Prevalence, severity, and predictors of fatigue in subjects with primary Sjögren's syndrome




To investigate the relationship of fatigue severity to other clinical features in primary Sjögren's syndrome (SS) and to identify factors contributing to the physical and mental aspects of fatigue.


We identified 94 subjects who met the American-European Consensus Group criteria for the classification of primary SS. Fatigue was assessed with a visual analog scale, the Fatigue Severity Scale (FSS), and the Profile of Fatigue (ProF). Associations with fatigue were compared using multivariate regression.


Abnormal fatigue, defined as an FSS score ≥4, was present in 67% of the subjects. Pain, helplessness, and depression were the strongest predictors of fatigue according to the FSS and the somatic fatigue domain of the ProF (ProF-S), both with and without adjustment for physiologic and serologic characteristics. Depression was associated with higher levels of fatigue; however, the majority of subjects with abnormal fatigue were not depressed. Anti-Ro/SSA–positive subjects were no more likely to report fatigue than seronegative subjects. The regression models explained 62% of the variance in FSS and 78% of the variance in ProF-S scores. Mental fatigue was correlated with depression and helplessness, but the model predicted only 54% of the variance in mental fatigue scores.


Psychosocial variables are determinants of fatigue, but only partially account for it. Although fatigue is associated with depression, depression is not the primary cause of fatigue in primary SS. Investigation of the pathophysiologic correlates of physical and mental aspects of fatigue is needed to guide the development of more effective interventions.


Primary Sjögren's syndrome (SS) is a common systemic autoimmune disorder affecting ∼0.09% of the adult population (1). Based on American-European Consensus Group (AECG) criteria, prevalence among women ranges 0.1–0.6% in US, UK, and Greek cohorts (2). Subjects present with constitutional symptoms, a wide variety of neurologic disorders and systemic involvement, and reports of oral and ocular dryness. Primary SS can lead to vasculitis (3) and is associated with a 40-fold increased risk of lymphoma (4). However, fatigue and pain are the most common extraglandular symptoms (5, 6).

Abnormal fatigue is defined as enduring, generalized tiredness and can be characterized in terms of intensity, duration, and effects upon daily function (7). In population-based studies, ∼20% of healthy adults reported persistent fatigue (8, 9). Among patients with autoimmune disease, the prevalence of fatigue is much higher, in the range of 60–70% (10–12).

Despite the impact that fatigue has on quality of life in rheumatic disorders, there is no consensus regarding the assessment of fatigue. There are very little data comparing different fatigue measures, and the pathogenesis of clinically significantly persistent fatigue is unknown.

In the primary care setting, chronic fatigue is strongly associated with depression. In a general medical practice, 73% of patients presenting with a report of chronic fatigue had a psychiatric diagnosis (13). The relationship of fatigue to depression in primary SS is less clear. Despite the importance of clinically significant fatigue in the majority of patients with primary SS, only a few studies have, to our knowledge, examined the relationship of fatigue to other clinical variables (5, 14–19). The relative contributions of physiological variables and behavioral- and immune-mediated factors to fatigue have not been well characterized. Although previous studies of primary SS have demonstrated an association of fatigue with depression (5), the relationship between fatigue and depression is complex and the effect of illness severity is unclear. A key unresolved issue is whether chronic fatigue experienced by patients with systemic autoimmunity is mediated primarily by a disturbance in immune function or by factors such as sleep disorder and depression, which are associated with fatigue in persons with nonautoimmune disorders.

In order to better understand the determinants of fatigue in primary SS, we concurrently evaluated the differential effects of behavioral, cognitive, and clinical variables contributing to fatigue in primary SS. We used multiple validated measures to assess fatigue, and compared the factors predictive of fatigue using 3 instruments and a visual analog scale (VAS). We hypothesized that depression, pain, and helplessness contribute to, but do not entirely account for, the variance in fatigue severity in subjects with primary SS.



Subjects with sicca symptoms, defined as xerophthalmia (dry eyes) and xerostomia (dry mouth), were recruited from the community and from rheumatology, neurology, and oral medicine clinics at the University of Minnesota. The study was approved by the Institutional Review Board of the University of Minnesota Medical School for studies involving human subjects, and informed consent was obtained from all subjects. All participants were evaluated with a detailed medical history regarding organ manifestations and family background of autoimmune disorders.


Systemic connective tissue disorders other than primary SS were established by history, physical examination, and careful review of medical records according to the American College of Rheumatology (formerly the American Rheumatism Association) criteria (20–22). Uniform application of the AECG criteria for primary SS (23) salivary and ocular function, and minor salivary gland biopsy was performed to differentiate subjects with primary and secondary SS from subjects with sicca symptoms who did not meet the criteria for primary SS. Phlebotomy was performed at the time of the clinic visit. Complete blood count and differential, erythrocyte sedimentation rate (ESR; Westergren method), and serologic tests for antinuclear antibodies (ANA), rheumatoid factor (RF), and anti–double-stranded DNA were performed by the University of Minnesota Medical Center Fairview Diagnostic Laboratories using standard methodologies. Anti-Ro/SSA and anti-La/SSB titers were determined by enzyme-linked immunosorbent assay (Immunovision, Springdale, AR) following the manufacturer's instructions.

Subjects provided information concerning the impact of fatigue on daily life, and on the presence of depression, pain, and helplessness. Global descriptions of fatigue and pain were obtained by asking the patient to indicate the degree of symptom severity on a 10-cm VAS (range 0–100). For the fatigue assessment we used a double-anchored VAS labeled at one end with “fatigue is no problem” and at the other with “fatigue is a major problem.” The specific anchors for the pain VAS were “no pain” and “pain as bad as it could be.”

Fatigue was also evaluated with validated self-report questionnaires: the Fatigue Severity Scale (FSS) and the Profile of Fatigue (ProF). The FSS is a 9-item instrument that focuses on the behavioral consequences of fatigue (12). Individuals rate the extent to which they agree with each statement regarding the impact of fatigue on activities of daily living according to a 7-point Likert scale where 1 = strongly disagree and 7 = strongly agree. The score range is 1–7. The composite score is the average of the 9 item scores, where higher scores indicate more severe fatigue. The FSS has been shown to have high sensitivity, reliability, and internal consistency in the assessment of fatigue (12), and has been widely utilized to assess fatigue severity in neurologic and autoimmune disorders including systemic lupus erythematosus (SLE), multiple sclerosis (MS), and chronic hepatitis C virus (HCV) infection (24–26). We used a cutoff score ≥4 to define fatigue cases based on data in the literature demonstrating that an FSS score ≥4 reliably differentiates subjects with fatigue from control subjects (12, 25, 27).

The ProF is a multidimensional instrument that was developed to characterize the pattern of fatigue associated with primary SS (28). The ProF consists of 16 items used to evaluate 2 domains of fatigue: somatic fatigue (the ProF-S; 12 items divided into 4 facets) and mental fatigue (the ProF-M; 4 items divided into 2 facets.). Respondents are asked to rate how they felt in the past 2 weeks on a scale of 0–7 where 0 = no problem at all and 7 = as bad as imaginable. The facet score is obtained by adding the item scores within the facet and dividing the sum by the number of items within the facet. The domain scores are obtained in the same way, i.e., by adding the facet scores within the domain and dividing the sum by the number of facets within the domain (28). ProF domain scores range 0–7, with higher scores indicating worse functioning. A cutoff score of >2 for both the ProF-S and the ProF-M was used to distinguish subjects with primary SS. The ProF has been validated in 2 studies of primary SS (28, 29). The individual domains of somatic and mental fatigue obtained with the ProF may vary independently of each other and a composite score is not provided (28).

The presence of depression was assessed with the Center for Epidemiologic Studies Depression Scale (CES-D), a 20-item questionnaire designed to evaluate depression (30). The score of each item ranges from 0 to 3. The overall score is the sum of all the items. Scores ≥16 correlate highly with the presence of depression on structured psychometric interviews.

Learned helplessness is a concept that refers to a psychological state in which individuals expect that nothing they do or can do will modify their symptoms. We used the 5-item helplessness subscale derived from the original 15-item Rheumatology Attitudes Index (RAI). The brief RAI has been validated in multiple studies of rheumatoid arthritis (RA) and SLE, and the reliability of the 5-item helplessness subscale has been tested in several ethnic groups (31, 32). Respondents were asked to rate their degree of agreement with each item using a 5-point Likert scale ranging from strongly disagree to strongly agree. Higher scores reflect greater degrees of helplessness. Possible scores range from 5 to 25.

Statistical analysis.

Continuous demographic variables and symptom characteristics were summarized by means and SDs for normally distributed variables, and skewed variables were transformed to the log scale. For log variables, the geometric mean was reported with the interval from the 33rd to 66th percentile, corresponding to the percentiles enclosed by mean ± SDs for a normal distribution. Categorical variables were summarized as number and percentage. Fatigued and nonfatigued subgroups were compared by t-tests for continuous variables and chi-square tests for categorical variables. We estimated 95% confidence intervals (95% CIs) for Pearson's correlation coefficients from 1,000 bootstrap samples with the bias-corrected accelerated estimator (33). We compared the roles of 3 questionnaire instruments in predicting 4 different fatigue ratings using linear regression models, with and without adjustment for demographic and symptom characteristics. All response and predictor variables were standardized to where the mean = 0 and the SD = 1. For log variables, the rescaling was done after taking logs. These linear transformations do not affect inferences (P values) and allow comparison of effect size and direction. All computations were performed using SAS software, version 9.1 (SAS Institute, Cary, NC).


Subject characteristics.

Ninety-four subjects met the AECG criteria (23) for the diagnosis of primary SS and all were included in the data analysis. The demographic variables, serologic status, and percentage of subjects in the cohort with positive histopathology on minor salivary gland biopsy are presented in Table 1. Minor salivary gland biopsies were performed on 69 (73%) subjects. Subjects were 98% white, predominantly of Northern European descent, with a mean age of 58 years (range 29–79 years) at examination. Average disease duration from the time of diagnosis was 7.9 years, and average age at diagnosis was 49.5 years.

Table 1. Demographic and symptom characteristics of the study participants*
 All (n = 94)Not fatigued (FSS <4) (n = 31)Fatigued (FSS ≥4) (n = 63)P
  • *

    Values for the highly skewed variables are the geometric mean (33rd–66th percentile); other values are as indicated. FSS = Fatigue Severity Scale; ProF-M = Profile of Fatigue mental domain; ProF-S = Profile of Fatigue somatic domain; VAS = visual analog scale; CES-D = Center for Epidemiologic Studies Depression Scale; RAI = Rheumatology Attitudes Index (helplessness); ANA = antinuclear antibody; RF = rheumatoid factor; ESR = erythrocyte sedimentation rate; WUSF = Whole Unstimulated Salivary Flow.

  • Comparison between subgroups with FSS <4 versus FSS ≥4.

  • Of 87 women with known status.

  • §

    Of 69 subjects biopsied.

  • Average of the right and left eye.

Women, n (%)90 (96)29 (94)61 (97)0.46
Race, n (%)    
 White92 (98)30 (97)62 (98) 
 African-American1 (1)01 (2) 
 Asian1 (1)1 (3)00.28
Education, n (%)    
 High school only21 (22)7 (23)14 (22) 
 College or postgraduate73 (78)24 (77)49 (78)0.97
Age at examination, mean ± SD years58 ± 1257 ± 1458 ± 110.90
Postmenopause, n (%)65 (74)18 (67)47 (78)0.25
Scored as fatigued, n (%)    
 FSS ≥463 (67)   
 ProF-M >245 (48)6 (19)39 (62)0.0001
 ProF-S >290 (96)9 (29)56 (89)0.0001
FSS score, mean ± SD4.6 ± 1.62.5 ± 0.75.4 ± 0.9
ProF-M score, mean ± SD2.8 ± 1.80.9 ± 1.63.3 ± 1.70.0003
ProF-S score, mean ± SD3.5 ± 1.82.2 ± 1.64.1 ± 1.50.0001
Fatigue VAS score, mean ± SD mm56 ± 3329 ± 3268 ± 250.0001
Pain VAS score, mean ± SD mm39 ± 3020 ± 2648 ± 280.0001
CES-D, mean ± SD13.2 ± 108.4 ± 915.5 ± 90.0006
Depressed (CES-D ≥16), n (%)30 (32)4 (13)26 (41)0.0055
RAI score, mean ± SD12.5 ± 510 ± 513.6 ± 40.0004
Biopsy findings positive, n (%)§51 (74)13 (72)38 (75)0.85
Anti-La/SSB positive, n (%)74 (79)26 (84)48 (76)0.39
Anti-Ro/SSA concentration, units/ml12 (0.1–1,150)77 (1–6,000)5 (0.1–400)0.006
Anti-Ro/SSA positive, n (%)80 (80)28 (90)52 (83)0.32
ANA positive, n (%)64 (68)24 (77)40 (63)0.17
Absolute lymphocytes, 109/liter1.3 (0.9–2.0)1.4 (0.9–1.9)1.3 (0.9–2.0)0.77
RF, IU/ml40 (8–200)71 (13–380)30 (7–140)0.015
ESR, mm/hour19 (9–37)23 (12–42)17 (8–34)0.049
WUSF, ml/minute1.3 (0.6–3.2)1.2 (0.5–3.0)1.4 (0.6–3.2)0.32
IgG, mg/dl1,400 (900–2,200)1,630 (1,020–2,600)1,300 (900–2,000)0.019
Schirmer's test, mm/5 minutes6.5 (2.8–15)5.4 (2.5–12)7.1 (3.0–17)0.14

Prevalence and predictors of fatigue severity.

Fatigued subjects (FSS score ≥4) composed 67% of our cohort. Fatigued and nonfatigued subjects did not differ in terms of sex proportion, race, age at examination, or education level. Fatigued subjects had lower RF, ESR, and IgG than nonfatigued subjects. Mean scores for the psychometric scales, with marked differences between fatigued and nonfatigued subjects on all scales, are presented in Table 1.

We investigated the correlations between the psychometric variables (Table 2). Each of the variables were only moderately related, and the strength of the interrelationships between pain and depression, between helplessness and depression, and between helplessness and pain were similar. Each variable proved to be a unique predictor of fatigue in the multivariate models (Tables 3 and 4).

Table 2. Correlations between CES-D, pain VAS, and RAI scores*
  • *

    Values are the Pearson's correlation coefficients (95% confidence intervals). See Table 1 for definitions.

CES-D0.44 (0.22–0.62)
RAI0.44 (0.24–0.62)0.54 (0.37–0.67)
Table 3. Comparison of fitted regression models for 4 fatigue measures (the FSS, ProF-M, ProF-S, and fatigue VAS) with adjustment for clinical characteristics*
  • *

    Values are the standardized regression coefficients showing relative effect size, and are ×100. All 4 fatigue measures are on a standardized scale. All predictors, transformed or untransformed, have been standardized. (log) = transformed to the logarithmic scale. See Table 1 for additional definitions.

  • The percentage of variability in the fatigue measure explained by the model.

CES-D21≤ 0.0543≤ 0.00133≤ 0.00117≤ 0.150
Pain VAS37≤ 0.00119 57≤ 0.00131≤ 0.01
RAI41≤ 0.00127≤ 0.0524≤ 0.0136≤ 0.01
Age at exam−5 −11 −20≤ 0.01−17≤ 0.05
Absolute lymphocytes (log)−26≤ 0.01−16≤ 0.150−5 −23≤ 0.05
RF (log)−27≤ 0.05−8 5 −29≤ 0.05
ESR (log)7 7 3 9 
WUSF (log)18≤ 0.0512 7 1 
IgG (log)24≤ 0.15011 −1 7 
Eye average (log)0 −3 −7 9 
ANA positive26 −17 54≤ 0.013 
Anti-Ro/SSA concentration (log)−19 −10 −17 −4 
R2, %62 54 78 58 
Table 4. Comparison of fitted regression models for 4 fatigue measures (the FSS, ProF-M, ProF-S, and fatigue VAS) without adjustment for clinical characteristics*
  • *

    Values are the standardized regression coefficients showing relative effect size, and are ×100. See Table 1 for definitions.

  • The percentage of variability in the fatigue measure explained by the model.

CES-D24≤ 0.0545≤ 0.00130≤ 0.00124≤ 0.01
Pain VAS35≤ 0.00116≤ 0.1044≤ 0.00134≤ 0.001
RAI32≤ 0.0124≤ 0.0529≤ 0.00127≤ 0.01
R2, %51 49 71 49 

Depression, defined as a CES-D score ≥16, was present in 32% of the subjects. The relationship between fatigue and depression is shown in Figure 1. The mean ± SD FSS score in subjects with depression was 5.5 ± 1.3 and the mean ± SD FSS score in the nondepressed group was 4.2 ± 1.5. Mean FSS scores were significantly higher in the group of subjects with depression (95% CI 0.7–2.0, P < 0.001). Although higher levels of fatigue were correlated with depression, the majority of the fatigued subjects (59%) were not depressed (Figure 1). Interestingly, the anti-Ro/SSA–negative subjects were clustered in the group of fatigued/nondepressed subjects.

Figure 1.

Scatter plot of the Fatigue Severity Scale (FSS) by the Center for Epidemiologic Studies Depression Scale (CES-D).

We compared linear regression models using FSS, fatigue VAS, and the ProF-S and ProF-M as the dependent variables, adjusting for symptom characteristics. Pain, helplessness, and depression were the strongest predictors of both FSS and ProF-S (Table 3). The ProF-M was most strongly associated with depression, and fatigue VAS was associated with pain and helplessness. Absolute lymphocyte count (log) was a significant predictor of FSS and VAS fatigue. RF (log) was a predictor of FSS and VAS fatigue, and ANA positivity was predictive of ProF-S only. These regression models explained greater than half of the variability in the responses.

We compared similar regression models for FSS, fatigue VAS, ProF-S, and ProF-M as the dependent variables without adjustment (Table 4). The predictive associations were essentially unchanged. Using the fatigue VAS as the outcome variable in the model gave results similar to the FSS, except with less weight on helplessness and more weight on age. The ProF-S was more heavily weighted on pain and the ProF-M was more heavily weighted on depression.


The main purpose of this study was to investigate the relative contributions of disease status (sicca severity) and behavioral and immunologic factors to fatigue in primary SS. The main finding of this study is that psychological factors were determinants of fatigue, but they explained only 62% of the variability in FSS. Depression was correlated with fatigue severity, but was not the primary cause of fatigue in primary SS. We also determined that, although the fatigue scales have somewhat different properties, the relationship of pain, depression, and helplessness to fatigue were similar in regression models using the various fatigue measures as the response variable. Neither sicca severity nor laboratory variables were consistently correlated with fatigue.

The mean FSS score of 4.6 that we found in our primary SS subjects is significantly different than the mean ± SD score of 2.3 ± 0.7 reported in healthy adults (12). The mean ProF domain scores in this study (3.43 for somatic fatigue and 2.80 for mental fatigue) were similar in magnitude to the ProF domain scores previously reported for primary SS cohorts in the UK and Sweden, suggesting that the experience of fatigue is similar among primary SS patient groups in different cultural contexts (28, 29).

This study confirms that psychosocial variables are strong determinants of fatigue, which has been reported previously in primary SS and other rheumatic disorders (34). Similar relationships between fatigue, pain, and psychological distress have been reported in SLE (35). In a recent study of fatigue in SLE, pain and depression predicted 42% of the variance in fatigue severity (36). In this study, although more severe fatigue was reported by subjects with depression, abnormal fatigue was frequently experienced in the absence of depression, suggesting that pathways leading to fatigue and depression are independent but interrelated. Use of a multidimensional tool such as the ProF to explore the factors contributing to the mental and somatic aspects of fatigue, previously suggested by Bowman et al (28), could be useful in studying hypotheses of fatigue pathophysiology.

To our knowledge, the current study is the first to examine the relationship of fatigue severity and the construct of helplessness in subjects with primary SS. Our observation that helplessness is associated with fatigue in primary SS suggests that, as previously observed in patients with SLE, fatigue in primary SS can be viewed from the behavioral aspect as a consequence of decreased ability to cope with chronic illness (37). Previous work in RA suggests that an individual with higher helplessness scores is more likely to experience greater pain, depression, and functional impairment (38). Cognitive interventions designed to modulate helplessness may have efficacy in primary SS, as has been demonstrated previously in other rheumatic disorders (39).

Our findings are compatible with the helplessness theory that suggests that patients who see themselves as unable to influence or control their condition are more susceptible to fatigue and depression. Helplessness might contribute to fatigue directly in several ways. In previous research, helplessness correlated with less effective medication use and less positive health behavior (such as exercise) (31). The relationship between helplessness and fatigue in our subjects with primary SS remained significant after taking into account the role of depression. Further study is needed to clarify the contribution of helplessness to fatigue and depression over time.

Our findings are generally consistent with those of previous studies of primary SS in which laboratory variables were not correlated with fatigue (5, 18). Barendregt et al found no correlation between fatigue scores and ESR, disease duration, or the hemoglobin level in patients with primary SS (5). Tensing et al reported that values of ANA, anti-Ro/SSA, and IgG level in primary SS correlated positively with vitality (and therefore inversely with fatigue) on the Medical Outcomes Study Short Form 36 (18). The work by Tensing, Berendregt, and their colleagues, taken together with our data, does not support a role for inflammatory or serologic variables in the pathogenesis of fatigue. Neither IgG level nor anti-Ro titer was predictive of fatigue in any of the multivariate models; ANA positivity was significant only for the ProF-S, and RF titer (log) was negatively correlated with the FSS and the fatigue VAS. However, our study is the first to examine the relationship of lymphocyte count to fatigue in primary SS, and the finding of a negative correlation of lymphocyte count with the FSS and fatigue VAS measures in our study is intriguing.

Inconsistent results were reported in 2 previous studies that examined the relationship of lymphocyte count to fatigue in patients with SLE (35, 40), and negative correlations between inflammatory indices and fatigue have been reported in previous studies of patients with RA and SLE (11, 24, 34, 37). Although a minority of studies of SLE have demonstrated a weak correlation of FSS with disease activity (35, 41), even patients with low disease activity or inactive disease have abnormal fatigue. Given the relationship between fatigue severity and lymphopenia that we observed at a single point in time, longitudinal data would be of interest to clarify the relationship between fatigue and immunologic disease activity in primary SS.

Current understanding of the physiological factors contributing to the perception of fatigue is limited. The effects of sleep quality and neuroendocrinologic variables have not been well studied. There are data regarding the relationship of fatigue to muscle endurance and aerobic exercise capacity in primary SS. Strombeck et al examined the relationship between fatigue and aerobic exercise performance (42). Aerobic capacity and fatigue were negatively correlated, but it is unclear whether patients were less fit because of their fatigue or whether decreased ability to exercise plays a causal role in fatigue.

Despite differences in patient age and sex, the mean ± SD FSS score of 4.6 ± 1.6 in subjects with primary SS in this cohort is similar in magnitude to mean FSS scores previously reported in other autoimmune disease cohorts, including SLE (4.7 ± 1.5), MS (4.8 ± 1.3), and primary biliary cirrhosis (4.6 ± 1.6) (12, 43). Fatigue, depression, and cognitive dysfunction are a poorly understood complex of symptoms characteristic of multiple chronic illnesses including SLE, MS, primary biliary cirrhosis, and HCV infection. (10, 11, 34, 41, 43–46). A similar syndrome of fatigue and neuropsychological symptoms also occurs in patients treated with interferon-α (INFα). In INFα-mediated fatigue, the central nervous system effects are mediated by inflammatory cytokines (47). The acute administration of INFα is associated with fatigue followed by depression and progressive cognitive dysfunction if INF therapy is continued (48). We have previously demonstrated that the INF signature correlates with sicca severity and anti-Ro/SSA titer in primary SS (49). Therefore, the finding of the current study that anti-Ro does not have a significant relationship with fatigue is inconsistent with the hypothesis that peripheral cytokines mediated by INF modulate fatigue in primary SS. There is evidence in animal models of autoimmune disease that suggests that elaboration of inflammatory cytokines within the central nervous system mediates behavioral and neuropsychological abnormalities (50). The animal data suggest a potential role for local cytokines generated within the central nervous system in modulating fatigue, depression, and possibly mild cognitive impairment in primary SS, but to date, the role of intrathecal inflammatory cytokines in primary SS has not been defined.

The strengths of this study include our concurrent assessment of the relationship of pain, depression, helplessness, and clinical variables; the evaluation of a large, community-based sample of subjects with primary SS; comparison between multiple, well-validated instruments for evaluating fatigue; and the careful application of criteria for diagnosis of SS in individuals with sicca symptoms. The demographic characteristics of our patient population are similar to other large, community-based cohorts. The ethnic distribution of the patient group reflects the ethnicity of primary SS in the general population of Minnesota.

Our study does have several limitations. We did not control for the effect of medications on fatigue. We used self-report instruments, potentially subject to response bias, to measure the subjective experience of fatigue. Given the cross-sectional design of this study, the relationship between disease activity and fatigue remains somewhat unclear. Longitudinal data would be helpful for establishing the relationship between the subjective experience of fatigue and the potential physiologic correlates of fatigue. More research is needed to clarify the immune-neuroendocrine interactions contributing to the pathogenesis of fatigue in primary SS and related autoimmune disorders.

The burden of fatigue in primary SS and other autoimmune disorders is considerable. We have demonstrated that psychological factors contribute to fatigue but do not completely account for it. In the future, delineation of the biologic pathways underlying the various subjective aspects of fatigue could provide additional insight into the causes of the persistent fatigue associated with primary SS. Moreover, elucidation of the neuroendocrinologic factors contributing to fatigue is likely to provide clues to this enigmatic and subtle cognitive dysfunction frequently reported by patients with primary SS.


Dr. Segal had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study design. Segal, Rhodus, Moser.

Acquisition of data. Segal, Hughes, D. Patel, K. Patel, Novitzke, Myers, Nazmul-Hossain, Emamian, Huang, Rhodus, Moser.

Analysis and interpretation of data. Segal, Thomas, Rogers, Rohrer, Gopalakrishnan, Myers, Rhodus, Moser.

Manuscript preparation. Segal, Thomas, Rhodus, Moser.

Statistical analysis. Segal, Thomas, Rogers.


The authors wish to thank the following research assistants, without whose support this study could not have been done: Megan Slater, Jill Weber, Liliana Tobon, Carol Dunn, Carolyn Meyer, Amber Leiran, Anita Peterson, and Nicky Te Poel. We also gratefully acknowledge the kind cooperation of the subjects; without their cooperation, this study would not have been possible.