Fig. 31.1 Measurement of quality of life in patients with primary SS, SLE, RA and controls (SF-36 and WHOQOL scales).

non-inflammatory conditions such as fibromyalgia. Data in PSS using a shortened form of the SF-36, the SF-20, have also been reported [18].

31.3Other Generic QoL/HRQoL Measures

Patients with PSS have been shown to have reduced QoL across all four domains of the WHOQoL-BREF compared with a community control comparator group [10]. The pattern was similar to a comparator group of patients with systemic lupus erythematosus. The main difference compared to a further control group of patients with rheumatoid arthritis was that the rheumatoid arthritis group had significantly lower scores on the physical domain scale (Fig. 31.1). The WHOQOL-BREF physical scale scores correlated with SF-36 vitality and physical domain scores.

Another HRQoL questionnaire that is increasingly likely to be used over the next few years is the EuroQoL 5-domain (EQ-5D) questionnaire [19]. The EuroQoL group, founded in 1987, includes researchers from the UK, Finland, the Netherlands, Norway, Sweden and other countries in Europe, North America, and Japan. Their goal was to develop a generic HRQoL measure for use across Europe and elsewhere. The EQ-5D comprises five domains: mobility, self-care, usual activities, pain/discomfort and anxiety/depression as well as a global health status “thermometer” (100 mm visual analogue scale). The EQ-5D is similar to the WHOQoL in that it generates a single global HRQoL score as well as individual domain scores. Rajagopalan et al. have reported on the EQ-5D in 32 patients with PSS and shown comparable reductions in HRQoL with the EQ-5D and SF-36 [20]. Two much larger studies are currently collecting EQ-5D data in PSS – the European League Against

Rheumatism (EULAR) Sjögren’s working group [21] and the UK Primary Sjögren’s Syndrome Registry (UKPSSR) [22].

Other HRQoL measures that have been widely used (although not in PSS) include the Nottingham Health Profile (NHP) [23], the Sickness Impact Profile (SIP) [24], and many others, e.g.: http://phi.uhce.ox.ac.uk/home.php and http://www.healthmeasurement.org/Measures.html. A Swedish group reported on reduced QoL in PSS using the Gothenburg Quality of Life Instrument (GQOL) [25].

31.4“Disease-Specific” HRQoL Measures

A number of oral and ocular dryness symptom questionnaires can be applied in PSS [26]. The Sicca Symptoms Inventory measures both oral and ocular dryness as well as other sicca symptoms [27]. Some of these questionnaires, such as the Oral Health Impact Profile [28], have been proposed to be “disease-specific” HRQoL measures, on the basis that they do not only measure oral symptoms but also the social impact of oral disorders. The OHIP comprises 49 questions in seven domains: functional limitations (Q1–9), physical pain (Q10–18), psychological discomfort (Q19–23), physical disability (Q24–32), psychological disability (Q33–38), social disability (Q39–43) and handicap (Q44–49). The items range from simple symptoms (e.g., Q1: “Have you had difficulty chewing any foods because of problems with your teeth, mouth or dentures?”) to more complex effects on social functioning (e.g., Q39: “Have you avoided going out because of problems with your teeth, mouth or dentures?”), and general health perception (e.g., Q44: “Have you felt that your general health has worsened because of problems with your teeth, mouth or dentures?”). In a study that compared different groups of patients lacking teeth to those with teeth, Allen et al. [29] demonstrated that the OHIP discriminated between groups whereas the SF-36 did not. Moreover, the OHIP was sensitive to change following the provision of dentures or dental implants [30].

In patients with PSS, OHIP-49 scores are reduced compared to controls and where the SF-36 was also used the scores parallel those of the latter [31–34]. In another study the OHIP-14 (a shortened version of the OHIP-49) total score correlated significantly with five of the eight SF-36 domain scores, particularly with the domains of social functioning (p < 0.01) and general health (p<0.01) [13]. One important point to emphasize is that since the OHIP includes question items on both social functioning and general health (see above), one might predict correlations between the generic and “disease-specific” HRQoL measures. It is useful to see this borne out in a formal evaluation in this study. Other reported oral health HRQoL measures include the Oral Health-related QoL measure [35], the Geriatric Oral Health Assessment Index [36], and the Xerostomia-related QoL questionnaire [37].

With regard to ocular features, a comparison of the widely used Ocular Surface Disease Index (OSDI) (predominantly a dryness symptom questionnaire) and the National Eye Institute Visual Function Questionnaire (NEI-VFQ) (which includes a broad range of visual symptom questions but also some vision-related HRQoL

domains such as vision-specific social functioning, mental health, role functioning and dependency) in 109 patients with dry eye showed significant correlations between the measures [38]. Similar correlations between the OSDI and the symptom components of the NEI-VFQ-25 were observed in a study of 42 patients with PSS [39]. The “HRQoL” components of the NEI-VFQ have been shown to correlate with relevant domains of the SF-36 in a study of patients with a variety of ocular disorders [40].

31.5Predictors of HRQoL (SF-36) in PSS

We have described a variety of studies above that demonstrate reduced SF-36 scores in patients with PSS. What are the potential reasons for reduced HRQoL in this disorder? Belenguer et al. studied 110 patients with PSS [11]. Age correlated with SF-36 physical functioning and bodily pain domain scores. Patients with extraglandular features had lower scores for the vitality, social functioning, bodily pain and general health, whereas sicca features were not significantly associated with SF-36 domain scores. Champey et al. studied 111 patients with PSS and 65 patients with sicca symptoms without autoimmune features [12]. In both groups, fatigue and pain correlated with physical composite scores of the SF-36. In addition, psychological distress, measured by the symptom checklist 90 revised (SCL-90-R) questionnaire, correlated with SF-36 physical and mental domain composite scores. However, sicca symptoms did not.

In a study by Meijer et al. that included 185 patients with PSS and 50 with secondary SS, fatigue was correlated strongly with physical and mental composite scores in the combined population [15]. Multivariate regression analysis also identified that “tendomyalgia”, comorbidity, male sex, and disability compensation correlated with SF-36 physical composite scores. Articular involvement, the use of anti-depressants, and comorbidity were associated with reduced SF-36 mental composite scores. However, the data interpretation was complicated by the fact that both PSS and secondary SS were included in the study. Another study of 277 patients with PSS demonstrated that somatic fatigue was the unique predictor of the general health domain scores of SF-36, pain, severity and depression of emotional well-being [16]. Depression accounted for 25% of the variance of emotional well-being. Age, pain severity, and somatic fatigue predicted the overall level of physical functioning [16].

A recent study of 30 patients with PSS examined the correlations between SF-36 scores and serum cytokine levels [17]. This study identified an inverse relationship between serum IL-6 levels and SF-36 bodily pain, physical functioning, and the physical composite score [17]. D’Elia and colleagues have also shown that baseline serum soluble IL-6 receptor (sIL6R) correlates inversely with fatigue as measured by MFI and VAS and positively with vitality and mental component scores of the SF-36 [41]. Data from other studies, however, report different findings. Hartkamp et al. [42] compared serum cytokine levels including of IL-6 in PSS patients and controls and found no correlation between the levels of fatigue (assessed using MFI) and the levels of these cytokines.

Table 31.2 Summary of published data on the clinical and biological predictors of HRQoL (SF-36 Domain Scores) in PSS [11, 12, 15–17, 41, 44, 45]

aSicca was not a predictor for any of the SF-36 domains listed [11, 12]

Fatigue is identified as a predictor of SF-36 domain scores in a variety of studies. In an investigation of 94 patients with PSS, pain, helplessness, and depression were predictors of physical and mental fatigue [43]. Table 31.2 indicates some of the predictors of reduced HRQoL identified in studies of PSS.

31.6Predictors of QoL and HRQoL (WHOQoL) in PSS

In validation studies of instruments for the assessment of systemic disease activity and accumulated damage in patients with PSS, we evaluated 104 patients at baseline and at 12 months. For the Sjögren’s systemic Clinical Activity Index (SCAI), the SF-36 vitality domain correlated with the SCAI fatigue domain and the SF-36 physical summary score correlated with the SCAI arthritis domain score [44]. A 29-item damage score that incorporated ocular, oral, and systemic domains was also agreed upon. Total damage score correlated with disease activity and duration at study entry and also with physical function as measured by the SF-36 [45].

We can also examine this same data looking for correlations between the WHO “global” QoL question “how do you rate your QoL?”, the WHO “global” HRQoL question “how satisfied are you with your health?” and multiple other symptomatic and “objective” measures (Table 31.3). One observation from these data is that age, disease duration and objective measures of disease activity SCAI (Sjögren’s Clinical

448 S.J. Bowman and W.-Fai Ng

Table 31.3 Correlation analysis of variables with WHOQoL ‘global’ QoL and HRQoL questions [3, 4]

Source: Data is derived from PSS patients recruited in Bowman et al. [44] and Barry et al. [45] IgG, IgA, anti-Ro and anti-La antibody titers*, SSDI [45] ocular*, oral*, systemic and total* damage: r between −0.146 and 0.206 p = not significant at 0.05. Patient n between 98 and 104 for all analyses above except for * where n is between 84 and 87

Activity Index) scores, Sjögren’s Syndrome Damage Index (SSDI) scores, tear production (Schirmer’s I test), the unstimulated salivary flow rate, and biological markers such as immunoglobulin and autoantibody titers correlate poorly with global WHOQoL item ratings. The symptomatic measures: a measure of depression (a modified short 10-item version of the Beck Depression Inventory (BDI)), components of the Profile of Fatigue and Discomfort (PROFAD), Sicca Symptoms Inventory (SSI), and the SF-36 all correlate highly with each other, such that it is