2 studies
2153 patients
-
35 (2, 67)
I2 = 98.8%
2 studies
596 patients
39 (36, 42)
I2 = 0.0%
2 studies
632 patients
-
-
-
28 (16, 40)
I2 = 90.8%
2 studies
596 patients
-
Overall quality
 
<3 points (low quality)
23 (13, 34)
I2 = 91.8%
7 studies
657 patients
18 (6, 29)
I2 = 93.2%
4 studies
446 patients
26 (18, 33)
I2 = 77.5%
6 studies
581 patients
34 (28, 40)
I2 = 45.5%
4 studies
443 patients
42 (21, 63)
I2 = 93.8%
3 studies
313 patients
41 (−14, 96)
I2 = 99.2%
2 studies
260 patients
5 (0, 9)
I2 = 72.1%
3 studies
326 patients
42 (32, 52)
I2 = 82.5%
5 studies
499 patients
30 (9, 52)
I2 = 96.0%
4 studies
337 patients
≥3 points (high quality)
26 (6, 42)
I2 = 98.2%
3 studies
2303 patients
3 (2, 5)
I2 = 0%
2 studies
476 patients
34 (20, 48)
I2 = 95.0%
6 studies
893 patients
42 (33, 52)
I2 = 87.9%
4 studies
1197 patients
36 (27, 45)
I2 = 72.4%
3 studies
468 patients
-
-
38 (23, 53)
I2 = 95.5%
5 studies
833 patients
-
Publication year
 
1990s
-
-
-
-
-
-
-
-
-
2000s
33 (17, 50)
I2 = 91.0%
3 studies
457 patients
-
25 (17, 33)
I2 = 81.3%
5 studies
660 patients
28 (23, 34)
I2 = 0.0%
2 studies
261 patients
30 (10, 51)
I2 = 86.8%
2 studies
141 patients
-
-
39 (22, 57)
I2 = 95.0%
4 studies
600 patients
56 (39, 73)
I2 = 86.3%
2 studies
397 patients
2010-
21 (14, 29)
I2 = 91.5%
6 studies
2424 patients
11 (2, 19)
I2 = 92.0%
4 studies
517 patients
35 (22, 48)
I2 = 93.1%
6 studies
734 patients
42 (35, 48)
I2 = 78.6%
6 studies
1379 patients
43 (32, 55)
I2 = 88.5%
4 studies
640 patients
34 (2, 65)
I2 = 98.8%
3 studies
545 patients
5 (0, 9)
I2 = 72.1%
3 studies
326 patients
41 (26, 56)
I2 = 93.8%
5 studies
652 patients
34 (2, 67)
I2 = 96.1%
2 studies
187 patients
Country of origin
 
North America
22 (8, 37)
I2 = 97.3%
4 studies
2363 patients
3 (2, 5)
I2 = 0%
2 studies
476 patients
-
38 (31, 45)
I2 = 83.9%
7 studies
1439 patients
30 (10, 51)
I2 = 86.8%
2 studies
141 patients
-
-
-
-
Asia
21 (0, 41)
I2 = 96.0%
3 studies
259 patients
21 (−3, 44)
I2 = 93.7%
2 studies
179 patients
26 (18, 34)
I2 = 85.4%
6 studies
767 patients
-
50 (31, 69)
I2 = 91.3%
2 studies
385 patients
34 (2, 65)
I2 = 98.8%
3 studies
545 patients
-
37 (23, 51)
I2 = 94.4%
6 studies
767 patients
29 (−13, 72)
I2 = 98.2%
2 studies
179 patients
Europe
-
-
33 (17, 49)
I2 = 93.8%
4 studies
565 patients
-
-
-
-
44 (28, 61)
I2 = 91.9%
3 studies
505 patients
-
South America
31 (12, 50)
I2 = 85.3%
2 studies
158 patients
-
-
-
-
-
-
-
32 (4, 60)
I2 = 93.5%
2 studies
158 patients
The first line in each set of data is percentage prevalence (95% CI)
DSM Diagnostic and Statistical Manual of Mental Disorders, ICD International Classification of Diseases, HADS Hospital Anxiety and Depression Scale, CES-D Centre for Epidemiological Studies Depression Scale, BDI Beck Depression Inventory

Associated study variables

We used Pearson’s and Spearmen’s correlation analyses to assess the association between variables including mean/medium disease duration, proportion of female participants, mean/medium age, representativeness, sample size, comparability, overall quality, country of origin, publication year, and the prevalence of depression and anxiety. Table 5 indicated that more recent publications was significantly associated with increased depression prevalence (r = 0.26, P = 0.04). No study characteristics presented a significant association with anxiety prevalence estimate.
Table 5
Pearson's and Spearmen’s correlation between study characteristics and prevalence estimates
Study characteristic
Depression prevalence estimate
Anxiety prevalence estimate
No. of studies
r
P
No. of studies
r
P
Female, %
59
0.03
0.84
24
0.07
0.76
Mean/medium age, year
55
−0.13
0.35
23
−0.18
0.94
Mean/medium disease duration, year
53
−0.07
0.64
21
0.24
0.29
Representativeness
59
0.03
0.85
24
0.08
0.70
Sample size
59
0.12
0.38
24
0.01
0.97
Comparability
59
0.24
0.07
24
−0.11
0.61
Overall quality
59
0.13
0.33
24
−0.10
0.64
Country of origin
59
0.01
0.92
24
−0.10
0.63
Publication year
59
0.26*
0.04
24
−0.04
0.84
*Significant at a P <0.05 level

Assessment of publication bias

Assessment of publication bias indicated significant publication bias, according to the Egger’s test, in studies reporting depression according to HADS with thresholds of 8 and CES-D with a cutoff of 16 or more [Egger: bias = 0.81 (95% CI: 0.04, 1.58), P = 0.04, and Egger: bias = 2.79 (95% CI: 0.61, 4.97), P = 0.02, respectively]. There was no significant evidence of publication bias in any other analyses (see Additional file 5).

Discussion

This systematic review and meta-analysis of 59 studies involving 10828 adult SLE patients demonstrated that a few studies using gold standard clinical interviews (DSM and/or ICD) reported that major depression and anxiety were presented in 24% and 37% among SLE patients, respectively. The majority of studies using screening tools found that significant depression were presented in 30% using the HADS a cutoff of 8 or more and 39% using the 21 Item-BDI with thresholds of 14. This study also found that more recent publications was significantly associated with increased depression prevalence among SLE patients. Furthermore, the prevalence of anxiety was 40% according to the HADS with thresholds of 8. These prevalence estimates are significantly higher than those observed in the general population [23, 24] and other rheumatic and connective tissue diseases [15, 25, 26]. Furthermore, these findings demonstrated that SLE patients tended to have a higher prevalence of anxiety than depression, which was in line with previous studies [27, 28]. Such discrepancy could be explained by the differences in time frames when these studies were performed, disease characteristics, social and cultural contexts of the lupus patients and tools used for assessing depression or anxiety. Because the development of depression and/or anxiety could result in increased incidence of cardiovascular diseases [5], decreased quality of life [9, 10], and a higher risk of premature mortality [11] among SLE patients, these findings highlighted an important issue in health education for this population.
Neuropsychiatric (NP) disorders appeared in about 70% of the patients diagnosed with SLE [29]. Previous meta-analyses have assessed the prevalence of the 19 NP syndromes defined by the American College of Rheumatology (ACR) in 1999 among SLE patients [30]. However, there were a wide variety of neurologic and psychiatric manifestations of SLE, which extended beyond those identified in the 1999 ACR classification criteria for SLE [31]. Several attempts have been made to devise a classification of NP-SLE manifestations because there were controversies regarding the inclusion of mood disorders in the 1999 ACR NP-SLE criteria [31, 32]. That’s why we excluded the studies investigating neuropsychiatric syndromes among SLE patients in this meta-analysis.
Although studies varied widely in terms of quality, our sensitivity analyses suggested that depression and/or anxiety prevalence estimates (except dysthymic disorder estimates) were reasonably stable. Variation in study sample size contributed importantly to the observed heterogeneity in the data. Studies with sample size <200 had higher anxiety estimates according to the HADS with thresholds of 8. Furthermore, studies with lower total overall quality scores yielded higher dysthymic disorder estimates according to DSM and/or ICD. Country, publication year, age, and gender also contributed to the heterogeneity between studies.
In this meta-analysis, many methods were used for data extraction and synthesis. The gold standard method was diagnostic interviews using DSM or ICD criteria, which were often time consuming and expensive. Therefore, it was not ideal for examining patients in a busy hospital environment [33]. Alternatively, self-report screening tools might be used, because they were quick and easy to complete and cheaper to use than diagnostic interviews. However, prevalence estimates using screening tools were often overestimated, because such tools tended to prioritize sensitivity over specificity [33]. Furthermore, there have not been validation studies to determine the best cut-point for screening tools in SLE patients, and several cut-off scores on self-report tools were often used in many studies. It indicated that the rheumatologists should always report prevalence at conventional cut-points, and screen for depression and anxiety among SLE patients according to the social and cultural contexts of the rheumatologists and SLE patients in clinical practice.
There are, however, additional important shortcomings in the evidence on prevalence of depression in SLE that need to be addressed. First, a substantial amount of the heterogeneity among the studies remained unexplained by the variables examined. Unexamined factors, such as gender, age, disease duration, might contribute to the risk for depression and/or anxiety symptom among SLE patients. Second, the data were derived from studies that used different designs and involved different groups of patients (e.g., from different countries), which might result in heterogeneity among the studies. Third, we did not look for healthy subjects in each study reporting the prevalence of depression or anxiety in SLE patients, which should be addressed in future research.

Conclusions

The prevalence of depression and anxiety was high in adult SLE patients. It indicated that rheumatologists should screen for depression and anxiety in their patients, and they should refer them to mental health providers in order to identify effective strategies for preventing and treating depression and anxiety among SLE patients.

Acknowledgments

We would like to thank Chenlin Zhang and Alick for their great assistance with this study.

Funding

This work was supported by the Natural Science Foundation of China (Grant no. 81401124); the Humanistic Nursing Care Foundation of China (Grant no. RW2016AM14); Preventive Medicine Projects from Bureau of Jiangsu Province (Y2012083); “Top Six Types of Talents” Financial Assistance of Jiangsu Province (Grant no. 10.WSN016); Jiangsu Provincial Commission of Health and Family Planning Foundation (Grant no. Z201622); Science Foundation of Nantong City (Grant no. MS22015003); the College graduate research and innovation of Jiangsu Province (KYZZ15_0353); and the Nantong University Graduate Innovation Program (YKC15075).

Availability of data and materials

The majority of data generated or analyzed during this study are included in this published article (and its Additional files). Remaining data not published here are available from the corresponding author on reasonable request.

Authors’ contributions

LZ and TF searched and checked the databases according to the inclusion and exclusion criteria, extracted the data and assessed their quality. LZ analyzed the data and wrote the draft of the paper. RY, QZ and BS gave advice on meta-analysis methodology and revised the paper. All authors contributed to reviewing or revising the paper. BS is the guarantor of this work and had full access to all the data in the study and takes responsibility for its integrity and the accuracy of the data analysis. All authors read and approved the final manuscript.

Competing interests

The authors declared that they have no competing interests.
Not applicable.
Ethical approval and consent to participate are not required for this review.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
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Metadaten
Titel
Prevalence of depression and anxiety in systemic lupus erythematosus: a systematic review and meta-analysis
verfasst von
Lijuan Zhang
Ting Fu
Rulan Yin
Qiuxiang Zhang
Biyu Shen
Publikationsdatum
01.12.2017
Verlag
BioMed Central
Erschienen in
BMC Psychiatry / Ausgabe 1/2017
Elektronische ISSN: 1471-244X
DOI
https://doi.org/10.1186/s12888-017-1234-1

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