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Pain and fatigue are predictors of quality of life in primary Sjögren’s syndrome

Pain and fatigue are predictors of quality of life in primary Sjögren’s syndrome Background: Few studies have evaluated the relation of quality of life (QoL) with symptoms and disease activity in primary Sjögren’s syndrome (pSS). There is also scant information on the predictors of QoL in this population. The aim of this study was to assess QoL in patients with pSS and to investigate their possible predictors. Methods: In a cross-sectional study, 77 patients with pSS were evaluated using the following questionnaires: Functional Assessment of Chronic Illness Therapy Fatigue Subscale (FACIT-Fatigue), EULAR Sjögren’s Syndrome Patient Reported Index (ESSPRI), EULAR Sjögren’s Syndrome Disease Activity Index (ESSDAI), Short Form-36 Health Survey (SF-36) and World Health Organization Quality of Life Assessment (WHOQOL-BREF). Seventy-seven healthy controls responded to the SF-36 and WHOQOL-BREF. The Mann-Whitney test, t-test, Pearson and Spearman correlation, and multiple regression analysis were used in the statistical analysis. Results: Patients with pSS and healthy controls were matched by gender and age. The mean scores for the ESSDAI, ESSPRI and FACIT-Fatigue were 3.34 ± 4.61, 6.58 ± 2.29 and 26.17 ± 11.02, respectively. Patients had a lower employment rate (36.4% versus 62.3%, p < 0.01) and higher work disability (10.4% versus 1.3%, p < 0.01). SF-36 and WHOQOL-BREF values were lower in patients with pSS (p < 0.001), except in the WHOQOL-BREF environment domain. Pain (ESSPRI), fatigue (FACIT-Fatigue), antinuclear antibody (ANA), anti-Ro-SSA and economic class (Brazilian Economic Classification Criteria - CCEB) were independent predictors of QoL. Conclusions: The main predictors of poor QoL in patients with pSS were pain and fatigue, and these symptoms had an impact regardless of disease activity, age, schooling, marital status, work disability and fibromyalgia. Keywords: Sjögren’s syndrome, Quality of life, Pain, Fatigue Introduction production of pathogenic autoantibodies [1]. Primary Primary Sjögren syndrome (pSS) is an autoimmune, Sjögren syndrome affects mainly Caucasian women chronic and systemic disease that causes an inflammatory in the 4th to 5th decade of life and presents a broad lymphocyte infiltrate with dysfunction of the salivary and clinical spectrum, with extraglandular manifestations lacrimal glands, leading to xerostomia and xerophthalmia. occurring in more than two-thirds of cases, the most Epigenetic mechanisms such as DNA demethylation in epi- common being arthralgia or arthritis, Raynaud’s thelial cells and altered expression of microRNAs in salivary phenomenon, skin vasculitis, interstitial pneumonitis glands act on genetically susceptible patients, leading to the and pulmonary fibrosis, peripheral neuropathy, and tubulointerstitial and glomerular nephritis [2–4]. Fatigue, a physical or mental feeling of tiredness, also * Correspondence: val.valim@gmail.com affects approximately 70% of these patients and is Department of Clinical Medicine, Cassiano Antonio Moraes University Hospital / EBSERH, Federal University of Espírito Santo (Ufes), Av. Marechal strongly associated with psychosocial factors, occupa- Campos, 1468, Maruípe, Vitória, ES CEP: 29075-910, Brazil tional dysfunction and a greater number of medical visits Brazilian Society of Rheumatology, São Paulo, Brazil but not with sicca severity or laboratory features [5, 6]. Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Dias et al. Advances in Rheumatology (2021) 61:28 Page 2 of 9 In pSS, pain can be explained by different reasons, such circulation areas of the hospital, as well as donors from as arthritis, pain amplification, and neuropathy. Arthritis the blood bank. The exclusion criteria were having auto- is usually symmetrical, predominantly in peripheral and immune rheumatic disease at < 18 years of age and any small joints, and may precede or appear simultaneously other comorbidity. All patients signed the ICF. The Re- with sicca symptoms. Small-fiber neuropathy is the most search Ethics Committee (REC) of HUCAM, protocol common cause of neuropathic pain and is characterized number 178.520, approved the project on January 30, by distal paraesthesias, allodynia, and burning and itch- 2013. ing sensations. Half of the pSS patients present wide- Demographic data such as age, gender, self-reported spread pain, and combined with fatigue and sleep color, level of schooling, income by the Brazilian Eco- disorders, the diagnosis of associated fibromyalgia may nomic Classification Criteria (CCEB) [24], labor status, be considered [7]. work disability (sick leave or early retirement), as well as PSS patients have low quality of life (QoL) in the phys- clinical data such as diagnosis of fibromyalgia (American ical, emotional and social dimensions evaluated by dif- College of Rheumatology - ACR 1990 or ACR 2010) [25, ferent instruments, such as the Short Form-36 Health 26], salivary gland biopsy, presence of antinuclear anti- Survey (SF-36), the World Health Organization Quality bodies (ANA), rheumatoid factor (RF), anti-SSA/Ro and of Life – BREF (WHOQOL-BREF) and the EuroQol 5- anti-SSB/La were collected from medical records and dimensions (EQ-5D) [8–20]. There is also an increase in physician interview. health expenditures, both individual and social, and a Minor salivary gland biopsies were performed and ana- higher frequency of work withdrawal in this population. lyzed by rheumatologists and pathologists with experience QoL can be influenced by several factors, such as age, in pSS and were considered positive when the histopath- schooling and socioeconomic level [6, 9, 11, 12, 21]. ology showed one or more lymphocytic infiltrates with Considering the aspects related to the disease itself, more than 50 mononuclear cells in an area of 4 mm [24]. pain, fatigue and dryness are associated with worse QoL The anti-SSA/Ro and anti-SSB/La laboratory tests were [11–13, 16, 17, 19, 22]. Comorbidities such as depres- performed by the hemagglutination technique, while ANA sion, anxiety, and fibromyalgia are also negatively corre- was performed by indirect immunofluorescence and RF lated [11, 18]. The association with immunological and by the latex test. biological variables is controversial or weak. Hypergam- To evaluate the activity of the disease, two physicians maglobulinemia, the presence of anti-SSA/Ro, anti-SSB/ experienced in pSS applied the ESSDAI. It has 12 La antibodies, antinuclear antibody (ANA) or rheuma- domains of systemic evaluation (constitutional, lymph- toid factor (RF), cytopenias, high cytokine levels or adenopathy, glandular, articular, cutaneous, respiratory, salivary gland biopsy do not correlate with worse QoL, renal, muscular, peripheral and central nervous system, while extraglandular manifestations, mainly articular and hematological and biological). The domains have differ- pulmonary, are poorly correlated [13]. Few studies have ent weights in the final score, 0 to 123, according to the evaluated the relationship of QoL with symptoms and level of activity [27, 28]. Values lower than 5 are consid- disease activity as measured by EULAR Sjögren’s Syn- ered to indicate low disease activity; values from 5 to 13, drome Patient Reported Index (ESSPRI) and EULAR moderate activity; and values greater than or equal to Sjögren’s Syndrome Disease Activity Index (ESSDAI) 14, high activity [29]. [17, 19]. There is also little information on the predic- Symptoms and QoL were assessed using self-administered tors of QoL in this population [11, 17, 19]. questionnaires, and a trained professional was available to The objective of this study was to evaluate whether assist participants when needed. PSS patients answered the disease activity or symptoms such as pain, dryness, and ESSPRI, which measures three symptoms related to the dis- fatigue are predictors of QoL regardless of other clinical- ease: dryness, pain and fatigue. Each domain ranges from 0 epidemiological features in patients with pSS. to 10, and the result is the average of the three domains [30]. Values less than 5 are considered acceptable [29]. Methods Fatigue in pSS patients was evaluated through the A cross-sectional study was conducted from January to Functional Assessment of Chronic Illness Therapy - July 2013 at the University Hospital of Federal University fatigue (FACIT-fatigue). The FACIT system originally of Espírito Santo (HUCAM), in Vitória, Brazil. developed to evaluate QoL in cancer patients has been PSS patients who met the American – European clas- widely used in several chronic diseases. Its score ranges sification criteria (AECG) [23] and signed the informed from 0 to 52, and its value is inversely proportional to consent form (ICF) were included. Secondary Sjögren’s the degree of fatigue [31]. syndrome patients were excluded. The SF-36 and WHOQOL-BREF questionnaires were The control group consisted of healthy individuals used to assess QoL in pSS patients and healthy controls. matched by gender and age who were in external The SF-36 is an easy-to-administer instrument Dias et al. Advances in Rheumatology (2021) 61:28 Page 3 of 9 consisting of 36 items divided into 8 domains: physical Table 1 Demographic and clinical data in pSS patients and healthy controls functioning, physical role functioning, bodily pain, gen- eral health, vitality, social functioning, emotional role pSS (n = 77) Controls (n = 77) functioning and mental health. These can be grouped Age, mean, years 52.34 (9.03) 52.27 (8.91) into two components that summarize the dimensions: Ethnicity physical (PCS) and mental (MCS) component summar- Black (%) 11.7 13 ies. Its final score ranges from 0 to 100, and the higher Brown (%) 59.7 49.4 the score, the better the overall health condition [32]. White (%) 24.7 37.7 Developed by the World Health Organization (WHO), Indigenous (%) 2.6 0 the WHOQOL-BREF is an abbreviated version of the WHOQOL-100. It is composed of 26 questions. The Education first two questions are general QoL issues, and the < 8 years (%) 50.7 57.2 remaining 24 facets will form four domains: physical, ≥ 8 years (%) 48.1 40.3 psychological, social relations and environment. The Never studied (%) 1.2 2.5 total score ranges from zero to 100, and the higher its Marital status value, the better the QoL [33, 34]. Married (%) 66.2 63.6 The chi-square, Fisher and likelihood ratio association tests were used for qualitative variables among patients Not married (%) 14.3 13 with pSS and healthy controls. The Kolmogorov-Smirnov Divorced/widow (%) 19.5 23.4 test was used to evaluate the normal distribution of the CCEB data. For quantitative variables, the Mann-Whitney test A (%) 1.3 0 was used when there was a breakdown of normality, and B (%) 23.4 26.6 with normal data, the t test was used. Pearson or C (%) 52 49.3 Spearman tests were used in the correlations. To identify independent predictors for quality of life, stepwise linear D (%) 18.2 24 regression analysis was performed. The variables consid- E (%) 0 0 ered in the analysis were age, weight, body mass index *Employment rate (%) 36.4 62.3 (BMI), smoking, alcoholism, marital status, schooling, Work disability (%)* 10.4 1.3 fibromyalgia, CCEB, work disability (sick leave or early re- Positive salivary biopsy 90.5 tirement), ESSDAI, ESSPRI, FACIT-Fatigue, salivary gland (focus score ≥ 1) (%) biopsy, ANA, anti-SSA/Ro, anti-SSB/La and RF. Variables Anti-SSA/Ro (%) 33.3 with a statistical significance level of 10% were included in Anti-SSB/La (%) 24 the multiple regression analysis. Statistical significance was set at a p value of ≤0.05. The Statistical Package for Antinuclear antibody (%) 68.9 the Social Sciences (SPSS), version 20.0, Armonk, New Rheumatoid factor (%) 29.2 York (NY), 2011 software was used. Fibromyalgia (%) 42.9 FACIT-Fatigue, mean, SD 26.17 (11.02) Results ESSPRI, mean, SD 6.58 (2.29) Of 127 pSS outpatients, 27 were excluded because they Fatigue, mean, SD 6.38 (2.57) did not meet the AECG, and 33 were not willing to participate. Dryness, mean, SD 6.53 (2.78) Seventy-seven pSS patients and 77 healthy women Pain, mean, SD 6.84 (3.12) were included, aged 27 to 67 years. Groups were similar Extra glandular manifestations (%) 49.4 in age, ethnicity, schooling, marital status and economic ESSDAI, mean SD 3.34 (4.61) classification. Patients had a lower employment rate pSS Primary Sjögren Syndrome, CCEB Brazilian Economic Classification Criteria, (36.4% versus 62.3%, p < 0.01) and higher work disability FACIT Fatigue – Functional Assessment of Chronic Illness Therapy-Fatigue, SD (10.4% versus 1.3%, p < 0.01). Moreover, the patients had standard deviation, ESSPRI EULAR Sjögren’s syndrome patient reported index *p < 0.01 a low disease activity (ESSDAI 3.34 ± 4.61) and a low fre- quency of autoantibodies, characterizing a sample with mild disease. Biological and articular domains were the most frequently affected. In contrast, the patients pre- The QoL measured by SF-36 and WHOQOL-BREF was sented a high level of symptoms (ESSPRI 6.58 ± 2.29). worse in patients with pSS than in healthy controls, except Among patients with pSS, the percentage of fibromyalgia for the environment domain tested by WHOQOL-BREF, was 42.9% (Table 1). which was similar for both groups (Table 2). Dias et al. Advances in Rheumatology (2021) 61:28 Page 4 of 9 Table 2 Comparison of quality of life between pSS patients and Table 3 Comparison of quality of life between patients with healthy controls acceptable and non-acceptable ESSPRI SF-36 pSS (n = 77) Controls (n = 77) ESSPRI *Physical functioning 37.3 ± 24.2 80.5 ± 20.8 Acceptable Non-acceptable SF36 *Physical role functioning 27.6 ± 35.9 73.4 ± 37.2 *Physical functioning 63.44 ± 29.08 30.83 ± 17.54 *Bodily pain 36.7 ± 22.2 69.5 ± 21.4 Physical role functioning 35.94 ± 43.75 25.00 ± 33.19 *General health 43.2 ± 17.9 69.5 ± 20.0 *Bodily pain 55.06 ± 25.69 31.80 ± 18.56 *Vitality 37.2 ± 20.6 64.8 ± 20.9 *General health 53.75 ± 19.21 40.57 ± 16.66 *Social functioning 48.3 ± 26.9 74.8 ± 23.1 Vitality 47.19 ± 34.92 34.92 ± 18.31 *Emotional role functioning 31.1 ± 38.6 69.3 ± 40.0 Social functioning 54.66 ± 47.02 47.02 ± 27.27 *Mental health 46.2 ± 22.3 67.8 ± 23.0 **Emotional role functioning 52.08 ± 25.00 25.00 ± 34.51 *PCS 33.1 ± 9.1 48.9 ± 8.5 **Mental health 56.00 ± 24.57 43.87 ± 21.05 *MCS 37.2 ± 11.4 46.8 ± 12.3 *PCS 40.21 ± 10.88 31.28 ± 7.62 WHOQOL-BREF MCS 40.83 ± 13.14 36.31 ± 10.84 *Physical health 41.6 ± 16.8 67.7 ± 16.8 WHOQOL-BREF *Psychological health 53.4 ± 18.8 63.9 ± 15.9 *Physical health 56.70 ± 19.25 37.54 ± 13.76 *Social relations 55.5 ± 22.0 65.4 ± 18.2 **Psychological health 63.02 ± 16.66 50.90 ± 18.75 Environment 49.1 ± 12.7 53.0 ± 16.5 SF-36 Short Form 36 Health Survey, pSS primary Sjögren’s Syndrome, PSC *Social relations 71.35 ± 14.58 51.11 ± 21.94 Physical Component Summary, MCS Mental Component Summary, WHOQOL- **Environment 54.88 ± 9.20 47.53 ± 13.23 BREF World Health Organization Quality of Life Assessment *p < 0.01 ESSPRI EULAR Sjögren’s syndrome patient reported index, SF-36 Short Form-36 Health Survey, PCS Physical Component Summary, MCS Mental Component Summary, WHOQOL-BREF World Health Organization quality of life – BREF *p < 0.01; **p < 0.05 In the pSS group, patients with a nonacceptable ESSP RI (≥ 5) had all WHOQOL-BREF and most SF-36 do- mains worse than patients with an acceptable ESSPRI (Table 3). Patients with pSS and fibromyalgia had worse Table 4 Comparison of QoL between pSS patients with QoL values in bodily pain (SF-36) and physical health fibromyalgia (WHOQOL-BREF) (Table 4). Fibromyalgia There was a moderate-to-strong correlation of FACIT- Yes No Fatigue with all domains of QoL questionnaires. The SF-36 Physical functioning 30.9 ± 18.9 42.6 ± 26.5 ESSPRI also correlated with all QoL domains. The ESS- DAI showed only a weak correlation with the emotional Physical role functioning 22.0 ± 30.5 32.4 ± 39.1 role functioning domain of the SF-36 and did not correl- *Bodily pain 25 ± 15.3 45.6 ± 22.4 ate with fatigue indexes (FACIT-Fatigue) and ESSPRI General health 37.9 ± 17.2 47.4 ± 17.4 (Table 5). Vitality 30.9 ± 17.4 42.2 ± 21.4 In the regression analysis, pain (ESSPRI), fatigue (FACI Social functioning 42.3 ± 25.2 53.7 ± 27.7 T-Fatigue), antinuclear antibody (ANA), anti-Ro-SSA and Emotional role functionig 28.3 ± 38.3 34.1 ± 39.0 economic class (Brazilian Economic Classification Criteria - CCEB) were independent predictors of QoL. The symp- Mental health 41.7 ± 22.7 49.6 ± 21.4 toms measured by FACIT-Fatigue and ESSPRI pain were PCS 29.7 ± 6.5 35.8 ± 9.8 the main predictors of poor QoL, regardless of age, marital MCS 35.7 ± 11.6 38.6 ± 11.1 status, schooling, work disability, disease activity and WHOQOL-BREF *Physical health 35.5 ± 15.3 46.2 ± 16.5 fibromyalgia. In the PCS of the SF-36, the predictors for Social relations 51.0 ± 23.0 58.9 ± 20.9 the worst values were pain, fatigue, and the presence of Environment 45.6 ± 11.4 51.8 ± 13.1 ANA and anti-SSA/Ro autoantibodies. Fatigue was the only predictor in the MCS of the SF-36 and psychological Psychological health 48.7 ± 19.3 56.8 ± 17.8 health domain of the WHOQOL-BREF. Pain interfered QoL Quality of Life, pSS primary Sjögren’s Syndrome, SF-36 Short Form 36 Health Survey, PSC Physical Component Summary, MCS Mental Component with the PCS of the SF-36, physical health, social relations Summary, WHOQOL-BREF World Health Organization Quality of and environmental domains of the WHOQOL-BREF Life Assessment (Table 6). *p < 0.01 Dias et al. Advances in Rheumatology (2021) 61:28 Page 5 of 9 Table 5 Correlation of quality of life, disease activity, symptoms and fatigue ESSDAI ESSPRI dryness ESSPRI fatigue ESSPRI pain ESSPRI Total FACIT-Fatigue SF36 Physical functioning 0.04 −0.44** −0.29* − 0.55** − 0.56** 0.53** Physical role functioning 0.01 −0.17 −0.08 − 0.23* −0.24* 0.35** Bodily pain 0.03 −0.33** −0.23* − 0.59** −0.53** 0.56** General health −0.08 −0.27* − 0.17 −0.34** − 0.34** 0.56** Vitality −0.04 −0.23* − 0.26* −0.36** − 0.39** 0.56** Social functioning −0.01 −0.33** − 0.18 −0.21 − 0.29* 0.45** Emotional role functioning −0.24** −0.31** − 0.11 −0.23 − 0.29* 0.48** Mental health 0.04 −0.21 −0.23* − 0.31** −0.28* 0.46** PCS 0.06 −0.35** −0.21 − 0.53** −0.5** 0.46** MCS −0.14 −0.2 − 0.17 −0.12 − 0.24* 0.48** Whoqol Bref Physical health −0.09 −0.34** − 0.19 −0.43** − 0.50** 0.68** Psychological health −0.08 −0.32** − 0.19 −0.36** − 0.38** 0.56** Social relations −0.03 −0.17 − 0.2 −0.34** − 0.33** 0.37** Environment −0.01 −0.19 − 0.18 −0.49** − 0.34** 0.32** ESSDAI −0.11 −0.01 − 0.04 −0.08 − 0.06 ESSDAI EULAR Sjögren’s syndrome disease activity index, ESSPRI EULAR Sjögren’s syndrome patient reported index, FACIT Fatigue – Functional Assessment of Chronic Illness Therapy-Fatigue, SF-36 Short Form-36 Health Survey, PCS Physical Component Summary, MCS Mental Component Summary, WHOQOL-BREF World Health Organization quality of life – BREF *p < 0.01; ‘**p < 0.05 Discussion Kingdom (UK) [18] and in 104 Korean patients [17]. In Here, PSS patients were found to have lower QoL scores contrast, Omma et al. found that the ESSDAI was an in- than healthy controls, corroborating previous studies in dependent determinant of all SF-36 domains, with the other countries [11–13, 15–19, 22]. The relevance of the exception of the vitality domain, in 105 patients from present data was to demonstrate that symptoms, but not Turkey, most of whom had low to moderate levels of disease activity, were the main predictors of low QoL. disease activity [36]. As in Liu et al.’s study [37], our re- Few studies have performed multivariate analyses to sults showed that pain and fatigue were independently identify predictors of QoL in pSS. Cornec et al. corrobo- associated with a low physical component summary rated the results of our study, showing that disease activ- (PCS) of the SF-36 and that fatigue was associated with ity is not associated with greater QoL impairments in a low mental component summary (MCS) of the SF-36. 120 French patients with moderate-to-high levels of sys- In the Cornec et al. study, only pain was associated [35]. temic activity, despite the low level of disease activity in Omma et al. demonstrated that the ESSPRI was an inde- our patients [35]. Disease activity (ESSDAI) was also not pendent determinant of bodily pain, general health, a predictor of QoL in 639 pSS patients from United mental health and PCS of the SF-36, while fatigue was Table 6 Predictors of quality of life SF-36 WHOQOL-BREF PCS MCS Physical health Psychological health Social relations Environment 2 2 2 2 2 2 R : 0.56 R : 0.22 R : 0.52 R : 0.36 R : 0.23 R : 0.30 ß p-value ß p-value ß p-value ß p-value ß p-value ß p-value ESSPRI-pain −1.16 0.00 −1.48 0.00 −1.53 0.06 −1.63 0.00 FACIT-Fatigue 0.31 0.00 0.51 0.00 0.88 0.00 1.00 0.00 0.48 0.04 ANA −4.64 0.01 Anti-SSA/Ro −4.09 0.01 CCEB − 4.91 0.05 −3.9 0.01 SF-36 Short Form-36 Health Survey, WHOQOL-BREF World Health Organization quality of life – BREF, PCS Physical Component Summary, MCS Mental Component Summary, ANA Antinuclear Antibody, CCEB Brazilian Economic Classification Criteria Dias et al. Advances in Rheumatology (2021) 61:28 Page 6 of 9 significantly correlated with four or more domains of severity in pSS [40]. A proteomic study of cerebrospinal the SF-36 [36]. fluid showed that some proteins that are increased in Results showed a correlation between the ESSDAI only pSS have a role in the downregulation of inflammation and the emotional aspects domain of the SF-36, and yet and in the cellular stress defense (hemopexin, pigment this correlation was weak, not being confirmed as a pre- epithelium-derived factor, clusterin, osteopontin, and dictor of QoL in patients with pSS. Sharing a similar re- selenium-binding protein 1). These results suggest that sult, a cohort in the UK using the EQ-5D to assess QoL some fatigue signaling pathways are associated with “cel- demonstrated a weak correlation with the ESSDAI [19]. lular protection and defense” and are not directly related Yacoub et al. used the degree of activity in salivary gland to proinflammatory factors [41]. Nonetheless, the evi- biopsy, immunological status and severity of systemic in- dence for an association between fatigue and disease ac- volvement as a way of assessing disease activity, and they tivity – or any other inflammatory markers – remains found no correlation with QoL or fatigue [13]. It is not controversial. clear why there is a weak association between disease ac- In fact, the pathogenesis of fatigue in pSS is unknown tivity (ESSDAI) and QoL. One possible answer could be but seems to be associated with a lower aerobic capacity the wide range of ESSDAI scores (0–123) in samples and lower physical activity levels, sleep disturbances, with low mean activity. In addition, ESSDAI is an index autonomic dysfunction, depression, psychological pro- that does not assess established damage, only current ac- files, and fibromyalgia [38]. It is noteworthy that, in the tivity; thus, perhaps the patient’s perception about the multiple regression models, fatigue measured by FACIT- QoL is not modified at that moment, but when there is Fatigue was the only predictor of the MCS of SF-36 and an established organic dysfunction. Other studies correl- the psychological component of WHOQOL-BREF. ating injury rates with disease activity and QoL could These data indicate that this symptom impacts not only better elucidate the issue. the physical aspects but also the mental health of these QoL was worse in patients with higher nonacceptable individuals. Other studies have pointed to depression as ESSPRI, and it was not associated with ESSDAI, corrob- an important determinant of poor QoL along with fa- orating that symptoms (fatigue, pain and dryness) im- tigue in these patients [11, 17, 18], which could partially pact QoL more than disease activity. explain the low values of the determination coefficients In pSS, QoL has been found to be associated with fa- in the mental domain of the SF-36, as well as in the psy- tigue, pain/articular involvement, ocular and oral in- chological, social relations and environmental domains volvement, pruritus, sexual dysfunction, impaired sleep, of the WHOQOL-BREF. However, we did not evaluate pulmonary manifestations, psychological dysfunction psychiatric disorders, such as depression or anxiety, and impaired physical function [20]. On the other hand, which is a limitation of this study. Interestingly, aerobic delayed diagnosis, protracted course of the disease, and exercise has been found to improve fatigue, but not QoL the lack of social support are also causes of the decline and depression [42], and resistance exercise has been in the quality of life in these patients [37]. found to improve QoL [43]. Clearly, many efforts still Fatigue is considered a hallmark of pSS [5]. In the need to be made to elucidate the pathogenesis of fatigue, present study, fatigue (FACIT-fatigue) was strongly asso- as well as to identify pharmacological and nonpharmaco- ciated with all dimensions of QoL and was an independ- logical therapies to treat fatigue and improve the QoL in ent risk factor for the physical and mental aspects of pSS. QoL in both instruments, SF-36 and WHOQOL-BREF. Pain was a determinant for lower QoL in the physical, In contrast, there was no association between fatigue social relations and environmental domains but not for and disease activity measured by the ESSDAI. Taken to- mental aspects. A large proportion of patients with pSS gether, the results suggest that fatigue is itself associated have noninflammatory musculoskeletal pain without the with pSS but may not be explained by disease activity. laboratory or clinical abnormalities of arthritis. Among Recent evidence has shown weak or no association patients with pSS, cases of pain amplification syndrome with inflammatory biomarkers such as interleukin (IL)- are associated with a benign pole of the disease, with a 1b, IL-2, IL-6, IL-10 and tumor necrosis factor alpha low frequency of autoantibodies and extraglandular (TNF-α). In the same direction, immunosuppressors and manifestations [44]. biological therapy failed to treat fatigue in pSS [38]. The prevalence of fibromyalgia in pSS varies from 12 However, Howard et al. showed that lower levels of the to 55% [7]. In our study, the prevalence was 42.9%. This pro-inflammatory cytokines inducible protein (IP)-10 large range can certainly be explained by the various cri- and interferon-gamma (IFN-γ), together with pain and teria to diagnose fibromyalgia as well as pSS that have depression, were the most important predictors of fa- been applied over time. Indeed, pain and fatigue are tigue [39], and Davies et al. demonstrated that TNF-α common symptoms in both fibromyalgia and pSS, and and LT-α have an inverse relationship with fatigue the association of the two can be a misleading factor. Dias et al. Advances in Rheumatology (2021) 61:28 Page 7 of 9 However, in the present study, fatigue and pain were the and anxiety were also not applied, and these data could main predictors of poor QoL, regardless of the diagnosis have improved the values of the mental domain deter- of fibromyalgia, indicating that pSS itself was associated mination coefficients. with poor QoL. Lendrem et al. found no difference in QoL between those with fibromyalgic symptoms and Conclusion those without [18]. Notwithstanding, our study did not This study demonstrated that the main predictors of investigate other factors, such as subclinical autonomic poor QoL in patients with pSS were pain and fatigue, in- dysfunction and sleep disorders, that could contribute to dependent of disease activity, age, schooling, work dis- pain and fatigue in these patients with pSS without ability, marital status and fibromyalgia. fibromyalgia [45]. The present study demonstrated a contribution of ANA Abbreviations and Anti-Ro/SSA, even if discrete, to worse values in the ANA: Antinuclear antibody; BMI: Body mass index; CCEB: Brazilian Economic SF-36 physical domain. This information differs from the Classification Criteria; ESSDAI: EULAR Sjögren’s Syndrome Disease Activity Index; ESSPRI: EULAR Sjögren’s Syndrome Patient Reported Index; FACIT- findings of other studies in which no correlation was Fatigue: Functional Assessment of Chronic Illness Therapy Fatigue Subscale; found between antibodies and QoL [9, 13, 18]. However, pSS: Primary Sjögren’s syndrome; QoL: Quality of life; RF: Rheumatoid factor; it is well established in the literature that patients with SF-36: Short Form-36 Health Survey; WHOQOL-BREF: World Health Organization Quality of Life Assessment positive autoantibodies evolve to greater glandular dys- function and systemic manifestations [46, 47]. Acknowledgements Although dryness is the main symptom and causes Not applicable. great discomfort in pSS patients, it was not a predictor of QoL, as demonstrated in previous studies [11, 35]. A Authors’ contributions review on QoL in pSS mentioned that it is possible this All authors contributed to the conception and design of the study, may reflect an inadequacy of single VAS scales, as is analysis and interpretation of the data. In addition, all authors performed a critical review and read and approved the final version of this often used in such studies, to capture the breadth and manuscript. impact of oral and ocular involvement. That review also showed that non-SS sicca syndrome patients have an im- Funding pairment of QoL similar to that observed in pSS and Not applicable. other chronic diseases such as rheumatoid arthritis, sys- temic lupus erythematosus and fibromyalgia [20]. Availability of data and materials In the comparison between patients and healthy con- The datasets analyzed during the current study are available from the corresponding author on reasonable request. trols, SF-36 and WHOQOL-BREF domains were worse in patients with pSS, showing that the disease had a Declarations negative influence on the different aspects of QoL. Inter- estingly, the environmental domain, which is associated Ethics approval and consent to participate with transportation-related and residential conditions, in All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or pSS was similar to that in healthy controls, probably be- national research committee and with the 1964 Helsinki Declaration cause both groups showed similar socioeconomic levels. and its later amendments or comparable ethical standards. Informed Other relevant information included the lower number consent was obtained from all individual participants included in the study. of employed individuals and the greater amount of sick leave among pSS patients compared to healthy controls. Consent for publication Patients with pSS also generate a higher cost to the Not applicable. health system, since they use more medical services, have higher hospitalization rates and use more medica- Competing interests tions [11, 20]. These data demonstrate how much the The authors declare that they have no competing interests. disease interferes not only emotionally and physically Author details but also socially and individually, affecting employers Department of Clinical Medicine, Cassiano Antonio Moraes University and the government, increasing social security costs and Hospital / EBSERH, Federal University of Espírito Santo (Ufes), Av. Marechal reducing the life expectancy of the worker. Campos, 1468, Maruípe, Vitória, ES CEP: 29075-910, Brazil. Brazilian Society of Rheumatology, São Paulo, Brazil. Department of Integrated Health The study has limitations. Medications used by pa- Education, Federal University of Espírito Santo (Ufes), Av. Marechal Campos, tients and other comorbidities were not collected. These 4 1468, Maruípe, Vitória, ES CEP: 29075-910, Brazil. Department of Clinical data could have enriched the analysis, as some medica- Medicine, School of Sciences of Santa Casa de Misericórdia de Vitória (Emescam), Av. Nossa Senhora da Penha 2190, Vitória, ES 29045-925, Brazil. tions can yield adverse effects and other diseases may Federal University of Espírito Santo (Ufes), Av. Marechal Campos, 1468, have symptoms with negative impacts on QoL. Ques- 6 Maruípe, Vitória, ES CEP: 29075-910, Brazil. Brazilian Sjögren Syndrome tionnaires about emotional aspects such as depression Commission, São Paulo, Brazil. Dias et al. 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Pain and fatigue are predictors of quality of life in primary Sjögren’s syndrome

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Abstract

Background: Few studies have evaluated the relation of quality of life (QoL) with symptoms and disease activity in primary Sjögren’s syndrome (pSS). There is also scant information on the predictors of QoL in this population. The aim of this study was to assess QoL in patients with pSS and to investigate their possible predictors. Methods: In a cross-sectional study, 77 patients with pSS were evaluated using the following questionnaires: Functional Assessment of Chronic Illness Therapy Fatigue Subscale (FACIT-Fatigue), EULAR Sjögren’s Syndrome Patient Reported Index (ESSPRI), EULAR Sjögren’s Syndrome Disease Activity Index (ESSDAI), Short Form-36 Health Survey (SF-36) and World Health Organization Quality of Life Assessment (WHOQOL-BREF). Seventy-seven healthy controls responded to the SF-36 and WHOQOL-BREF. The Mann-Whitney test, t-test, Pearson and Spearman correlation, and multiple regression analysis were used in the statistical analysis. Results: Patients with pSS and healthy controls were matched by gender and age. The mean scores for the ESSDAI, ESSPRI and FACIT-Fatigue were 3.34 ± 4.61, 6.58 ± 2.29 and 26.17 ± 11.02, respectively. Patients had a lower employment rate (36.4% versus 62.3%, p < 0.01) and higher work disability (10.4% versus 1.3%, p < 0.01). SF-36 and WHOQOL-BREF values were lower in patients with pSS (p < 0.001), except in the WHOQOL-BREF environment domain. Pain (ESSPRI), fatigue (FACIT-Fatigue), antinuclear antibody (ANA), anti-Ro-SSA and economic class (Brazilian Economic Classification Criteria - CCEB) were independent predictors of QoL. Conclusions: The main predictors of poor QoL in patients with pSS were pain and fatigue, and these symptoms had an impact regardless of disease activity, age, schooling, marital status, work disability and fibromyalgia. Keywords: Sjögren’s syndrome, Quality of life, Pain, Fatigue Introduction production of pathogenic autoantibodies [1]. Primary Primary Sjögren syndrome (pSS) is an autoimmune, Sjögren syndrome affects mainly Caucasian women chronic and systemic disease that causes an inflammatory in the 4th to 5th decade of life and presents a broad lymphocyte infiltrate with dysfunction of the salivary and clinical spectrum, with extraglandular manifestations lacrimal glands, leading to xerostomia and xerophthalmia. occurring in more than two-thirds of cases, the most Epigenetic mechanisms such as DNA demethylation in epi- common being arthralgia or arthritis, Raynaud’s thelial cells and altered expression of microRNAs in salivary phenomenon, skin vasculitis, interstitial pneumonitis glands act on genetically susceptible patients, leading to the and pulmonary fibrosis, peripheral neuropathy, and tubulointerstitial and glomerular nephritis [2–4]. Fatigue, a physical or mental feeling of tiredness, also * Correspondence: val.valim@gmail.com affects approximately 70% of these patients and is Department of Clinical Medicine, Cassiano Antonio Moraes University Hospital / EBSERH, Federal University of Espírito Santo (Ufes), Av. Marechal strongly associated with psychosocial factors, occupa- Campos, 1468, Maruípe, Vitória, ES CEP: 29075-910, Brazil tional dysfunction and a greater number of medical visits Brazilian Society of Rheumatology, São Paulo, Brazil but not with sicca severity or laboratory features [5, 6]. Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Dias et al. Advances in Rheumatology (2021) 61:28 Page 2 of 9 In pSS, pain can be explained by different reasons, such circulation areas of the hospital, as well as donors from as arthritis, pain amplification, and neuropathy. Arthritis the blood bank. The exclusion criteria were having auto- is usually symmetrical, predominantly in peripheral and immune rheumatic disease at < 18 years of age and any small joints, and may precede or appear simultaneously other comorbidity. All patients signed the ICF. The Re- with sicca symptoms. Small-fiber neuropathy is the most search Ethics Committee (REC) of HUCAM, protocol common cause of neuropathic pain and is characterized number 178.520, approved the project on January 30, by distal paraesthesias, allodynia, and burning and itch- 2013. ing sensations. Half of the pSS patients present wide- Demographic data such as age, gender, self-reported spread pain, and combined with fatigue and sleep color, level of schooling, income by the Brazilian Eco- disorders, the diagnosis of associated fibromyalgia may nomic Classification Criteria (CCEB) [24], labor status, be considered [7]. work disability (sick leave or early retirement), as well as PSS patients have low quality of life (QoL) in the phys- clinical data such as diagnosis of fibromyalgia (American ical, emotional and social dimensions evaluated by dif- College of Rheumatology - ACR 1990 or ACR 2010) [25, ferent instruments, such as the Short Form-36 Health 26], salivary gland biopsy, presence of antinuclear anti- Survey (SF-36), the World Health Organization Quality bodies (ANA), rheumatoid factor (RF), anti-SSA/Ro and of Life – BREF (WHOQOL-BREF) and the EuroQol 5- anti-SSB/La were collected from medical records and dimensions (EQ-5D) [8–20]. There is also an increase in physician interview. health expenditures, both individual and social, and a Minor salivary gland biopsies were performed and ana- higher frequency of work withdrawal in this population. lyzed by rheumatologists and pathologists with experience QoL can be influenced by several factors, such as age, in pSS and were considered positive when the histopath- schooling and socioeconomic level [6, 9, 11, 12, 21]. ology showed one or more lymphocytic infiltrates with Considering the aspects related to the disease itself, more than 50 mononuclear cells in an area of 4 mm [24]. pain, fatigue and dryness are associated with worse QoL The anti-SSA/Ro and anti-SSB/La laboratory tests were [11–13, 16, 17, 19, 22]. Comorbidities such as depres- performed by the hemagglutination technique, while ANA sion, anxiety, and fibromyalgia are also negatively corre- was performed by indirect immunofluorescence and RF lated [11, 18]. The association with immunological and by the latex test. biological variables is controversial or weak. Hypergam- To evaluate the activity of the disease, two physicians maglobulinemia, the presence of anti-SSA/Ro, anti-SSB/ experienced in pSS applied the ESSDAI. It has 12 La antibodies, antinuclear antibody (ANA) or rheuma- domains of systemic evaluation (constitutional, lymph- toid factor (RF), cytopenias, high cytokine levels or adenopathy, glandular, articular, cutaneous, respiratory, salivary gland biopsy do not correlate with worse QoL, renal, muscular, peripheral and central nervous system, while extraglandular manifestations, mainly articular and hematological and biological). The domains have differ- pulmonary, are poorly correlated [13]. Few studies have ent weights in the final score, 0 to 123, according to the evaluated the relationship of QoL with symptoms and level of activity [27, 28]. Values lower than 5 are consid- disease activity as measured by EULAR Sjögren’s Syn- ered to indicate low disease activity; values from 5 to 13, drome Patient Reported Index (ESSPRI) and EULAR moderate activity; and values greater than or equal to Sjögren’s Syndrome Disease Activity Index (ESSDAI) 14, high activity [29]. [17, 19]. There is also little information on the predic- Symptoms and QoL were assessed using self-administered tors of QoL in this population [11, 17, 19]. questionnaires, and a trained professional was available to The objective of this study was to evaluate whether assist participants when needed. PSS patients answered the disease activity or symptoms such as pain, dryness, and ESSPRI, which measures three symptoms related to the dis- fatigue are predictors of QoL regardless of other clinical- ease: dryness, pain and fatigue. Each domain ranges from 0 epidemiological features in patients with pSS. to 10, and the result is the average of the three domains [30]. Values less than 5 are considered acceptable [29]. Methods Fatigue in pSS patients was evaluated through the A cross-sectional study was conducted from January to Functional Assessment of Chronic Illness Therapy - July 2013 at the University Hospital of Federal University fatigue (FACIT-fatigue). The FACIT system originally of Espírito Santo (HUCAM), in Vitória, Brazil. developed to evaluate QoL in cancer patients has been PSS patients who met the American – European clas- widely used in several chronic diseases. Its score ranges sification criteria (AECG) [23] and signed the informed from 0 to 52, and its value is inversely proportional to consent form (ICF) were included. Secondary Sjögren’s the degree of fatigue [31]. syndrome patients were excluded. The SF-36 and WHOQOL-BREF questionnaires were The control group consisted of healthy individuals used to assess QoL in pSS patients and healthy controls. matched by gender and age who were in external The SF-36 is an easy-to-administer instrument Dias et al. Advances in Rheumatology (2021) 61:28 Page 3 of 9 consisting of 36 items divided into 8 domains: physical Table 1 Demographic and clinical data in pSS patients and healthy controls functioning, physical role functioning, bodily pain, gen- eral health, vitality, social functioning, emotional role pSS (n = 77) Controls (n = 77) functioning and mental health. These can be grouped Age, mean, years 52.34 (9.03) 52.27 (8.91) into two components that summarize the dimensions: Ethnicity physical (PCS) and mental (MCS) component summar- Black (%) 11.7 13 ies. Its final score ranges from 0 to 100, and the higher Brown (%) 59.7 49.4 the score, the better the overall health condition [32]. White (%) 24.7 37.7 Developed by the World Health Organization (WHO), Indigenous (%) 2.6 0 the WHOQOL-BREF is an abbreviated version of the WHOQOL-100. It is composed of 26 questions. The Education first two questions are general QoL issues, and the < 8 years (%) 50.7 57.2 remaining 24 facets will form four domains: physical, ≥ 8 years (%) 48.1 40.3 psychological, social relations and environment. The Never studied (%) 1.2 2.5 total score ranges from zero to 100, and the higher its Marital status value, the better the QoL [33, 34]. Married (%) 66.2 63.6 The chi-square, Fisher and likelihood ratio association tests were used for qualitative variables among patients Not married (%) 14.3 13 with pSS and healthy controls. The Kolmogorov-Smirnov Divorced/widow (%) 19.5 23.4 test was used to evaluate the normal distribution of the CCEB data. For quantitative variables, the Mann-Whitney test A (%) 1.3 0 was used when there was a breakdown of normality, and B (%) 23.4 26.6 with normal data, the t test was used. Pearson or C (%) 52 49.3 Spearman tests were used in the correlations. To identify independent predictors for quality of life, stepwise linear D (%) 18.2 24 regression analysis was performed. The variables consid- E (%) 0 0 ered in the analysis were age, weight, body mass index *Employment rate (%) 36.4 62.3 (BMI), smoking, alcoholism, marital status, schooling, Work disability (%)* 10.4 1.3 fibromyalgia, CCEB, work disability (sick leave or early re- Positive salivary biopsy 90.5 tirement), ESSDAI, ESSPRI, FACIT-Fatigue, salivary gland (focus score ≥ 1) (%) biopsy, ANA, anti-SSA/Ro, anti-SSB/La and RF. Variables Anti-SSA/Ro (%) 33.3 with a statistical significance level of 10% were included in Anti-SSB/La (%) 24 the multiple regression analysis. Statistical significance was set at a p value of ≤0.05. The Statistical Package for Antinuclear antibody (%) 68.9 the Social Sciences (SPSS), version 20.0, Armonk, New Rheumatoid factor (%) 29.2 York (NY), 2011 software was used. Fibromyalgia (%) 42.9 FACIT-Fatigue, mean, SD 26.17 (11.02) Results ESSPRI, mean, SD 6.58 (2.29) Of 127 pSS outpatients, 27 were excluded because they Fatigue, mean, SD 6.38 (2.57) did not meet the AECG, and 33 were not willing to participate. Dryness, mean, SD 6.53 (2.78) Seventy-seven pSS patients and 77 healthy women Pain, mean, SD 6.84 (3.12) were included, aged 27 to 67 years. Groups were similar Extra glandular manifestations (%) 49.4 in age, ethnicity, schooling, marital status and economic ESSDAI, mean SD 3.34 (4.61) classification. Patients had a lower employment rate pSS Primary Sjögren Syndrome, CCEB Brazilian Economic Classification Criteria, (36.4% versus 62.3%, p < 0.01) and higher work disability FACIT Fatigue – Functional Assessment of Chronic Illness Therapy-Fatigue, SD (10.4% versus 1.3%, p < 0.01). Moreover, the patients had standard deviation, ESSPRI EULAR Sjögren’s syndrome patient reported index *p < 0.01 a low disease activity (ESSDAI 3.34 ± 4.61) and a low fre- quency of autoantibodies, characterizing a sample with mild disease. Biological and articular domains were the most frequently affected. In contrast, the patients pre- The QoL measured by SF-36 and WHOQOL-BREF was sented a high level of symptoms (ESSPRI 6.58 ± 2.29). worse in patients with pSS than in healthy controls, except Among patients with pSS, the percentage of fibromyalgia for the environment domain tested by WHOQOL-BREF, was 42.9% (Table 1). which was similar for both groups (Table 2). Dias et al. Advances in Rheumatology (2021) 61:28 Page 4 of 9 Table 2 Comparison of quality of life between pSS patients and Table 3 Comparison of quality of life between patients with healthy controls acceptable and non-acceptable ESSPRI SF-36 pSS (n = 77) Controls (n = 77) ESSPRI *Physical functioning 37.3 ± 24.2 80.5 ± 20.8 Acceptable Non-acceptable SF36 *Physical role functioning 27.6 ± 35.9 73.4 ± 37.2 *Physical functioning 63.44 ± 29.08 30.83 ± 17.54 *Bodily pain 36.7 ± 22.2 69.5 ± 21.4 Physical role functioning 35.94 ± 43.75 25.00 ± 33.19 *General health 43.2 ± 17.9 69.5 ± 20.0 *Bodily pain 55.06 ± 25.69 31.80 ± 18.56 *Vitality 37.2 ± 20.6 64.8 ± 20.9 *General health 53.75 ± 19.21 40.57 ± 16.66 *Social functioning 48.3 ± 26.9 74.8 ± 23.1 Vitality 47.19 ± 34.92 34.92 ± 18.31 *Emotional role functioning 31.1 ± 38.6 69.3 ± 40.0 Social functioning 54.66 ± 47.02 47.02 ± 27.27 *Mental health 46.2 ± 22.3 67.8 ± 23.0 **Emotional role functioning 52.08 ± 25.00 25.00 ± 34.51 *PCS 33.1 ± 9.1 48.9 ± 8.5 **Mental health 56.00 ± 24.57 43.87 ± 21.05 *MCS 37.2 ± 11.4 46.8 ± 12.3 *PCS 40.21 ± 10.88 31.28 ± 7.62 WHOQOL-BREF MCS 40.83 ± 13.14 36.31 ± 10.84 *Physical health 41.6 ± 16.8 67.7 ± 16.8 WHOQOL-BREF *Psychological health 53.4 ± 18.8 63.9 ± 15.9 *Physical health 56.70 ± 19.25 37.54 ± 13.76 *Social relations 55.5 ± 22.0 65.4 ± 18.2 **Psychological health 63.02 ± 16.66 50.90 ± 18.75 Environment 49.1 ± 12.7 53.0 ± 16.5 SF-36 Short Form 36 Health Survey, pSS primary Sjögren’s Syndrome, PSC *Social relations 71.35 ± 14.58 51.11 ± 21.94 Physical Component Summary, MCS Mental Component Summary, WHOQOL- **Environment 54.88 ± 9.20 47.53 ± 13.23 BREF World Health Organization Quality of Life Assessment *p < 0.01 ESSPRI EULAR Sjögren’s syndrome patient reported index, SF-36 Short Form-36 Health Survey, PCS Physical Component Summary, MCS Mental Component Summary, WHOQOL-BREF World Health Organization quality of life – BREF *p < 0.01; **p < 0.05 In the pSS group, patients with a nonacceptable ESSP RI (≥ 5) had all WHOQOL-BREF and most SF-36 do- mains worse than patients with an acceptable ESSPRI (Table 3). Patients with pSS and fibromyalgia had worse Table 4 Comparison of QoL between pSS patients with QoL values in bodily pain (SF-36) and physical health fibromyalgia (WHOQOL-BREF) (Table 4). Fibromyalgia There was a moderate-to-strong correlation of FACIT- Yes No Fatigue with all domains of QoL questionnaires. The SF-36 Physical functioning 30.9 ± 18.9 42.6 ± 26.5 ESSPRI also correlated with all QoL domains. The ESS- DAI showed only a weak correlation with the emotional Physical role functioning 22.0 ± 30.5 32.4 ± 39.1 role functioning domain of the SF-36 and did not correl- *Bodily pain 25 ± 15.3 45.6 ± 22.4 ate with fatigue indexes (FACIT-Fatigue) and ESSPRI General health 37.9 ± 17.2 47.4 ± 17.4 (Table 5). Vitality 30.9 ± 17.4 42.2 ± 21.4 In the regression analysis, pain (ESSPRI), fatigue (FACI Social functioning 42.3 ± 25.2 53.7 ± 27.7 T-Fatigue), antinuclear antibody (ANA), anti-Ro-SSA and Emotional role functionig 28.3 ± 38.3 34.1 ± 39.0 economic class (Brazilian Economic Classification Criteria - CCEB) were independent predictors of QoL. The symp- Mental health 41.7 ± 22.7 49.6 ± 21.4 toms measured by FACIT-Fatigue and ESSPRI pain were PCS 29.7 ± 6.5 35.8 ± 9.8 the main predictors of poor QoL, regardless of age, marital MCS 35.7 ± 11.6 38.6 ± 11.1 status, schooling, work disability, disease activity and WHOQOL-BREF *Physical health 35.5 ± 15.3 46.2 ± 16.5 fibromyalgia. In the PCS of the SF-36, the predictors for Social relations 51.0 ± 23.0 58.9 ± 20.9 the worst values were pain, fatigue, and the presence of Environment 45.6 ± 11.4 51.8 ± 13.1 ANA and anti-SSA/Ro autoantibodies. Fatigue was the only predictor in the MCS of the SF-36 and psychological Psychological health 48.7 ± 19.3 56.8 ± 17.8 health domain of the WHOQOL-BREF. Pain interfered QoL Quality of Life, pSS primary Sjögren’s Syndrome, SF-36 Short Form 36 Health Survey, PSC Physical Component Summary, MCS Mental Component with the PCS of the SF-36, physical health, social relations Summary, WHOQOL-BREF World Health Organization Quality of and environmental domains of the WHOQOL-BREF Life Assessment (Table 6). *p < 0.01 Dias et al. Advances in Rheumatology (2021) 61:28 Page 5 of 9 Table 5 Correlation of quality of life, disease activity, symptoms and fatigue ESSDAI ESSPRI dryness ESSPRI fatigue ESSPRI pain ESSPRI Total FACIT-Fatigue SF36 Physical functioning 0.04 −0.44** −0.29* − 0.55** − 0.56** 0.53** Physical role functioning 0.01 −0.17 −0.08 − 0.23* −0.24* 0.35** Bodily pain 0.03 −0.33** −0.23* − 0.59** −0.53** 0.56** General health −0.08 −0.27* − 0.17 −0.34** − 0.34** 0.56** Vitality −0.04 −0.23* − 0.26* −0.36** − 0.39** 0.56** Social functioning −0.01 −0.33** − 0.18 −0.21 − 0.29* 0.45** Emotional role functioning −0.24** −0.31** − 0.11 −0.23 − 0.29* 0.48** Mental health 0.04 −0.21 −0.23* − 0.31** −0.28* 0.46** PCS 0.06 −0.35** −0.21 − 0.53** −0.5** 0.46** MCS −0.14 −0.2 − 0.17 −0.12 − 0.24* 0.48** Whoqol Bref Physical health −0.09 −0.34** − 0.19 −0.43** − 0.50** 0.68** Psychological health −0.08 −0.32** − 0.19 −0.36** − 0.38** 0.56** Social relations −0.03 −0.17 − 0.2 −0.34** − 0.33** 0.37** Environment −0.01 −0.19 − 0.18 −0.49** − 0.34** 0.32** ESSDAI −0.11 −0.01 − 0.04 −0.08 − 0.06 ESSDAI EULAR Sjögren’s syndrome disease activity index, ESSPRI EULAR Sjögren’s syndrome patient reported index, FACIT Fatigue – Functional Assessment of Chronic Illness Therapy-Fatigue, SF-36 Short Form-36 Health Survey, PCS Physical Component Summary, MCS Mental Component Summary, WHOQOL-BREF World Health Organization quality of life – BREF *p < 0.01; ‘**p < 0.05 Discussion Kingdom (UK) [18] and in 104 Korean patients [17]. In Here, PSS patients were found to have lower QoL scores contrast, Omma et al. found that the ESSDAI was an in- than healthy controls, corroborating previous studies in dependent determinant of all SF-36 domains, with the other countries [11–13, 15–19, 22]. The relevance of the exception of the vitality domain, in 105 patients from present data was to demonstrate that symptoms, but not Turkey, most of whom had low to moderate levels of disease activity, were the main predictors of low QoL. disease activity [36]. As in Liu et al.’s study [37], our re- Few studies have performed multivariate analyses to sults showed that pain and fatigue were independently identify predictors of QoL in pSS. Cornec et al. corrobo- associated with a low physical component summary rated the results of our study, showing that disease activ- (PCS) of the SF-36 and that fatigue was associated with ity is not associated with greater QoL impairments in a low mental component summary (MCS) of the SF-36. 120 French patients with moderate-to-high levels of sys- In the Cornec et al. study, only pain was associated [35]. temic activity, despite the low level of disease activity in Omma et al. demonstrated that the ESSPRI was an inde- our patients [35]. Disease activity (ESSDAI) was also not pendent determinant of bodily pain, general health, a predictor of QoL in 639 pSS patients from United mental health and PCS of the SF-36, while fatigue was Table 6 Predictors of quality of life SF-36 WHOQOL-BREF PCS MCS Physical health Psychological health Social relations Environment 2 2 2 2 2 2 R : 0.56 R : 0.22 R : 0.52 R : 0.36 R : 0.23 R : 0.30 ß p-value ß p-value ß p-value ß p-value ß p-value ß p-value ESSPRI-pain −1.16 0.00 −1.48 0.00 −1.53 0.06 −1.63 0.00 FACIT-Fatigue 0.31 0.00 0.51 0.00 0.88 0.00 1.00 0.00 0.48 0.04 ANA −4.64 0.01 Anti-SSA/Ro −4.09 0.01 CCEB − 4.91 0.05 −3.9 0.01 SF-36 Short Form-36 Health Survey, WHOQOL-BREF World Health Organization quality of life – BREF, PCS Physical Component Summary, MCS Mental Component Summary, ANA Antinuclear Antibody, CCEB Brazilian Economic Classification Criteria Dias et al. Advances in Rheumatology (2021) 61:28 Page 6 of 9 significantly correlated with four or more domains of severity in pSS [40]. A proteomic study of cerebrospinal the SF-36 [36]. fluid showed that some proteins that are increased in Results showed a correlation between the ESSDAI only pSS have a role in the downregulation of inflammation and the emotional aspects domain of the SF-36, and yet and in the cellular stress defense (hemopexin, pigment this correlation was weak, not being confirmed as a pre- epithelium-derived factor, clusterin, osteopontin, and dictor of QoL in patients with pSS. Sharing a similar re- selenium-binding protein 1). These results suggest that sult, a cohort in the UK using the EQ-5D to assess QoL some fatigue signaling pathways are associated with “cel- demonstrated a weak correlation with the ESSDAI [19]. lular protection and defense” and are not directly related Yacoub et al. used the degree of activity in salivary gland to proinflammatory factors [41]. Nonetheless, the evi- biopsy, immunological status and severity of systemic in- dence for an association between fatigue and disease ac- volvement as a way of assessing disease activity, and they tivity – or any other inflammatory markers – remains found no correlation with QoL or fatigue [13]. It is not controversial. clear why there is a weak association between disease ac- In fact, the pathogenesis of fatigue in pSS is unknown tivity (ESSDAI) and QoL. One possible answer could be but seems to be associated with a lower aerobic capacity the wide range of ESSDAI scores (0–123) in samples and lower physical activity levels, sleep disturbances, with low mean activity. In addition, ESSDAI is an index autonomic dysfunction, depression, psychological pro- that does not assess established damage, only current ac- files, and fibromyalgia [38]. It is noteworthy that, in the tivity; thus, perhaps the patient’s perception about the multiple regression models, fatigue measured by FACIT- QoL is not modified at that moment, but when there is Fatigue was the only predictor of the MCS of SF-36 and an established organic dysfunction. Other studies correl- the psychological component of WHOQOL-BREF. ating injury rates with disease activity and QoL could These data indicate that this symptom impacts not only better elucidate the issue. the physical aspects but also the mental health of these QoL was worse in patients with higher nonacceptable individuals. Other studies have pointed to depression as ESSPRI, and it was not associated with ESSDAI, corrob- an important determinant of poor QoL along with fa- orating that symptoms (fatigue, pain and dryness) im- tigue in these patients [11, 17, 18], which could partially pact QoL more than disease activity. explain the low values of the determination coefficients In pSS, QoL has been found to be associated with fa- in the mental domain of the SF-36, as well as in the psy- tigue, pain/articular involvement, ocular and oral in- chological, social relations and environmental domains volvement, pruritus, sexual dysfunction, impaired sleep, of the WHOQOL-BREF. However, we did not evaluate pulmonary manifestations, psychological dysfunction psychiatric disorders, such as depression or anxiety, and impaired physical function [20]. On the other hand, which is a limitation of this study. Interestingly, aerobic delayed diagnosis, protracted course of the disease, and exercise has been found to improve fatigue, but not QoL the lack of social support are also causes of the decline and depression [42], and resistance exercise has been in the quality of life in these patients [37]. found to improve QoL [43]. Clearly, many efforts still Fatigue is considered a hallmark of pSS [5]. In the need to be made to elucidate the pathogenesis of fatigue, present study, fatigue (FACIT-fatigue) was strongly asso- as well as to identify pharmacological and nonpharmaco- ciated with all dimensions of QoL and was an independ- logical therapies to treat fatigue and improve the QoL in ent risk factor for the physical and mental aspects of pSS. QoL in both instruments, SF-36 and WHOQOL-BREF. Pain was a determinant for lower QoL in the physical, In contrast, there was no association between fatigue social relations and environmental domains but not for and disease activity measured by the ESSDAI. Taken to- mental aspects. A large proportion of patients with pSS gether, the results suggest that fatigue is itself associated have noninflammatory musculoskeletal pain without the with pSS but may not be explained by disease activity. laboratory or clinical abnormalities of arthritis. Among Recent evidence has shown weak or no association patients with pSS, cases of pain amplification syndrome with inflammatory biomarkers such as interleukin (IL)- are associated with a benign pole of the disease, with a 1b, IL-2, IL-6, IL-10 and tumor necrosis factor alpha low frequency of autoantibodies and extraglandular (TNF-α). In the same direction, immunosuppressors and manifestations [44]. biological therapy failed to treat fatigue in pSS [38]. The prevalence of fibromyalgia in pSS varies from 12 However, Howard et al. showed that lower levels of the to 55% [7]. In our study, the prevalence was 42.9%. This pro-inflammatory cytokines inducible protein (IP)-10 large range can certainly be explained by the various cri- and interferon-gamma (IFN-γ), together with pain and teria to diagnose fibromyalgia as well as pSS that have depression, were the most important predictors of fa- been applied over time. Indeed, pain and fatigue are tigue [39], and Davies et al. demonstrated that TNF-α common symptoms in both fibromyalgia and pSS, and and LT-α have an inverse relationship with fatigue the association of the two can be a misleading factor. Dias et al. Advances in Rheumatology (2021) 61:28 Page 7 of 9 However, in the present study, fatigue and pain were the and anxiety were also not applied, and these data could main predictors of poor QoL, regardless of the diagnosis have improved the values of the mental domain deter- of fibromyalgia, indicating that pSS itself was associated mination coefficients. with poor QoL. Lendrem et al. found no difference in QoL between those with fibromyalgic symptoms and Conclusion those without [18]. Notwithstanding, our study did not This study demonstrated that the main predictors of investigate other factors, such as subclinical autonomic poor QoL in patients with pSS were pain and fatigue, in- dysfunction and sleep disorders, that could contribute to dependent of disease activity, age, schooling, work dis- pain and fatigue in these patients with pSS without ability, marital status and fibromyalgia. fibromyalgia [45]. The present study demonstrated a contribution of ANA Abbreviations and Anti-Ro/SSA, even if discrete, to worse values in the ANA: Antinuclear antibody; BMI: Body mass index; CCEB: Brazilian Economic SF-36 physical domain. This information differs from the Classification Criteria; ESSDAI: EULAR Sjögren’s Syndrome Disease Activity Index; ESSPRI: EULAR Sjögren’s Syndrome Patient Reported Index; FACIT- findings of other studies in which no correlation was Fatigue: Functional Assessment of Chronic Illness Therapy Fatigue Subscale; found between antibodies and QoL [9, 13, 18]. However, pSS: Primary Sjögren’s syndrome; QoL: Quality of life; RF: Rheumatoid factor; it is well established in the literature that patients with SF-36: Short Form-36 Health Survey; WHOQOL-BREF: World Health Organization Quality of Life Assessment positive autoantibodies evolve to greater glandular dys- function and systemic manifestations [46, 47]. Acknowledgements Although dryness is the main symptom and causes Not applicable. great discomfort in pSS patients, it was not a predictor of QoL, as demonstrated in previous studies [11, 35]. A Authors’ contributions review on QoL in pSS mentioned that it is possible this All authors contributed to the conception and design of the study, may reflect an inadequacy of single VAS scales, as is analysis and interpretation of the data. In addition, all authors performed a critical review and read and approved the final version of this often used in such studies, to capture the breadth and manuscript. impact of oral and ocular involvement. That review also showed that non-SS sicca syndrome patients have an im- Funding pairment of QoL similar to that observed in pSS and Not applicable. other chronic diseases such as rheumatoid arthritis, sys- temic lupus erythematosus and fibromyalgia [20]. Availability of data and materials In the comparison between patients and healthy con- The datasets analyzed during the current study are available from the corresponding author on reasonable request. trols, SF-36 and WHOQOL-BREF domains were worse in patients with pSS, showing that the disease had a Declarations negative influence on the different aspects of QoL. Inter- estingly, the environmental domain, which is associated Ethics approval and consent to participate with transportation-related and residential conditions, in All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or pSS was similar to that in healthy controls, probably be- national research committee and with the 1964 Helsinki Declaration cause both groups showed similar socioeconomic levels. and its later amendments or comparable ethical standards. Informed Other relevant information included the lower number consent was obtained from all individual participants included in the study. of employed individuals and the greater amount of sick leave among pSS patients compared to healthy controls. Consent for publication Patients with pSS also generate a higher cost to the Not applicable. health system, since they use more medical services, have higher hospitalization rates and use more medica- Competing interests tions [11, 20]. These data demonstrate how much the The authors declare that they have no competing interests. disease interferes not only emotionally and physically Author details but also socially and individually, affecting employers Department of Clinical Medicine, Cassiano Antonio Moraes University and the government, increasing social security costs and Hospital / EBSERH, Federal University of Espírito Santo (Ufes), Av. Marechal reducing the life expectancy of the worker. Campos, 1468, Maruípe, Vitória, ES CEP: 29075-910, Brazil. Brazilian Society of Rheumatology, São Paulo, Brazil. Department of Integrated Health The study has limitations. Medications used by pa- Education, Federal University of Espírito Santo (Ufes), Av. Marechal Campos, tients and other comorbidities were not collected. These 4 1468, Maruípe, Vitória, ES CEP: 29075-910, Brazil. Department of Clinical data could have enriched the analysis, as some medica- Medicine, School of Sciences of Santa Casa de Misericórdia de Vitória (Emescam), Av. Nossa Senhora da Penha 2190, Vitória, ES 29045-925, Brazil. tions can yield adverse effects and other diseases may Federal University of Espírito Santo (Ufes), Av. Marechal Campos, 1468, have symptoms with negative impacts on QoL. Ques- 6 Maruípe, Vitória, ES CEP: 29075-910, Brazil. Brazilian Sjögren Syndrome tionnaires about emotional aspects such as depression Commission, São Paulo, Brazil. Dias et al. 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