Nagui Gendi

Health-related utility values of patients with primary Sjögren's syndrome and its predictors

Objectives EuroQoL-5 dimension (EQ-5D) is a standardised preference-based tool for measurement of health-related quality of life and EQ-5D utility values can be converted to quality-adjusted life years (QALYs) to aid cost-utility analysis. This study aimed to evaluate the EQ-5D utility values of 639 patients with primary Sjögrens syndrome (PSS) in the UK. Methods Prospective data collected using a standardised pro forma were compared with UK normative data. Relationships between utility values and the clinical and laboratory features of PSS were explored. Results The proportion of patients with PSS reporting any problem in mobility, self-care, usual activities, pain/discomfort and anxiety/depression were 42.2%, 16.7%, 56.6%, 80.6% and 49.4%, respectively, compared with 5.4%, 1.6%, 7.9%, 30.2% and 15.7% for the UK general population. The median EQ-5D utility value was 0.691 (IQR 0.587–0.796, range −0.239 to 1.000) with a bimodal distribution. Bivariate correlation analysis revealed significant correlations between EQ-5D utility values and many clinical features of PSS, but most strongly with pain, depression and fatigue (R values>0.5). After adjusting for age and sex differences, multiple regression analysis identified pain and depression as the two most important predictors of EQ-5D utility values, accounting for 48% of the variability. Anxiety, fatigue and body mass index were other statistically significant predictors, but they accounted for <5% in variability. Conclusions This is the first report on the EQ-5D utility values of patients with PSS. These patients have significantly impaired utility values compared with the UK general population. EQ-5D utility values are significantly related to pain and depression scores in PSS.

Fatigue in primary Sjögren's syndrome is associated with lower levels of proinflammatory cytokines.

Objectives This article reports relationships between serum cytokine levels and patient-reported levels of fatigue, in the chronic immunological condition primary Sjögrens syndrome (pSS). Methods Blood levels of 24 cytokines were measured in 159 patients with pSS from the United Kingdom Primary Sjögrens Syndrome Registry and 28 healthy non-fatigued controls. Differences between cytokines in cases and controls were evaluated using Wilcoxon test. Patient-reported scores for fatigue were evaluated, classified according to severity and compared with cytokine levels using analysis of variance. Logistic regression was used to determine the most important predictors of fatigue levels. Results 14 cytokines were significantly higher in patients with pSS (n=159) compared to non-fatigued healthy controls (n=28). While serum levels were elevated in patients with pSS compared to healthy controls, unexpectedly, the levels of 4 proinflammatory cytokines—interferon-γ-induced protein-10 (IP-10) (p=0.019), tumour necrosis factor-α (p=0.046), lymphotoxin-α (p=0.034) and interferon-γ (IFN-γ) (p=0.022)—were inversely related to patient-reported levels of fatigue. A regression model predicting fatigue levels in pSS based on cytokine levels, disease-specific and clinical parameters, as well as anxiety, pain and depression, revealed IP-10, IFN-γ (both inversely), pain and depression (both positively) as the most important predictors of fatigue. This model correctly predicts fatigue levels with reasonable (67%) accuracy. Conclusions Cytokines, pain and depression appear to be the most powerful predictors of fatigue in pSS. Our data challenge the notion that proinflammatory cytokines directly mediate fatigue in chronic immunological conditions. Instead, we hypothesise that mechanisms regulating inflammatory responses may be important.

Do the EULAR Sjögren’s syndrome outcome measures correlate with health status in primary Sjögren’s syndrome?

OBJECTIVE This study sets out to investigate the relationship between health status [EuroQol five-dimensions questionnaire (EQ-5D)] in primary SS and three of the European League Against Rheumatism (EULAR) SS outcome measures-the disease activity index (ESSDAI), the patient reported index (ESSPRI) and the sicca score. In particular, the goal was to establish whether there is a relationship between the EULAR outcome measures and quality of life. METHODS Health status was evaluated using a standardized measure developed by the EuroQol Group-the EQ5D. This permits calculation of two measures of health status: time trade-off (TTO) values and the EQ-5D visual analogue scale (VAS) scores. We used Spearmans rank correlation analysis to investigate the strength of association between health status and three EULAR measures of physician- and patient-reported disease activity in 639 patients from the UK primary SS registry (UKPSSR) cohort. RESULTS This study demonstrates that the EULAR SS disease-specific outcome measures are significantly correlated with health outcome values (P < 0.001). Higher scores on the ESSDAI, EULAR sicca score and ESSPRI are associated with poorer health states-i.e. lower TTO values and lower VAS scores. While all three are significantly correlated with TTO values and EQ-5D VAS scores, the effect is strongest for the ESSPRI. CONCLUSION This study provides further evidence supporting the use of ESSDAI, EULAR sicca score and ESSPRI measures in the clinic. We also discuss the need for disease-specific measures of health status and their comparison with standardized health outcome measures.

A Transcriptional Signature of Fatigue Derived from Patients with Primary Sjögren's Syndrome.

Background Fatigue is a debilitating condition with a significant impact on patients’ quality of life. Fatigue is frequently reported by patients suffering from primary Sjögren’s Syndrome (pSS), a chronic autoimmune condition characterised by dryness of the eyes and the mouth. However, although fatigue is common in pSS, it does not manifest in all sufferers, providing an excellent model with which to explore the potential underpinning biological mechanisms. Methods Whole blood samples from 133 fully-phenotyped pSS patients stratified for the presence of fatigue, collected by the UK primary Sjögren’s Syndrome Registry, were used for whole genome microarray. The resulting data were analysed both on a gene by gene basis and using pre-defined groups of genes. Finally, gene set enrichment analysis (GSEA) was used as a feature selection technique for input into a support vector machine (SVM) classifier. Classification was assessed using area under curve (AUC) of receiver operator characteristic and standard error of Wilcoxon statistic, SE(W). Results Although no genes were individually found to be associated with fatigue, 19 metabolic pathways were enriched in the high fatigue patient group using GSEA. Analysis revealed that these enrichments arose from the presence of a subset of 55 genes. A radial kernel SVM classifier with this subset of genes as input displayed significantly improved performance over classifiers using all pathway genes as input. The classifiers had AUCs of 0.866 (SE(W) 0.002) and 0.525 (SE(W) 0.006), respectively. Conclusions Systematic analysis of gene expression data from pSS patients discordant for fatigue identified 55 genes which are predictive of fatigue level using SVM classification. This list represents the first step in understanding the underlying pathophysiological mechanisms of fatigue in patients with pSS.

Subjective and Objective Measures of Dryness Symptoms in Primary Sjögren’s Syndrome – Capturing the discrepancy

To develop a novel method for capturing the discrepancy between objective tests and subjective dryness symptoms (a sensitivity scale) and to explore predictors of dryness sensitivity.