POS0960 PRESENCE AND ASSOCIATED FACTORS OF FATIGUE IN PATIENTS IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)

Background:

Fatigue/tiredness is an essential aspect of disease for patients with axial spondyloarthritis (axSpA). However, little is known about its prevalence and associated factors.

Objectives:

The aim is to assess the prevalence of fatigue and associated factors in a large sample of patients with axSpA patients from 13 European countries.

Methods:

Data from 2,846 unselected patients of the European Map of Axial Spondyloarthritis (EMAS) through an online survey (2017-2018) across 13 European countries were analyzed.

The presence of fatigue/tiredness was evaluated using the Visual Analogue Scale from the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI): “How would you describe the overall level of fatigue/tiredness you have experienced? (0-10)”. Risk of poor mental health was assessed using the 12-Item General Health Questionnaire (GHQ-12; 0-12).

Possible associated factors included: Socio-demographic and disease characteristics, disease activity and function and mental health disorders.

The Mann-Whitney test was used to compare the means of variables of two categories vs. the numerical variables, the χ2 test was used to compare the distribution between the categorical variables. Binary logistic regression and multiple linear regression were used to identify possible predictors.

Results:

A total of 2,846 axSpA patients participated in the EMAS survey: mean age was 43.9 years, 61.3% female, 48.1% had a university degree, 67.9% were married and 71.3% were HLA-B27 positive. Fatigue/tiredness was associated with younger age (6.4±2.3 vs 5.5±2.4), being female (6.6±2.2 vs 5.7±2.4), lower educational level (6.9±2.4 vs 6.0±2.0) and separated or divorced persons (6.8±2.2 vs 6.2±2.3; all p<0.001). Those reporting work impact (6.8±2.1 vs 5.8±2.4), physically inactive (6.9±2.2 vs 6.1±2.3) or those with sleep disorders (7.0±2.0 vs 5.8±2.4), anxiety (7.0 ± 2.0 vs 5.9±2.4) or depression (7.2±1.9 vs 5.9±2.4; all p<0.001) also presented greater fatigue, as did those with higher morning stiffness (r=0.499) and functional limitation (r=0.257), and poorer mental health GHQ-12 (r=0.419). Finally, the variables independently associated with fatigue were female gender (B=0.427), being physical inactive (B=-0.395) and those with greater morning stiffness severity (B=0.349; see Table 1). In addition, those on temporary and permanent sick leave, along with the unemployed, presented greater fatigue (7.1, 6.8 and 7.1 respectively).

Table 1.

Linear regression analysis to predict presence of fatigue/tiredness (N = 2052)

SimpleMultivariateB95% CIp-valueB95% CIp-valueAge-0.018-0.025, -0.011<0.001*-0.015-0.022, -0.008<0.001Gender (female)0.8380.659, 1.017<0.001*0.4270.264, 0.590<0.001Marital status (married)0.1900.042, 0.3390.012*0.1620.021, 0.3020.024*Educational level (university)-0.274-0.402, -0.146<0.001*-0.128-0.245, -0.0120.031*BMI (Overweight/Obesity)0.151-0.026, 0.3280.094NANANAMorning stiffness severity (0-10) *0.4730.442, 0.505<0.001*0.3490.314, 0.385<0.001*Functional limitation (0-54)0.0380.032, 0.044<0.001*0.0140.008, 0.019<0.001*Reported Work impact (yes)0.9360.753, 1.119<0.001*0.2280.068, 0.3890.005*Physical activity (yes)-0.726-0.968, -0.485<0.001*-0.395-0.611, -0.178<0.001*Sleep disorder (yes)1.1911.013, 1.368<0.001*0.2760.095, 0.4580.003*Anxiety (yes)1.1390.950, 1.327<0.001*0.002-0.215, 0.2200.982Depression (yes)1.2741.079, 1.469<0.001*0.2230.001, 0.4460.049*GHQ-12 (0-12) **0.2340.215, 0.254<0.0010.1100.088, 0.132<0.001*

*As measured by the respective item of the BASDAI scale

**12-item General Health Questionnaire. A value of 3 or above indicates a risk of poor mental health

Conclusion:

Fatigue/tiredness was highly prevalent among axSpA European patients with female gender, engage in physical activity and those with greater morning stiffness severity most strongly associated, and the unemployed presenting greatest fatigue.

Acknowledgements:

This study was supported by Novartis Pharma AG. The authors would like to thank all patients who participated in the study.

Disclosure of Interests:

Marco Garrido-Cumbrera: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Laura Christen Employee of: Novartis Pharma AG, Christine Bundy Speakers bureau: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer., Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, José Correa-Fernández: None declared, Sergio Sanz-Gómez: None declared, Denis Poddubnyy Speakers bureau: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB., Grant/research support from: Abbvie, MSD, Novartis, and Pfizer.

POS0905 ACHIEVEMENT OF PARTIAL REMISSION AND INACTIVE DISEASE IN UPADACITINIB-TREATED PATIENTS WITH ANKYLOSING SPONDYLITIS

Background:

Assessment of SpondyloArthritis international Society (ASAS) response criteria and AS Disease Activity Score (ASDAS) are both commonly used, rigorous composite indices consisting of components with relevance to patients. Clinically meaningful thresholds for these measures have been defined to reflect partial remission (PR), inactive disease (ID), and low disease activity (LDA).

Objectives:

To study the association of ASAS PR and ordinal ASDAS disease categories (including ASDAS ID, which is the most stringent category of this composite score) in upadacitinib (UPA)-treated patients with AS.

Methods:

In the SELECT-AXIS 1 (NCT03178487) study, biologic DMARD naïve-patients (pts; ≥18 y) with active AS and intolerance/contraindication or inadequate response to ≥2 NSAIDs were randomized 1:1 to UPA 15 mg once daily (QD) or placebo (PBO).1 At wk 14, pts entered an open-label extension (OLE) of UPA 15 mg QD; pts randomized to PBO were switched to UPA. This post hoc analysis assessed the responsiveness of individual ASAS and ASDAS core components among pts who achieved ASAS PR. The association of ASAS PR with achievement of ASDAS ID (ASDAS <1.3), ASDAS LDA (ASDAS <2.1 but ≥1.3) or ASDAS high disease activity (HDA)/very HDA (VHDA) (ASDAS ≥2.1 for HDA/VHDA) was also assessed by measures including Youden index, distance to perfect point, and sensitivity/specificity equality. These evaluations were performed in pts randomized to UPA from baseline (BL; continuous UPA, assessed at wk 14) and those who were randomized to PBO and switched to UPA upon entry in the OLE (PBO to UPA; re-baselined at wk 14 and assessed at wk 32, representing 18 wks of UPA exposure).

Results:

At wk 14, for the continuous UPA group, 16 pts (19%) achieved ASAS PR. At wk 32, following 18 wks of UPA exposure for the PBO-to-UPA group, 28 pts (33%) achieved ASAS PR. Among both groups (continuous UPA and PBO-to-UPA), improvements were seen across all core components (Figure 1). Of the 44 total pts who achieved ASAS PR, 91% achieved either ASDAS ID or LDA. The majority of patients who achieved ASAS PR achieved ASDAS ID in the continuous UPA and PBO-to-UPA groups: 11/16 (69%) and 16/28 (57%), respectively. For the continuous UPA group, the remaining 5 pts who achieved ASAS PR also achieved ASDAS LDA (Table 1). ASAS PR was associated with ASDAS categories in the following manner: the highest rate of ASAS PR was achieved for ASDAS ID followed by ASDAS LDA followed by ASDAS HDA/VHDA. The cutoff of 1.3 (the upper threshold for ASDAS ID) was a better discrimination threshold for ASAS PR than the cutoff of 2.1 (the upper threshold for ASDAS LDA).

Conclusion:

Nineteen percent of pts receiving UPA from BL achieved ASAS PR after 14 wks of treatment, with similar results seen in pts who were originally randomized to PBO and switched to UPA at wk 14. A consistent improvement was seen across all core components of ASAS among those who achieved ASAS PR with UPA treatment. The achievement of ASAS PR was most closely associated with the achievement of ASDAS ID, providing further clarity on the reduction of disease activity in AS pts treated with UPA.

References:

[1]van der Heijde, et al. Lancet. 2019;394(10214):2108-2117.

Table 1.

Association Between ASAS PR and ASDAS Clinical Thresholds (ID/LDA/HDA or VHDA)

ASDAS ID(<1.3)ASDAS LDA(1.3 to <2.1)ASDAS HDA or VHDA(≥2.1)Continuous UPA Groupn=15n=31n=39 ASAS PR Responders (n=16)1150 ASAS PR Non-responders (n=69)42639PBO to UPA Groupn=25n=35n=25 ASAS PR Responders (n=28)1684 ASAS PR Non-responders (n=57)92721

P<0.001 for association of ASAS PR with the ordered ASDAS categories of ID-LDA-HDA, for both Continuous UPA Group and PBO to UPA Group. P-value calculated from Cochran-Armitage trend test for association of ordinal categories.

ASAS, Assessment of SpondyloArthritis international Society response criteria; ASDAS, AS Disease Activity Score; HDA, high disease activity; ID, inactive disease; LDA, low disease activity; PBO, placebo; PR, partial remission; UPA, upadacitinib; VHDA, very high disease activity.

Acknowledgements:

AbbVie funded this study and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this publication. No honoraria or payments were made for authorship. Medical writing support was provided by J Urbanik of AbbVie and M Hovenden and J Matsuura of Complete Publication Solutions, LLC (funded by AbbVie).

Disclosure of Interests:

Atul Deodhar Speakers bureau: Novartis and Pfizer, Consultant of: Novartis, Pfizer, AbbVie, Eli Lilly, UCB Pharma, GlaxoSmithKline, Galapagos, Janssen, Boehringer Ingelheim and Celgene, Amgen., Grant/research support from: AbbVie, Eli Lilly, UCB Pharma, GlaxoSmithKline, Andrew Ostor Consultant of: AbbVie, BMS, Roche, Janssen, Lilly, Novartis, Pfizer, UCB, Gilead, and Paradigm, anna maniccia Shareholder of: AbbVie, Employee of: AbbVie, Fabiana Ganz Shareholder of: AbbVie, Employee of: AbbVie, Tianming Gao Shareholder of: AbbVie, Employee of: AbbVie, Alvina Chu Shareholder of: AbbVie, Employee of: AbbVie, Denis Poddubnyy Speakers bureau: AbbVie, BMS, Lilly, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Biocad, Gilead, GSK, Lilly, MSD, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Lilly, MSD, Novartis, and Pfizer

OP0256 CHOOSE WISELY: IMAGING FOR DIAGNOSIS OF AXIAL SPONDYLOARTHRITIS

Background:

To date, the European Alliance of Associations for Rheumatology (EULAR) guidelines recommend X-ray (XR) as first line imaging in axial Spondyloarthritis (axSpA) and magnetic resonance imaging (MR) if the diagnosis cannot be established by XR and clinical features. However, much knowledge has been gained recently strengthening the applicability of MR for the detection of structural lesions and raising the question, whether XR is still necessary. Also, several publications used low-dose computed tomography (CT) as reference standard and imaging test.

Objectives:

In light of this complex diagnostic situation, the aim of this study was to compare the three major modalities, XR, MR and CT of SIJ, in their diagnostic performance of axSpA and differential diagnosis in a cohort of patients with low back pain using the final judgment of the rheumatologist as standard of reference.

Methods:

163 patients (89 with axSpA; 74 with degenerative diseases) underwent XR, CT and MR. Three blinded experts categorized the imaging into axSpA, other diseases or normal in 5 separate reading rounds (XR, CT, MR, XR+MR, CT+MR, respectively). The results were compared to the clinical diagnosis. Sensitivity and specificity values for axSpA and interrater reliability were compared.

Results:

XR showed lower sensitivity and specificity (66.3%/67.6% respectively) compared to MR (82.0%/86.5%) and CT (77.5%/97.3%). Sensitivity and specificity of XR+MR was similar to MR alone (77.5% / 87.8%). However, CT+MR was superior to MR alone (75.6% / 97.3%) (see Figure). CT had the best interrater reliability (kappa = 0.875) followed by MR (0.665) and XR (0.517). CR+MR reliability was similar (0.662) compared to MR alone, while CT+MR reliability (0.732) was superior.

Figure 1.

Frequency of positive and negative findings in radiography (XR), computed tomography (CT), magnetic resonance imaging (MR) and combinations and resulting diagnostic accuracy values. SE: Sensitivity, SP: Specificity, LR-/+: negative/positive likelihood ratio.

Conclusion:

In conclusion, XR is inferior to cross-sectional imaging and should be replaced by MR or CT for differential diagnosis. While MR is the most sensitive imaging technique, it lacks specificity when compared to CT. CT alone has high diagnostic accuracy, despite being insensitive to bone marrow lesions such as fatty metaplasia or osteitis. Adding CT to MR leads to an increase in specificity at a minor expense of sensitivity.

References:

[1]Sieper J, Rudwaleit M, Baraliakos X, et al. The Assessment of SpondyloArthritis international Society (ASAS) handbook: a guide to assess spondyloarthritis. Ann Rheum Dis. 2009;68 Suppl 2:ii1-44.

[2]Mandl P, Navarro-Compán V, Terslev L, et al. EULAR recommendations for the use of imaging in the diagnosis and management of spondyloarthritis in clinical practice. Ann Rheum Dis. 2015;74(7):1327-39.

[3]Diekhoff T, Hermann KA, Greese J, et al. Comparison of MRI with radiography for detecting structural lesions of the sacroiliac joint using CT as standard of reference: results from the SIMACT study. Ann Rheum Dis. 2017.

[4]Diekhoff T, Greese J, Sieper J, Poddubnyy D, Hamm B, Hermann KA. Improved detection of erosions in the sacroiliac joints on MRI with volumetric interpolated breath-hold examination (VIBE): results from the SIMACT study. Ann Rheum Dis. 2018;77(11):1585-89.

[5]Baraliakos X, Hoffmann F, Deng X, Wang YY, Huang F, Braun J. Detection of Erosions in Sacroiliac Joints of Patients with Axial Spondyloarthritis Using the Magnetic Resonance Imaging Volumetric Interpolated Breath-hold Examination. The Journal of rheumatology. 2019;46(11):1445-49.

[6]Wu H, Zhang G, Shi L, et al. Axial Spondyloarthritis: Dual-Energy Virtual Noncalcium CT in the Detection of Bone Marrow Edema in the Sacroiliac Joints. Radiology. 2019;290(1):157-64.

Disclosure of Interests:

Torsten Diekhoff Speakers bureau: Canon MS, Roche, Novartis, MSD, Grant/research support from: Assessment of Spondyloarthritis International Society, Iris Eshed: None declared, Felix Radny: None declared, Katharina Ziegeler: None declared, Fabian Proft: None declared, Juliane Greese: None declared, Dominik Deppe: None declared, Robert Biesen: None declared, Kay-Geert Hermann: None declared, Denis Poddubnyy: None declared

OP0251 DATA-DRIVEN DEFINITIONS BASED ON INFLAMMATORY LESIONS FOR A POSITIVE MRI OF THE SPINE CONSISTENT WITH AXIAL SPONDYLOARTHRITIS

Background:

The ASAS definition of a positive MRI for inflammation in the spine (ASAS-MRIspine+) is intended for classification of patients as having axSpA but is often misused for diagnostic purposes. This is problematic because bone marrow edema (BME) in the spine may occur in 20-40% of those with mechanical back disorders. The ASAS MRI group has generated updated consensus lesion definitions which have been validated on MRI spine images from the ASAS Classification Cohort.

Objectives:

We aimed to identify quantitative cut-offs based on numbers of vertebral corners that define ASAS-MRIspine+, there being two gold standards: A. majority central reader decision as to the presence of spine MRI findings consistent with axSpA B. rheumatologist expert opinion diagnosis of axSpA.

Methods:

Eight ASAS-MRI readers recorded MRI lesions in the spine according to recently updated ASAS definitions from 62 cases in an eCRF that comprises global assessment (MRI consistent with axSpA? (yes/no)), and detailed scoring of lesions for all sites in the spine. We calculated sensitivity and specificity for numbers of vertebral corners with BME where a majority of readers (≥5/8) agreed as to the presence of MRI findings consistent with axSpA. We selected cut-offs with ≥95% specificity. These cut-offs were analyzed for their predictive utility for rheumatologist diagnosis of axSpA by calculating positive and negative predictive values (PPV, NPV) and selecting cut-offs with PPV ≥95%. Both criteria were considered requirements for designation of MRI cut-offs defining ASAS-MRIspine+.

Results:

MRI findings consistent with axSpA were observed by majority read in 8 (20%) of 40 cases diagnosed with axSpA, and 0 (0%) of 19 cases without axSpA. Cut-offs achieving specificity of ≥95% for MRI findings consistent with axSpA were 4 vertebral corners (sensitivity 75%) for all cases, 3 vertebral corners (sensitivity 37.5%) for cases with ≥1 additional location with inflammation, 1 vertebral corner (sensitivity 62.5%) in cases with ≥2 vertebral corner fat lesions (Table 1). All of the above cut-offs also had very high PPV (≥95%) for diagnosis of axSpA in cases diagnosed by the rheumatologist (Table 2).

Table 1.

Majority readers agree MRI findings consistent with axSpA are present is the gold-standard external reference

MRI cut-offsSensitivity (95%CI)Specificity (95%CI)BME in ≥2 vertebral corners87.5 (47.3 - 99.7)87.0 (75.1 - 94.6)BME in ≥ 3 vertebral corners87.5 (47.3 - 99.7)94.4 (84.6 - 98.8)BME in ≥4 vertebral corners75.0 (34.9 - 96.8)98.2 (90.1 - 100.0)Cases with ≥1 additional non-corner site inflammatory lesionBME in ≥2 vertebral corners37.5 (8.5 - 75.5)94.4 (84.6 - 98.8)BME in ≥3 vertebral corners37.5 (8.5 - 75.5)98.2 (90.1-100.0)Cases with ≥2 vertebral corner fat lesionsBME in ≥1 vertebral corner62.5 (24.5 - 91.5)100.0 (93.4-100.0)BME in ≥2 vertebral corners62.5 (24.5 - 91.5)100.0 (93.4-100.0)Table 2.

Predictive values of cut-offs for number of vertebral corners with BME according to the diagnostic ascertainment of the rheumatologist

MRI cut-offsSensitivity (95%CI)Specificity (95%CI)PPVNPVMRI findings consistent with axSpA ≥any 2 readers52.5 (36.1 - 68.5)94.7 (74.0 - 99.9)95.5 (75.3 - 99.3)48.6 (40.2 - 57.2)MRI findings consistent with axSpA ≥majority read20.0 (9.1 - 35.6)100.0 (82.4 - 100.0)100.037.3 (33.7 - 40.9)BME in ≥ 4 vertebral corners17.5 (7.3 - 32.8100.0 (82.4 - 100.0)100.036.5 (33.3 - 39.9)Cases with ≥1 additional inflammatory lesionBME in ≥ 3 vertebral corners10.00 (2.8 - 23.7)100.00 (82.4 - 100.0)100.034.5 (32.2 - 36.9)Cases with ≥2 vertebral corner fat lesionsBME in ≥1 vertebral corner12.50 (4.2 - 26.8)100.00 (82.4 - 100.0)100.035.2 (32.6 - 37.9)

Conclusion:

A cut-off of BME in ≥4 vertebral corners, or ≥3 corners in the setting of additional inflammatory lesions at other locations or corner fat, are primary candidates for defining ASAS-MRIspine+. These cut-offs apply to typical patients referred to a rheumatologist with a high index of suspicion of axSpA and may not be appropriate in other populations.

Disclosure of Interests:

None declared

POS0990 FACTORS ASSOCIATED WITH ENGAGING IN PHYSICAL ACTIVITY IN AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)

Background:

Physical activity is an essential component in axial spondyloarthritis (axSpA) care, improving physical and mental well-being.

Objectives:

This analysis aims to identify factors associated with engaging in physical activity among axSpA patients.

Methods:

Data from 2,424 unselected patients participating in EMAS (N=2,846), a cross-sectional study (2017-2018) across 13 European countries, were analysed. Engaging in physical activity was assessed by the following item: “Do you do any physical or sporting activity?” for which participants could report at least 1 physical activity or that they did not do any physical activity. BASDAI (0-10), spinal stiffness (3-12), functional limitation (0-54), and mental health using General Health Questionnaire GHQ-12 (0-12) were assessed. Mann-Whitney and Pearson’s χ2 tests were used to analyse relationships between engaging in physical activity and sociodemographic factors, patient-reported outcomes, employment, lifestyle and comorbidities. Univariable and multivariable binary logistic regression were used to analyse variables possibly explaining engagement in physical activity.

Results:

Mean age was 43.9±12.3 years, 61.3% were female, 48.1% had a university degree and 67.9% were married. 81.8% (n= 2,329) engaged in at least one kind of physical activity. Those physically active were typically male (85.3% vs 79.7% female, p<0.001), university educated (86.0% vs 78.0%, p<0.001), married (83.1% vs 79.2% unmarried, p=0.046), and members of a patient organisation (86.4% vs 78.9% non-member, p<0.001). 25.1% of obese patients (n=533) did not engage in physical exercise (v. 16.6% not obese, p<0.001). Those not engaging in physical activity reported greater disease activity (6.0 vs 5.4 BASDAI, p<0.001), functional limitation (21.6 vs 20.2, p=0.010), spinal stiffness (8.3 vs 7.6, p<0.001), and poorer mental health (5.9 vs 4.8 GHQ-12, p<0.001). Furthermore, 83.9% of those employed (n=1,457) were physically active, versus 73.7% unemployed (n=205; p<0.001). In the multivariable binary logistic regression, the qualitative variables associated with engaging in physical activity were belonging to a patient organisation (OR= 1.91), not being obese (OR= 1.58), being university educated (OR= 1.54), and being male (OR= 1.39). The quantitative variables associated with engaging in physical activity were lower spinal stiffness (OR=0.90), better mental health (OR=0.96), and one-year age increase (OR=1.02). (Table 1).

Table 1.

Regression analysis for variables explaining engagement in physical activity (n=2,424)

Univariable logistic analysisMultivariable logistic analysisQualitative variablesOR95% CI7OR95% CI7Gender. Male11.481.21, 1.811.391.06, 1.82Educational level. University21.731.42, 2.111.541.18, 2.00Marital Status. Married31.731.06, 1.581.180.91, 1.54Patient organization. Member41.71)1.39, 2.101.911.43, 2.55Body Mass Index. Not Obese51.691.35, 2.121.581.17, 2.13Employment status. Employed61.281.06, 1.561.000.76, 1.32Quantitative variablesOR95% CI7OR95% CI7Age1.011.00, 1.021.021.01, 1.03BASDAI (0-10)0.860.82, 0.910.960.89, 1.04GHQ-12 (0-12)0.940.92, 0.960.960.93, 0.99Functional Limitation (0-54)0.990.99, 1.001.000.99, 1.01Spinal Stiffness (3-12)0.900.86, 0.940.900.84, 0.95Proportion of life with axSpA (0-1)2.831.50, 5.352.000.91, 4.39

1Male vs Female; 2University vs no university; 3Married vs unmarried; 4Member vs not; 5Not obese (underweight, normal and overweight) vs obese; 6Employed vs not (unemployed, sick leave, retirement, housework and student).795% CI for test H0: OR=1

Conclusion:

These results show that increasing age, being male, university educated, member of a patient organisation, not obese, having lower spinal stiffness, and better mental health increase the probability of engaging in physical activity. Physical activity is an important part of axSpA care and patient organizations play a critical role in enhancing access to and participation in physical activity.

Acknowledgements:

This study was supported by Novartis Pharma AG. The authors would like to thank all patients who participated in the study.

Disclosure of Interests:

Marco Garrido-Cumbrera: None declared, Denis Poddubnyy Consultant of: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB., Grant/research support from: Abbvie, MSD, Novartis, and Pfizer, Christine Bundy Consultant of: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Laura Christen Employee of: Novartis Pharma AG, Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, David Gálvez-Ruiz: None declared, Pedro Plazuelo-Ramos: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB.

POS0989 FACTORS ASSOCIATED WITH INABILITY TO WORK AND DISABILITY IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)

Background:

Axial spondyloarthritis (axSpA) is associated with a high burden of disease, which may lead to inability to work and disability.

Objectives:

This analysis aims to identify factors associated with inability to work and disability among European axSpA patients.

Methods:

Data from 2,846 unselected patients participating in EMAS, a cross-sectional study (2017-2018) across 13 European countries were analysed. The sample was divided into those on permanent sick leave or with a recognised disability (Group 1) and those with neither permanent sick leave nor a recognized disability (Group 2). Mann-Whitney and Pearson’s χ2 tests were used to analyse possible differences between groups regarding sociodemographic characteristics, patient-reported outcomes [BASDAI (0-10), GHQ-12 (0-12), functional limitation (0-54) and spinal stiffness (3-12)], lifestyle habits, working life, and comorbidities). Univariable and multivariable binary logistic regression were used to analyse variables possibly explaining being on permanent sick leave and disability, for which 1,657 patients were included.

Results:

Mean age was 43.9 years, 61.3% were female, 48.1% had a university degree, and 67.9% were married. Patients in Group 1 (34.4%; n=978) were more likely to be women (54.3%), married (71.1%), with higher disease activity (BASDAI 5.9 vs. 5.3), functional limitation (25.1 vs. 18.0), spinal stiffness (8.6 vs. 7.3; all p<0.001), and longer diagnostic delay (8.1 vs 7.1 years; p = 0.01) than those in Group 2 (65.6%; n=1,868). In addition, 88.0% of Group 1 (n=728) had difficulties in finding a job due to axSpA throughout life; and more than 30.0% reported a diagnosis of anxiety, depression, or sleep disorders. Moreover, being in Group 1 was associated with higher functional limitation in all daily activities. In the multivariable binary logistic regression, the qualitative variables associated with permanent sick leave or disability were: difficulties finding work (OR= 2.52), belonging to a patient organisation (OR= 1.54) and work choice determined by axSpA (OR= 1.38). The quantitative variables associated with permanent sick leave or disability were: higher spinal stiffness (OR= 1.09), older age (OR= 1.03), longer disease duration (OR= 1.03), shorter diagnostic delay (OR= 0.98), and higher functional limitation (OR= 1.01) (Table 1).

Table 1.

Regression analysis for variables explaining being on permanent sick leave or disability (n=1,657)

Univariable logistic analysisMultivariable logistic analysisQualitative variablesOR95% CI3OR95% CI3Gender11.571.34, 1.831.240.97, 1.57Educational level21.711.46, 2.001.080.86, 1.35Member of a patient organisation. Yes1.961.67, 2.291.541.23, 1.94Smoking. Yes1.281.08, 1.511.220.96, 1.55Difficulty finding job due to axSpA. Yes3.712.89, 4.772.521.83, 3.47Work choice determined by axSpA. Yes1.691.43, 1.991.381.09, 1.75Anxiety diagnosis. Yes1.271.07, 1.510.980.72, 1.34Depression diagnosis. Yes1.581.33, 1.891.250.92, 1.69Sleep disorder diagnosis. Yes1.331.13, 1.560.950.73, 1.23Quantitative variablesOR95% CI3OR95% CI3Age. Years1.041.03, 1.041.031.01, 1.04BASDAI (0-10)1.181.13, 1.241.060.98, 1.13Functional limitation (0-54)1.031.02, 1.031.011.00, 1.02Spinal stiffness (3-12)1.251.20, 1.291.091.03, 1.15Diagnostic delay1.011.01, 1.020.980.96, 0.99Disease duration1.041.03, 1.051.031.01, 1.04

1Male vs Female; 2No university studies vs university studies. 395% CI for test H0: OR=1

Conclusion:

One third of patients reported being on permanent sick leave or having a recognised disability. They were more likely to have higher spinal stiffness scores, were older in age, experiencing difficulty finding a job, and belonged to a patient organisation. Increased efforts in relation to early access to effective treatments and the creation of flexible working environments are essential for axSpA patients to continue working and remain active, which benefits their quality of life.

Acknowledgements:

This study was supported by Novartis Pharma AG.The authors would like to thank all patients who participated in this study.

Disclosure of Interests:

Marco Garrido-Cumbrera: None declared, Christine Bundy Consultant of: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Laura Christen Employee of: Novartis Pharma AG, Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, David Gálvez-Ruiz: None declared, Pedro Plazuelo-Ramos: None declared, Denis Poddubnyy Consultant of: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Abbvie, MSD, Novartis, and Pfizer.

POS0296 DOSING OF BDMARDS IN AXSPA AND PSA IN A REAL WORLD SETTING

Background:

The treatment of patients with axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA) has been revolutionised by the introduction of biologic DMARDs targeting TNF, IL17, and IL23 inhibitors (i). In Germany, about 30-50% of axSpA and PsA patients receive treatment with bDMARDs. Although many patients benefit from these drugs, in some patients effectiveness of the standard dose may be insufficient and higher doses are used.

Objectives:

To describe dosing of TNFi and non-TNFi bDMARDs over a 2 year period in a real world cohort of patients with axSpA and PsA managed by rheumatologists.

Methods:

RABBIT-SpA is a prospective longitudinal cohort study including axSpA and PsA patients enrolled at the start of a new conventional treatment (including NSAID) or b/tsDMARD treatment. Description of dosing of TNFi (adalimumab bio-original (bo), adalimumab bio-similar (bs), etanercept bo, etanercept bs, golimumab, certolizumab) in comparison to nonTNFi-bDMARDs (secukinumab, ustekinumab, ixekizumab, guselkumab) in axSpA and PsA. Standard dosing was defined according to the current labels for axSpA and PsA.

Results:

1628 patients (axSpA: n=903, PsA: n=725) were included in this analysis. At inclusion mean age was 44 years in axSpA and 51 years in PsA. 44% of patients with axSpA and 58% of those with PsA were female. The mean disease duration of axSpA was 7.6 years, of PsA 6.4 years.

Standard doses of TNFi were used during a 2 year period in > 90% of patients with axSpA and PsA (Figure 1). In contrast, standard doses of non-TNFi-bDMARDs were only used in 70-80% of patients. The percentage of documented higher doses in patients with axSpA ranged from 20-30% at different time points. In PsA, this percentage increased from 27% at baseline to 44% at 2 years. On the other hand, TNFi were used in lower doses than the label in up to 9% and 7 % of patients with axSpA and PsA, respectively, after 2 years.

Figure 1.

Percentages of patients with axSpA or PsA who received less than, equal to, or more than the approved doses of bDMARDs at baseline and at 5 follow-up visits.

Conclusion:

While TNFi are used in licensed doses in most patients, non-TNFi-bDMARDs were often used in higher doses, which corresponds to higher doses approved in other indications like psoriasis. The effectiveness of this treatment strategy in axSpA and PsA needs to be analysed further.

Acknowledgements:

RABBIT-SpA is supported by a joint, unconditional grant from AbbVie, Amgen, Biogen, Hexal, Janssen-Cilag, Lilly, MSD, Novartis, Pfizer, UCB, and Viatris.

We thank all participating patients and rheumatologists.

Disclosure of Interests:

Anne Regierer Grant/research support from: AbbVie, Amgen, Biogen, Hexal, Janssen-Cilag, Lilly, MSD, Novartis, Pfizer, UCB, and Viatris., Anja Weiß Grant/research support from: AbbVie, Amgen, Biogen, Hexal, Janssen-Cilag, Lilly, MSD, Novartis, Pfizer, UCB, and Viatris., Denis Poddubnyy: None declared, Herbert Kellner: None declared, Frank Behrens: None declared, Georg Schett: None declared, Juergen Braun: None declared, Joachim Sieper: None declared, Anja Strangfeld Grant/research support from: AbbVie, Amgen, Biogen, Hexal, Janssen-Cilag, Lilly, MSD, Novartis, Pfizer, UCB, and Viatris

POS0453 VALIDATION OF THE SIMPLIFIED DISEASE ACTIVITY INDEX (SDAI) WITH A QUICK QUANTITATIVE C-REACTIVE PROTEIN ASSAY (SDAI-Q) IN PATIENTS WITH RHEUMATOID ARTHRITIS: A NATIONAL, MULTICENTER STUDY

Background:

Therapeutic decisions in RA patients should be based on regular disease activity assessment using scores like the Simplified Disease Activity Index (SDAI) or the Clinical Disease Activity Index (CDAI) [1]. The CDAI has the benefit of being immediately available, while the SDAI encompasses with the C-reactive protein (CRP) an acute phase reactant and therefore is the recommended score for the use in clinical trials. However, CRP determination takes hours to days, thus hindering the treat-to-target concept using the SDAI. Quick quantitative CRP (qCRP) tests allow CRP measurement within a few minutes. Therefore, qCRP based SDAI (SDAI-Q) could combine the advantages of both scores.

Objectives:

To validate the SDAI-Q in a prospective, multicenter study of RA patients.

Methods:

The study was conducted in five centers in Berlin, Germany. Consecutive adult (≥ 18 years) RA patients were included. In addition to a rheumatological assessment, including patient reported outcomes, routine CRP was measured in the local labs. Additionally, a qCRP testing with the „QuikRead go instrument“ (Aidian Oy, Finland) was performed locally (measurement range 0.5 - 200 mg/l). Statistical analysis included descriptive statistics, cross tabulation and weighted Cohen´s kappa comparing disease activity categories, Bland-Altman plots and intraclass correlation coefficient (ICC) for CRP, qCRP, SDAI, SDAI-Q and CDAI.

Results:

In this study 100 RA patients were included (mean age: 60.9 years, mean disease duration: 11.4 years, 73.0% were female, 63.0% RF positive, 57.0% ACPA positive, 49.0% positive and 29% negative for both parameters). 75.0% were treated with csDMARD, 15% with tsDMARDs, 39.0% with bDMARDs and 40% with glucocorticoids (mean prednisolone equivalent: 5.4 mg prednisolone/d). Mean CRP and qCRP-levels were 6.97 and 7.89 mg/l, respectively (ICC 0.992; 95%CI: 0.987; 0.995). Comparing SDAI-Q and SDAI, all patients (100%) achieved the same disease activity status (Table 1A); weighted Cohen´s kappa was 1.000 (95%CI: 1.000; 1.000). ICC for SDAI-Q- and SDAI-values was 1.000 (95%CI: 1.000; 1.000). The agreement of SDAI-Q and SDAI is shown in a Bland-Altman plot (Figure 1). When comparing the CDAI with the SDAI-Q 93 patients (93%) were assigned to the same disease activity category (Table 1B); weighted Cohen´s kappa was 0.929 (95%CI: 0.878; 0.981). ICC for numerical values of SDAI-Q and CDAI was 0.989 (95%CI: 0.978; 0.994).

Conclusion:

SDAI-Q showed an absolute agreement with SDAI on the assignment to disease activity categories with the important advantage of time. With SDAI-Q, rheumatologists could base their clinical decision-making immediately on an index-based disease activity measurement by using a composite score considering acute phase reactants. Consequently, SDAI-Q can be integrated in clinical routine and clinical trials and could be implemented into the treat-to-target concept in RA patients.

References:

[1]Smolen JS, et al. Ann Rheum Dis. 2016 Jan; 75(1):3-15.

Table 1.

A) Disease activity categories by SDAI-Q vs. SDAI; B) Disease activity categories by SDAI-Q vs. CDAI

ASDAI-Q (n = 100)Remission (≤ 3.3)Low Disease Activity (> 3.3 and ≤ 11)Moderate Disease Activity (> 11 and ≤ 26)High Disease Activity (> 26)SDAIRemission (≤ 3.3)28 (28.0%)Low Disease Activity (> 3.3 and ≤ 11)31 (31.0%)Moderate Disease Activity (> 11 and ≤ 26)35 (35.0%)High Disease Activity (> 26)6 (6.0%)BSDAI-Q (n = 100)Remission (≤ 3.3)Low Disease Activity (> 3.3 and ≤ 11)Moderate Disease Activity (> 11 and ≤ 26)High Disease Activity (> 26)CDAIRemission (≤ 2.8)26 (26.0%)Low Disease Activity (> 2.8 and ≤ 10)2 (2.0%)28 (28.0%)2 (2.0%)Moderate Disease Activity (> 10 and ≤ 22)3 (3.0%)33 (33.0%)High Disease Activity (> 22)6 (6.0%)

Fields highlighted in red indicate that disease activity categories do not match.

SDAI = Simplified Disease Activity Index;

SDAI-Q = SDAI calculated with a quick quantitative CRP assay;

CDAI = Clinical Disease Activity Index.

Figure 1.

Bland-Altman plot for SDAI and SDAI-Q Acknowledgements

The authors would like to deeply thank Braun T, Doerwald C, Deter N, Höppner C, Lackinger J, Lorenz C, Lunkwitz K, Mandt B, Sron S and Zernicke J for their practical support and coordinating the study.

Funding statement:

The AQUA study was supported by an unrestricted research grant from Novartis. Testing kits were provided free of charge from Aidian Oy, Finland.

Disclosure of Interests:

None declared

POS0923 INFLUENCE OF BASELINE DEMOGRAPHICS ON IMPROVEMENTS IN DISEASE ACTIVITY MEASURES IN PATIENTS WITH ANKYLOSING SPONDYLITIS RECEIVING UPADACITINIB: A POST HOC SUBGROUP ANALYSIS OF SELECT-AXIS 1

Background:

Upadacitinib (UPA), an oral Janus kinase inhibitor, has demonstrated efficacy and safety through 14 weeks in the SELECT-AXIS 1 study in biologic disease-modifying antirheumatic drug-naïve patients with active ankylosing spondylitis (AS).1

Objectives:

To evaluate the efficacy of UPA 15 mg once daily (QD) in selected subgroups of patients with AS based on different baseline characteristics.

Methods:

In SELECT-AXIS 1, patients were randomized to 14 weeks of blinded treatment with UPA 15 mg QD or placebo (PBO). This post hoc analysis evaluated the proportions of patients achieving ≥40% improvement in Assessment of SpondyloArthritis International Society criteria (ASAS40), ≥50% improvement in the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI50), and change from baseline in Ankylosing Spondylitis Disease Activity Score with C-reactive protein (ASDAS[CRP]) at Week 14 across subgroups based on the following baseline patient characteristics: gender, age, body mass index, AS symptom duration, C-reactive protein (CRP) levels, Spondyloarthritis Research Consortium of Canada Magnetic Resonance Imaging index, and human leukocyte antigen B27 status. For missing data, non-responder imputation analysis was used for ASAS40 and BASDAI50, and mixed model repeated measures analysis was used for ASDAS(CRP).

Results:

Baseline disease characteristics were balanced between the treatment groups at randomization, as previously reported.1 ASAS40 and BASDAI50 response rates at Week 14 were numerically higher with UPA 15 mg versus PBO across the demographic and disease characteristic subgroups evaluated (Figure 1), including some subgroups with small sample sizes, such as patients with disease duration <5 years and female patients. Improvements from baseline in ASDAS(CRP) were also consistently greater with UPA 15 mg versus PBO across the subgroups evaluated (Table 1).

Conclusion:

Within subgroups evaluated, most patients with active AS receiving UPA 15 mg demonstrated greater improvements versus PBO in disease activity measures assessed by ASAS40, BASDAI50, and change from baseline in ASDAS(CRP). There was some evidence that gender, AS symptom duration, and baseline CRP levels seemed to influence outcomes, though results should be interpreted with caution due to small sample sizes for some subgroups.

References:

[1]van der Heijde D, et al. Lancet 2019;394:2108–17.

Table 1.

PBO-corrected mean change from baseline (95% CI) in ASDAS(CRP) at Week 14 in patients receiving UPA 15 mg by baseline subgroups (MMRM)

nASDAS(CRP)SubgroupUPA15 mgPBOPBO-corrected mean change from baseline (95% CI)GenderMale5862–1.11 (–1.37, –0.84)Female2622–0.44 (–0.92, 0.03)Age<40 years2436–1.00 (–1.42, –0.58)40–<65 years5146–0.88 (–1.17, –0.59)Body mass index<25 kg/m23237–0.92 (–1.30, –0.55)≥25 kg/m25247–0.89 (–1.20, –0.59)AS symptom duration<5 years1617–0.90 (–1.46, –0.34)≥5 years6867–0.92 (–1.18, –0.66)Baseline hsCRP≤2.8 mg/L2319–0.59 (–1.02, –0.15)>2.8–<10 mg/L3934–0.59 (–0.95, –0.23)≥10 mg/L2231–1.64 (–2.01, –1.27)Inflammation based on SPARCC MRI scoresPositivea5657–0.98 (–1.27, –0.69)Negativeb2116–0.60 (–1.08, –0.12)HLA-B27 statusPositive6266–0.97 (–1.24, –0.71)Negative2017–0.73 (–1.28, –0.17)

aSpine SPARCC score ≥2 or sacroiliac joint SPARCC score ≥2. bSpine SPARCC score <2 and sacroiliac joint SPARCC score <2

ASDAS(CRP), Ankylosing Spondylitis Disease Activity Score with C-reactive protein; CI, confidence interval; HLA-B27, human leukocyte antigen B27; hsCRP, high-sensitivity C-reactive protein; MMRM, mixed model repeated measures; MRI, magnetic resonance imaging; PBO, placebo; SPARCC, Spondyloarthritis Research Consortium of Canada; UPA, upadacitinib

Acknowledgements:

AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and participated in the writing, review, and approval of the abstract. No honoraria or payments were made for authorship. Medical writing support was provided by Laura Chalmers, PhD, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests:

Filip van den Bosch Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Janssen, and UCB, Denis Poddubnyy Speakers bureau: AbbVie, Celgene, Eli Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Celgene, Eli Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Jayne Stigler Employee of: AbbVie employee and may own stock or options, Andrew Ostor Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Salvatore D’Angelo Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, and UCB, Victoria Navarro-Compán Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche, and UCB, In-Ho Song Employee of: AbbVie employee and may own stock or options, Tianming Gao Employee of: AbbVie employee and may own stock or options, Fabiana Ganz Employee of: AbbVie employee and may own stock or options, Lianne S. Gensler Consultant of: AbbVie, Eli Lilly, Gilead, GSK, Novartis, Pfizer, and UCB, Grant/research support from: Pfizer and UCB

AB0465 INDIVIDUAL COMPONENTS CONTRIBUTING TO THE ACHIEVEMENT OF ASAS40 RESPONSE IN BIOLOGIC NAÏVE PATIENTS WITH RADIOGRAPHIC axSpA: RESULTS FROM THE COAST-V TRIAL

Background:

Ixekizumab (IXE), an IL-17A antagonist, is effective in patients with radiographic axial spondyloarthritis (rad-axSpA). Assessment in SpondyloArthritis International Society (ASAS) 40 response – the primary study endpoint – was achieved at week (wk) 16 by 48% of those treated with 80mg subcutaneous IXE every 4 wks (Q4W) in the phase 3 COAST V trial (NCT 02696785) 1. Until now, no information has been available on the efficacy of IXE on the components of ASAS40 composite endpoint.

Objectives:

To describe which individual components of ASAS40 drive achievement of efficacy response.

Methods:

This exploratory post-hoc analysis was based on COAST V data. Patients enrolled in COAST V met ASAS criteria for rad-axSpA and were biological disease-modifying antirheumatic drug (bDMARD)-naïve. Patients were assigned 1:1:1:1 to subcutaneous placebo (PBO), IXE Q4W, IXE Q2W or 40 mg adalimumab (ADA). Only data for approved doses are shown.

To reach ASAS40 response, patients must have an improvement of at least 40% and at least 2 units for at least 3 of 4 individual components which define response (patient global assessment of disease activity, spinal pain, inflammation (defined as the mean of Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) questions 5 and 6), and function (Bath Ankylosing Spondylitis Functional Index - BASFI)), without worsening in the remaining component. We describe the percentage of patients who achieved this change, had an insufficient response, or deteriorated in each component out to wk 16 for IXE Q4W, ADA and PBO. The time course of the change from baseline in individual components of the ASAS response is depicted descriptively per treatment arm by use of the mean and standard deviation. Observed data have been utilised.

Results:

IXE Q4W response at 16 wks was driven by all 4 individual components of the ASAS40 with the largest improvements for patients treated with IXE Q4W seen in inflammation and spinal pain (Figure 1).

At wk 16, at least 50% of all patients treated with IXE Q4W achieved response on spinal pain (60.3%), inflammation (60.3%) and patient global assessment (50%), with 43.6% of patients meeting the response criteria for function (Table 1). The corresponding results for ADA were 43.2%, 47.7% 39.8%, and 35.2%.

Conclusion:

Our findings show that meeting ASAS40 response criterion for an individual component at 16 wks by patients treated with IXE Q4W was broadly similar between individual components. However, a clinically relevant improvement was more frequently observed for the spinal pain and inflammation components.

References:

[1]Dougados, M., et al. (2020). Ann Rheum Dis79(2): 176-185.

Table 1.

Observed changes from baseline (CFB), percentage improvements and response status of patients enrolled in COAST V trial at wk 16

MeasureObserved CFB(SD)Observed % improvement (SD)Improvement >=40% and >=2 unitsn (%)Insufficient responsen (%)Deterioratedn (%)IXE Q4W (N=78) Patient global assessment-2.6 (2.9)32.3 (51.1)39 (50.0)30 (38.5)9 (11.5) Spinal pain-3.3 (2.7)43.4 (34.4)47 (60.3)27 (34.6) 4 (5.1) Inflammation*-3.2 (2.5)46.8 (32.8)47 (60.3)25 (32.0)6 (7.7) Function-2.5 (2.3)39.6 (31.0)34 (43.6)37 (47.4)7 (9.0)ADA (N=88) Patient global assessment-2.6 (2.4)35.2 (33.4)35 (39.8)48 (54.5)5 (5.7) Spinal pain-2.6 (2.4)36.8 (34.7)38 (43.2)44 (50.0)6 (6.8) Inflammation*-2.6 (2.4)38.4 (36.9)42 (47.7)37 (42.0)9 (10.2)Function-2.1 (2.2)35.2 (34.3)31 (35.2)48 (54.6)9 (10.2)PBO (N=86) Patient global assessment-1.5 (2.0)18.0 (37.9)21 (24.4)54(62.8)11(12.8) Spinal pain-1.9 (1.9)25.8 (26.7)23 (26.8)55(64.0)8(9.3) Inflammation*-1.4 (1.9)20.9 (33.9)19 (22.1)53 (61.6)14 (16.3) Function-1.3 (1.8)19.1 (31.6)16 (18.6)51 (59.3)19 (22.1)

*Inflammation is the mean of BASDAI 5 (Morning stiffness severity) and BASDAI 6 (Morning stiffness duration)

Mean baseline values for PBO, ADA and IXE Q4W respectively: Patient global assessment (7.1, 7.1, 6.9), spinal pain (7.4, 7.0, 7.2), inflammation (Q5/6) (6.7, 6.6, 6.5), function (6.3, 6.1, 6.1)

Acknowledgements:

Alan Ó Céilleachair, an employee of Eli Lilly and Company, provided editorial and writing support.

Disclosure of Interests:

Denis Poddubnyy Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly and Company, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Biocad, Gilead, GlaxoSmithKline, Eli Lilly and Company, MSD, Novartis, Pfizer, Samsung Bioepis, and UCB, Grant/research support from: AbbVie, Eli Lilly and Company, MSD, Novartis, and Pfizer, Suzan Attar: None declared., Michael J. Nissen Speakers bureau: AbbVie, Celgene, Eli Lilly and Company, Janssen, Novartis and Pfizer., Consultant of: AbbVie, Celgene, Eli Lilly and Company, Janssen, Novartis and Pfizer., Grant/research support from: AbbVie, Erica Filippi Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Hagen Russ Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Alper Erdogan Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Yves Schymura Employee of: Eli Lilly and Company, Soyi Liu Leage Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Eduardo Collantes Estevez Speakers bureau: Novartis, Janssen, Eli Lilly and Company, AbbVie, Paid instructor for: Novartis, Grant/research support from: Eli Lilly and Company, francesco ciccia Speakers bureau: AbbVie, Celgene, UCB, Pfizer, MSD, Amgen, Eli Lilly and Company, Novartis, Sobi, Roche, BMS, Paid instructor for: Novartis, UCB, Pfizer, Consultant of: Novartis, UCB, Pfizer, Grant/research support from: Pfizer, Roche, UCB.

POS1002 BASELINE CALPROTECTIN AND VISFATIN LEVELS PREDICT RADIOGRAPHIC SPINAL PROGRESSION AFTER 2 YEARS IN ANKYLOSING SPONDYLITIS PATIENTS ON TNF INHIBITOR THERAPY

Background:

Radiographic spinal progression determinates functional status and mobility in ankylosing spondylitis (AS)1.

Objectives:

To analyse whether biomarker of inflammation, bone turnover and adipokines at baseline or their change after 3 months or 2 years can predict spinal radiographic progression after 2 years in AS patients treated with TNF-α inhibitors (TNFi).

Methods:

Consecutive AS patients from the Groningen Leeuwarden Axial Spondyloarthritis (GLAS) cohort2 starting TNFi between 2004 and 2012 were included. The following serum biomarkers were measured at baseline, 3 months and 2 years of follow-up with ELISA:

 - Markers of inflammation: calprotectin, matrix metalloproteinase-3 (MMP-3), vascular endothelial growth factor (VEGF)

 - Markers of bone turnover: bone-specific alkaline phosphatase (BALP), serum C-terminal telopeptide (sCTX), osteocalcin (OC), osteoprotegerin (OPG), procollagen typ I and II N-terminal propeptide (PINP; PIINP), sclerostin.

 - Adipokines: high molecular weight (HMW) adiponectin, leptin, visfatin

Two independent readers assessed spinal radiographs at baseline and 2 years of follow-up according to the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). Radiographic spinal progression was defined as mSASSS change ≥2 units or the formation of ≥1 new syndesmophyte over 2 years. Logistic regression was performed to examine the association between biomarker values at baseline, their change after 3 months and 2 years and radiographic spinal progression. Multivariable models for each biomarker were adjusted for mSASSS or syndesmophytes at baseline, elevated CRP (≥5mg/l), smoking status, male gender, symptom duration, BMI, and baseline biomarker level (the latter only in models with biomarker change).

Results:

Of the 137 included AS patients, 72% were male, 79% HLAB27+; mean age at baseline was 42 years (SD 10.8), ASDAScrp 3.8 (0.8) and mSASSS 10.6 (16.1). After 2 years of follow-up, 33% showed mSASSS change ≥2 units and 24% had developed ≥1 new syndesmophyte. Serum levels of biomarkers of inflammation and bone formation showed significant changes under TNFi therapy, whereas adipokine levels were not altered from baseline (Figure 1).

Univariable logistic regression revealed a significant association of baseline visfatin (odds ratio OR [95% confidence interval] 1.106 [1.007-1.215]) and sclerostin serum levels (OR 1.006 [1.001-1.011]) with mSASSS progression after 2 years. Baseline sclerostin levels were also associated with syndesmophyte progression (OR 1.007 [1.001-1.013]). In multivariable logistic analysis, only baseline visfatin level remained significantly associated (OR 1.465 [1.137-1.889]) with mSASSS progression. Furthermore, baseline calprotectin showed a positive association with both, mSASSS (OR 1.195 [1.055-1.355]) and syndesmophyte progression (OR 1.107 [1.001-1.225]) when adjusting for known risk factors for radiographic progression.

Univariable logistic regression showed that change of sclerostin after 3 months was associated with syndesmophytes progression (OR 1.007 [1.000-1.015), change of PINP level after 2 years was associated with mSASSS progression (OR 1.027 [1.003-1.052]) and change of visfatin after 2 years was associated with both measures of radiographic progression – mSASSS (OR 1.108 [1.004-1.224]) and syndesmophyte formation (OR 1.115; [1.002-1.24]). However, those associations were lost in multivariable analysis.

Conclusion:

Independent of known risk factors, baseline calprotectin and visfatin levels were associated with radiographic spinal progression after 2 years of TNFi. Although biomarkers of inflammation and bone formation showed significant changes under TNFi therapy, these changes were not significantly related to radiographic spinal progression in our cohort of AS patients.

References:

[1]Poddubnyy et al 2018

[2]Maas et al 2019

Acknowledgements:

Dr. Judith Rademacher is participant in the BIH-Charité Clinician Scientist Program funded by the Charité –Universitätsmedizin Berlin and the Berlin Institute of Health.

Disclosure of Interests:

Judith Rademacher: None declared, Mark Siderius: None declared, Laura Gellert: None declared, Freke Wink Consultant of: AbbVie, Maryna Verba: None declared, Fiona Maas: None declared, Lorraine M Tietz: None declared, Denis Poddubnyy: None declared, Anneke Spoorenberg Consultant of: Abbvie, Pfizer, MSD, UCB, Lilly and Novartis, Grant/research support from: Abbvie, Pfizer, UCB, Novartis, Suzanne Arends Grant/research support from: Pfizer.

POS1045 Ixekizumab efficacy on spinal pain, disease activity and quality of life in patients with psoriatic arthritis presenting with symptoms suggestive of axial involvement

Background:

Many patients with psoriatic arthritis (PsA) experience back pain and stiffness, which may suggest axial involvement [1]. The prevalence of axial involvement in PsA varies between 25-70% [2]. Ixekizumab (IXE), a monoclonal antibody with high affinity for IL17-A, has been studied in Phase 3 trials in patients with PsA (SPIRIT-P1 [Biologic-naïve; NCT01695239] and SPIRIT-P2 [Inadequate response or intolerant to 1 or 2 TNF inhibitors (TNFi); NCT02349295]) [3] [4].

Objectives:

To determine the efficacy of IXE up to 52 weeks (Wks) in reducing axial symptoms in patients with active PsA presenting with symptoms suggestive of axial involvement.

Methods:

This post-hoc analysis included data from two subpopulations of patients with PsA (pooled SPIRIT-P1 and -P2). Symptoms suggestive of axial involvement were defined as Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) Q2 (back pain) ≥4, and an average of Q5 + Q6 (intensity and duration of morning stiffness in the spine) ≥4 at baseline. Patients included in the sensitivity analysis subgroup 1 were, in addition to the above-mentioned overall analysis criteria, <45 years of age, while patients included in sensitivity analysis subgroup 2 were aged <45 but also had elevated C-reactive protein (CRP) (> 5 mg/l) at baseline. Efficacy of IXE was analysed using BASDAI questions, total BASDAI, mBASDAI (without Q3), and Ankylosing Spondylitis Disease Activity Score (ASDAS) change from baseline, as well as BASDAI50 response and Short-Form-36 physical component summary (SF-36 PCS) improvement, at Wks 16, 24 and 52. Treatment comparison was done using logistic regression for BASDAI50, and analysis of covariance (ANCOVA) model for other endpoints. Missing data for binary and continuous endpoints were imputed by non-responder imputation and modified baseline observation carried forward (mBOCF), respectively.

Results:

A total of 313 patients (placebo (PBO), N=151; IXE Q4W, N=162) met the overall analysis inclusion criteria. Baseline values for BASDAI and ASDAS related endpoints were balanced across treatment arms (Table 1). Improvement in axial symptoms were significantly greater in patients treated with IXE compared to PBO at Wks 16 and 24 (Figure 1. next page) Improvement in quality of life (QoL) measures (SF-36 PCS) were also significantly greater in patients treated with IXE compared to PBO at Wks 16 and 24 (Table 1). Similar results were observed for patients < 45 years, and in patients < 45 years with CRP > 5 mg/l at baseline (sensitivity analysis, data not shown).

Table 1.

Baseline values and change from baseline (mBOCF) in the overall analysis population at Wks 16, 24 and 52 for BASDAI and ASDAS related endpoints in patients with PsA and axial pain. Data presented as mean (SD) unless otherwise specified. ‡p<0.001 vs PBO.

Conclusion:

IXE is effective in reducing axial symptoms and improving QoL in patients with active PsA presenting with symptoms suggestive of axial involvement.

References:

[1]Yap KS. Ann Rheum Dis. 2018;77(11)

[2]Feld J. Nat Rev Rheumatol. 2018;14

[3]Orbai A. Clin Exp Rheumatol. 2020[online]

[4]Genovese MC. Rheumatol. 2018;57(11)

Figure 1.

Change from baseline (mBOCF) in BASDAI and ASDAS related endpoints in patients with PsA and axial pain in the overall analysis population. Data presented as mean (SD). ‡p<0.001 vs PBO.

Acknowledgements:

Edel Hughes, an employee of Eli Lilly and Company, provided editorial and writing support.

Disclosure of Interests:

Atul Deodhar Speakers bureau: Janssen, Novartis, Pfizer, Paid instructor for: Boeheringer Ingelheim, Pfizer, Consultant of: AbbVie, Amgen, Boeheringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Galapagos, Glaxo Smith Kline, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Eli Lilly, Glaxo Smith Kline, Novartis, Pfizer, UCB, Dafna D Gladman Consultant of: Abbvie, Amgen, BMS, Galapagos, Gilead, Eli Lilly, Janssen, Novartis, Pfizer, UCB, Grant/research support from: Abbvie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, UCB, Rebecca Bolce Shareholder of: Employee and shareholder of Eli Lilly and Company, Employee of: Employee and shareholder of Eli Lilly and Company, David Sandoval Shareholder of: Eli Lilly and Company, Employee of: Currently employed by Eli Lilly and Company, So Young Park Shareholder of: Eli Lilly & Company, Employee of: Eli Lilly & Company, Soyi Liu Leage Shareholder of: Owns Lilly shares (company producing drug/devices for use in rheumatology), Employee of: Employee of Eli Lilly and Company, Peter Nash Speakers bureau: Honoraria for lectures on behalf Abbvie, BMS, Celgene, Roche, Sanofi, Lilly, Novartis, Janssen, Pfizer, Boehringer, Samsung, Consultant of: Advice on behalf Abbvie, BMS, Celgene, Roche, Sanofi, Lilly, Novartis, Janssen, Pfizer, Boehringer, Samsung, Grant/research support from: Research funding for clinical trials on behalf Abbvie, BMS, Celgene, Roche, Sanofi, Lilly, Novartis, Janssen, Pfizer, Boehringer, Samsung, Denis Poddubnyy Speakers bureau: AbbVie, Bristol-Myers Squibb, Lilly, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Biocad, Gilead, GlaxoSmithKline, Eli Lilly, MSD, Novartis, Pfizer, Samsung Bioepis, and UCB, Grant/research support from: AbbVie, Eli Lilly, MSD, Novartis, and Pfizer.

OP0031 SHARED AND DISTINCT GUT MICROBIOME SIGNATURES IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS AND ITS RELATED IMMUNE-MEDIATED DISEASES

Background:

Immune-mediated diseases such as spondyloarthritis (SpA) consistently coincide with dysbiosis of the gut microbiota and frequently present with additional inflammatory pathologies such as Crohn’s disease (CD) and acute anterior uveitis (AAU). Deep profiling of gut microbiota may reveal new pathways of how SpA and its related diseases are initiated and perpetuated.

Objectives:

To identify the presence of shared and specific gut microbiota signatures for SpA and its related diseases as a whole, as well as for the individual diseases, relative to healthy controls.

Methods:

Patients were recruited with a definite diagnosis of axial SpA, AAU or CD and were compared to controls (patients with back pain and previously ruled out SpA/CD/AAU diagnosis). All patients were naïve to or did not receive treatment with biological disease-modifying antirheumatic drugs for at least 3 months before enrollment of the study. Fecal samples were collected and microbiota composition was determined by 16S rRNA gene sequencing, followed by computational analysis referencing the SILVA138 database. Nonparametric Wilcoxon tests were used to calculate differential abundances between binary groups, and the Spearman correlation was used with continuous covariates. Nested linear models and likelihood ratio tests were used to assess confounding with respect to patient characteristics, HLA-B27 expression, inflammatory markers, and the presence of other immune-mediated diseases.

Results:

A total of 300 patients were recruited for the study: 111 axial SpA, 110 AAU, and 79 CD patients and were compared to 63 control individuals. Fifty-three of patients were males with an age (mean±SD) of 39.1±12.3 years. The prevalence of HLA-B27 was 63.0% by patients compared to 7.9% by control individuals. A multivariate PERMANOVA test between the groups was significant (p<0.001), revealing a difference in overall composition between the groups.

At the phylum level, patients with axial SpA, AAU and CD contained higher abundances of Proteobacteria, Bacteroidetes and Fusobacteria, and lower abundances of Firmicutes and Actinobacteria compared to the control group. At the genus level, patients (with axial SpA, AAU and CD) displayed a shared gut microbiome signature differing from that of control individuals. Patients samples were strongly depleted in Blautia compared to the control group. Many of the differentially abundant taxa also correlated with increased inflammation as measured by C-reactive protein (CRP), including a depletion of Fusicatenibacter, Lachnospiraceae FCS020 and Roseburia, as well as an enrichment of Lactobacillus and Veillonella. By looking at each separate disease phenotype, CD patients differed significantly from the control individuals with respect to many genera. These primarily consisted of depletions in Clostridiales (Roseburia, Coprococcus, Ruminococcaceae), and enrichments of pathogen-harboring genera such as Escherichia-Shigella and Fusobacterium. Axial SpA patients were uniquely enriched in Collinsella and Holdemanella and depleted in Cupriavidus; the enrichment of Lactobacillus and depletion of Blautia observed in all patient groups was also associated to the presence of axial SpA, though confounded by CRP. There were strong taxa associations to the presence of HLA-B27, including enrichment of Asteroleplasma, Coprococcus, Faecalibacterium, Rominococcaceae, Lachnospiraceae NK4A136 and Rikenellaceae.

Conclusion:

There is a robust shared taxonomic signature among related immune-mediated diseases, in addition to individual disease phenotype signatures. Patients frequently exhibited a strong depletion in Blautia and an enrichment in Lactobacillus as well as pathogen-harboring genera such as Escherichia-Shigella and Fusobacterium.

Figure 1.

Taxa associations within and between the groups resulting from comparing each with the control group and accounting for disease concomitance and patient characteristics (FDR ≤ 0.05). AAU, anterior acute uveitis; CD, Crohn’s disease; SpA, spondyloarthritis.

Disclosure of Interests:

None declared

POS0065-PARE HEALTH IMPACT OF OVERWEIGHT AND OBESITY IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)

Background:

Growing evidence on the negative role of overweight and obesity on the health outcomes of patients with axial spondyloarthritis (axSpA) exists.

Objectives:

The aim of the study is to evaluate the association between Body Mass Index (BMI) categories and sociodemographic, disease-characteristics and patient-reported outcomes (PROs) in a large sample of axSpA patients.

Methods:

Data from 2,846 unselected patients of the European Map of Axial Spondyloarthritis (EMAS) through an online survey (2017-2018) across 13 European countries were analyzed. Using self-reported height and weight patients were classified into under and normal weight (<24.9 Kg/m2), overweight (25.0-29.9Kg/m2) or obese (>30.0Kg/m2) following WHO guidelines. The Kruskal-Wallis test was used to compare the means of numerical variables between polytomous variables, the χ2 test was used to compare the distribution between the categorical variables. Simple and multivariate logistic regression were used to identify possible associated factors.

Results:

A total 2,846 axSpA patients participated in the EMAS survey: mean age was 43.9 years, 61.3% female, 48.1% had a university degree and 67.9% were married and 71.3% were HLA-B27 positive. The percentage of patients with obesity was 18.7%, overweight 33.5%, normal weight 44.0% and underweight 3.8% with an accumulate prevalence of overweight/obesity of 52.2% (compared to 51.6 % of the EU’s population1). Those with obesity engage less frequently in sport (50.1% vs 33.3%; p<0.001) and in intimate relationships since disease onset (36.5% vs 20.4%; p<0.001), have higher functional limitations when tying shoe laces (46.8% vs 33.6%; p<0.001) and higher functional limitations regarding housework (52.2% vs 48.2%; p=0.024). Furthermore, they present greater disease activity (6.1±1.8 vs 5.4±2.0; p<0.001) and spinal stiffness (8.6±2.3 vs 7.4±2.5; p<0.001) compared to under and normal weight. For obese patients, the percentage of depression is higher (34.5% vs 23.7%; p<0.001), presenting a poorer mental health (5.7 ± 4.3 vs 5.0 ±4.2; p<0.001). The factors most strongly associated with obesity were higher functional limitation when tying shoe laces (OR=1.467; p<0.001), the female gender (OR=1.433; p<0.001) and lesser frequency of intimate relation (OR=1.239; p<0.001; see Table 1).

Table 1.

Logistic regression analysis to predict presence of obesity (N = 1,194)

SimpleMultivariateOR95% CIp-valueOR95% CIp-valueAge1.0261.018, 1.034<0.0011.0261.012, 1.040<0.001Gender (female)1.3361.095, 1.6290.0041.4331.031, 1.9900.032Marital status (married)1.3841.184, 1.617<0.0010.9820.746, 1.2920.897Educational level (university)0.7760.681, 0.884<0.0011.0460.849,1.2890.674Employment status (employed)1.0350.987, 1.0850.154NANANAEngage in sports (much less than before)1.3131.202, 1.433<0.0011.1430.978, 1.3360.093Travel/ excursions (much less than before)1.3161.186, 1.461<0.0010.9810.800, 1.2020.852Intimate relations (much less than before)1.5711.393, 1.772<0.0011.2391.003, 1.5300.047Tying shoe laces (high)1.4331.232, 1.666<0.0011.4671.176, 1.8300.001Housework / cleaning (high)1.2261.048, 1.4340.0110.7600.596, 0.9700.028BASDAI (0-10) N:2,5841.2201.156, 1.288<0.0011.1271.021, 1.2440.018Spinal Stiffness (3-12) N:2,6601.1841.136, 1.234<0.0011.0570.987, 1.1330.115Sleep disorders diagnosis1.5581.284, 1.892<0.0011.0450.753, 1.4490.793Depression diagnosis1.6481.340, 2.027<0.0011.2670.892, 1.7990.186Psychological distress GHQ-12 (0-12)1.0531.029, 1.078<0.0010.9950.954, 1.0380.813

Conclusion:

Results from the largest European axSpA survey reveal a similar prevalence of overweight and obesity to the general population. However, compared to normal weight, obese patients present greater disease activity, spinal stiffness and poorer mental health. Additionally, women with axSpA appear to be more vulnerable than men to obesity.

References:

[1]EU Eurostat. Overweight and obesity - BMI statistics.

Acknowledgements:

This study was supported by Novartis Pharma AG. The authors would like to thank all patients who participated in the study.

Disclosure of Interests:

Marco Garrido-Cumbrera: None declared, Denis Poddubnyy Speakers bureau: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Abbvie, MSD, Novartis, and Pfizer, Laura Christen Employee of: Novartis Pharma AG, Christine Bundy Speakers bureau: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Raj Mahapatra: None declared, Souzi Makri: None declared, Sergio Sanz-Gómez: None declared, José Correa-Fernández: None declared, Carlos Jesús Delgado-Domínguez: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB.

POS0961 PREVALENCE AND ASSOCIATED FACTORS OF SLEEP DISORDERS IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)

Background:

Sleep is an essential health aspect that is often impacted in patients with axial spondyloarthritis (axSpA).

Objectives:

This analysis aims to assess the prevalence and associated factors of sleep disorders in a large sample of European axSpA patients.

Methods:

Data were analyzed from 2,846 unselected patients with self-reported clinician-given diagnosis of axSpA of the European Map of Axial Spondyloarthritis (EMAS) through an online survey (2017-2018) across 13 European countries. Socio-demographic data; BASDAI [0-10] scores; engagement in physical activity; axSpA influence on work choice (assessed with yes/no question “Was your current or past work choice in any way determined by axSpA?”); risk of psychological distress (12-item General Health Questionnaire [GHQ-12; 0-12]); functional limitation [0-54] and self-reported anxiety and depression were evaluated. Presence of sleep disorders was assessed by the question: “Please indicate whether you have been diagnosed with any of the following: sleep disorders”. A Mann-Whitney test was used to compare the means of numerical variables between dichotomous variables, the Chi-Square test was used to compare the distribution between the categorical variables. Simple and multivariable logistic regression models were used to identify associations between sleep disorders and disease characteristics, mental health and work-related variables.

Results:

Age of respondents was 43.9 years; 61.3% were female; 48.1% had a university degree; 67.9% were married and 71.3% were HLA-B27 positive. The prevalence of sleep disorders was 39.0%. In the bivariate analysis, presence of sleep disorders was associated with female gender (68.3% vs. 31.7%; p<0.001); overweight/obese (56.5% vs. 49.8%; p<0.001); increased BASDAI scores (6.1±1.8 vs. 5.0±2.1; p<0.001); fatigue (7.0±2.0 vs. 5.8±2.4; p<0.001); morning stiffness (5.8±2.4 vs. 4.8±2.4; p<0.001), work impact (56.5% vs. 38.2%; p< 0.001); anxiety (56.8% vs. 12.5%; p<0.001); depression (51.8% vs. 10.1%; p<0.001) and higher GHQ-12 scores (6.4±4.0 vs. 3.9±3.9; p<0.001). However, factors that remained independently associated with sleep disorders in the multivariable analysis were anxiety (OR=3.8 p<0.001) and depression (OR=3.1 p<0.001) and female gender (OR=1.4; p=0.002) [Table 1].

Table 1.

Regression analysis to predict presence of sleep disorders (N=2191)

Simple logistic regressionMultivariable logistic regressionOR95% CIp-valueOR95% CIp-valueGender (female)1.591.36-1.87<0.0011.401.13-1.730.002Marital status (married)1.130.99-1.280.074NANANAOverweight/Obesity1.311.12-1.530.0011.391.14-1.710.001BASDAI (0-10)1.331.27-1.39<0.0011.070.95-1.210.246Fatigue/Tiredness (0-10)*1.281.23-1.33<0.0011.040.97-1.120.271Morning Stiffness intensity (0-10)*1.191.15-1.23<0.0011.050.98-1.130.188Reported Work impact (yes)2.101.78-2.48<0.0011.291.05-1.580.015Anxiety (yes)9.187.58-11.11<0.0013.842.99-4.94<0.001Depression (yes)9.537.78-11.66<0.0013.092.37-4.02<0.001GHQ-12 (0-12)**1.161.14-1.19<0.0011.031.00-1.060.029

*As measured by the respective item of the BASDAI scale.

**12-item General Health Questionnaire. A value of 3 or above indicates a risk of poor mental health.

Conclusion:

Sleep disorders were highly prevalent among axSpA European patients and strongly associated with female gender and reporting worse mental health, and spinal stiffness. Patients on permanent and temporary sick leave were more likely to report sleep disorders. The strong association between sleep disorders with both anxiety and depression should encourage rheumatologists to screen their patients with sleep disturbance in case they require additional specialist support.

Acknowledgements:

This study was supported by Novartis Pharma AG. The authors would like to thank all patients who participated in the study.

Disclosure of Interests:

Marco Garrido-Cumbrera: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB., Laura Christen Employee of: Novartis Pharma AG, Christine Bundy Speakers bureau: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, José Correa-Fernández: None declared, Denis Poddubnyy Speakers bureau: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Abbvie, MSD, Novartis, and Pfizer.

POS0969 UNVEILING AXIAL INVOLVEMENT IN PSORIATIC ARTHRITIS: AN ANCILLARY ANALYSIS OF THE ASAS-perSpA STUDY

Background:

Heterogeneity in psoriatic arthritis (PsA) is a current matter of discussion, especially concerning axial involvement.

Objectives:

To determine the profile of axial PsA (axPsA) in a worldwide setting. Secondly, to identify predictive factors associated with the development of axial involvement in patients with PsA.

Methods:

Data from 3684 patients with axial spondyloarthritis (axSpA) or PsA from the ASAS-PerSpA study were analysed. The ASAS-PerSpA is an observational, cross-sectional study that recruited consecutive patients with SpA from 68 centers worldwide. For this analysis, 367 PsA patients ever presenting axial involvement according to their rheumatologist were defined as axPsA and compared with 2651 axSpA patients, using logistic regression to later identify predictive factors for rheumatologist diagnosis of axPsA. In addition, the axPsA patients were also compared with 666 PsA patients without axial involvement (pPsA) and the characteristics associated with axial manifestations were determined by logistic regression analysis.

Results:

Among all patients, 2651 were identified as axSpA and 1033 patients as PsA. Among those with axial involvement, 2651 were identified as axSpA (100% of axSpA) and 367 as axPsA (35.5 % of PsA). In comparison with axSpA, axPsA patients were less frequently males, older, less frequently HLA-B27 positive and had a higher body mass index (Table 1). Additionally, while patients with axPsA had more peripheral manifestations and psoriasis, concomitant IBD and uveitis were higher in axSpA. In the multivariable analysis, older age at diagnosis (OR= 1.04), peripheral arthritis (OR= 7.32) and dactylitis (OR= 2.82) were significantly associated with a diagnosis of axPsA. However, uveitis (OR= 0.22), IBD (OR= 0.12) or HLA*B27 carriership (OR= 0.26) were inversely associated with axPsA diagnosis as compared to axSpA. Furthermore, axial involvement in patients with PsA was significantly associated with male gender (OR= 1.68), elevated CRP (OR= 2.87), and the absence of psoriasis (OR= 0.33).

Conclusion:

In this worldwide setting, axPsA was defined by rheumatologists as a unique phenotype, with disease features lying between axSpA and pure pPsA. Male gender, elevated CRP and the absence of psoriasis were associated with axial involvement in patients with PsA.

Table 1.

Demographic and disease characteristics of patients with axial involvement included in the ASAS PerSpA study. Results shown as absolute numbers (percentages) or as the mean ± standard deviation

axSpAn= 2651axPsAn= 367p-valueSex (male)1816 (68.5) 196 (53.4)<0.001Age at study visit42.1(13.0)50.0 (12.7)<0.001Body Mass Index25.9 (5.1)27.4 (5.7)<0.001Family history of SpA944 (35.6)135 (36.8)0.684Past history or current symptoms of back pain2625 (99.0)358 (97.5)0.04Inflammatory back pain (ASAS definition), n/N(%)2500/2632 (94.9)317/362 (87.6)<0.001Sacroiliitis on imaging, n/N (%) by: xRay mNY criteria1997/2586 (77.2)185/298 (62.1)<0.001 MRI-SIJ, ASAS definition1449/1757 (82.4)141/225 (62.6)<0.001 mNY criteria or ASAS definition2446/2634 (92.9)243/339 (71.7)<0.001HLA B27 positive1674 /2126 (78.7)54/182 (29.6)<0.001Elevated CRP (>5 mg/dL)1863/2569 (72.5)274/356 (76.9)0.2Classification criteria ASAS criteria2339 (88.2)185 (50.4)<0.001 CASPAR criteria123 (4.6)274 (74.4)<0.001Peripheral Arthritis946 (35.7)318 (86.6)<0.001Enthesitis1086 (41.0)198 (54.0)<0.001Dactylitis155 (5.8)125 (34.1)<0.001Psoriasis185 (7.0)324 (88.3)<0.001IBD129 (4.9)3 (0.8)<0.001Uveitis576(21.7)13 (3.5)<0.001csDMARD (ever)1359 (51.3)339 (92.4)<0.001bDMARD (ever)1585 (59.8)263 (71.7)<0.001Specific drug for axial involvementNSAIDs2465 (98.6)317 (96.1)0.002csDMARD828 (33.1)187 (56.7)<0.001bDMARD1288 (51.5)180 (54.4)0.32

axSpA: axial spondyloarthritis; axPsA: axial psoriatic arthritis; IBD: Inflammatory Bowel Disease; CRP: C-Reactive Protein; mNY: modified New York; csDMARDs: conventional synthetic DMARDs; bDMARDs: biological DMARDs; NSAID: Non-steroidal anti-inflammatory drugs

Disclosure of Interests:

Diego Benavent: None declared, Chamaida Plasencia: None declared, Denis Poddubnyy: None declared, Mitsumasa Kishimoto Consultant of: AbbVie, Amgen-Astellas BioPharma, Asahi-Kasei Pharma, Astellas, Ayumi Pharma, BMS, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Janssen, Kyowa Kirin, Novartis, Ono Pharma, Pfizer, Tanabe-Mitsubishi, Teijin Pharma, and UCB Pharma., Fabian Proft Grant/research support from: AbbVie, AMGEN, BMS, Celgene, MSD, Novartis, Pfizer, Roche, UCB, Haruki Sawada: None declared, Clementina López-Medina: None declared, Maxime Dougados: None declared, Victoria Navarro-Compán: None declared.

POS1069 VALIDATION OF THE DISEASE ACTIVITY INDEX FOR PSORIATIC ARTHRITIS (DAPSA) WITH A QUICK QUANTITATIVE C-REACTIVE PROTEIN ASSAY (Q-DAPSA) IN PATIENTS WITH PSORIATIC ARTHRITIS (PSA): A PROSPECTIVE, NATIONAL, MULTICENTER STUDY

Background:

Psoriatic arthritis (PsA) is a heterogeneous disease with multiple musculoskeletal and dermatological manifestations. Due to this multifaceted clinical appearance, international guidelines do not provide a clear recommendation for one specific score to assess disease activity in PsA [1]. The Disease Activity Index for Psoriatic Arthritis (DAPSA), a validated, unidimensional score focusing on joint involvement, is one of the recommended options [1]. However, routine determination of C-reactive protein (CRP) to calculate DAPSA values takes hours to days. In contrast, quick quantitative CRP (qCRP) tests require only a few minutes and might facilitate regular assessment of the DAPSA (as Q-DAPSA) in clinical routine.

Objectives:

To validate the Q-DAPSA in a prospective, multicenter study of PsA patients. Since the Disease Activity Score 28 (DAS28) is not only used in rheumatoid arthritis, but also in PsA patients, the study also investigated the performance of a qCRP based DAS28 (DAS28-qCRP) in a PsA cohort.

Methods:

The study was conducted in five centers in Berlin, Germany. Consecutive adult (≥ 18 years) PsA patients were included. In addition to a rheumatological assessment, including patient reported outcomes (PROs), routine CRP and erythrocyte sedimentation rate (ESR) were measured in the local labs. Additionally, a qCRP testing with the „QuikRead go instrument“ (Aidian Oy, Finland) was performed locally at the study center (measurement range 0.5 - 200 mg/l for hematocrit concentrations of 40 – 45%). Statistical analysis included descriptive statistics, cross tabulation and weighted Cohen´s kappa comparing disease activity categories, Bland-Altman plots and intraclass correlation coefficient (ICC) for DAPSA, Q-DAPSA, DAS28-CRP and DAS28-qCRP.

Results:

In this study 104 patients were included between January and October 2020 (mean age: 51.2 years, mean disease duration: 7.1 years, 49 patients (47.1%) were male). 53 patients (51.0%) were treated with a bDMARD and 37 patients (35.6%) with csDMARDs. CRP and qCRP showed mean values of 5.20 and 6.17 mg/l, respectively. With the Q-DAPSA, 103 patients (99.0%) were assigned to the same disease activity category when compared to DAPSA (Table 1). Weighted Cohen´s kappa was 0.990 (95%CI 0.970; 1.000). ICC for numerical values of DAPSA and Q-DAPSA was 1.000 (95%CI 0.999; 1.000). The agreement of Q-DAPSA and DAPSA is shown in a Bland-Altman plot (Figure 1). DAS28-CRP and -qCRP were available for 103 patients; 101 patients (98.1%) showed the same disease activity category in the DAS28-qCRP and weighted Cohen´s kappa was 0.951 (95%CI 0.886; 1.000).

Conclusion:

The Q-DAPSA and DAPSA showed an almost perfect agreement on the assignment to disease activity categories (99%) with the important advantage of time. With Q-DAPSA, rheumatologists could base their clinical decision-making on a disease activity measurement by using a composite score immediately. Consequently, Q-DAPSA can be integrated in clinical routine and clinical trials and could be implemented into the treat-to-target concept in PsA patients. For rheumatologists who prefer DAS28-CRP for assessing disease activity in PsA patients, DAS28-qCRP may serve as a suitable alternative.

References:

[1]Smolen JS, et al. Ann Rheum Dis. 2018 Jan; 77(1):3-17.

Table 1.

Disease activity categories by Q-DAPSA vs. DAPAS

Q-DAPSA (n = 104)Remission (≤ 4)Low Disease Activity (> 4 and ≤ 14)High Disease Activity (> 14 and≤ 28)Very high Disease Activity (> 28)DAPSARemission (≤ 4)36 (34.6%)1 (1.0%)Low Disease Activity (> 4 and ≤ 14)39 (37.5%)High Disease Activity (> 14 and ≤ 28)22 (21.2%)Very high Disease Activity (> 28)6 (5.8%)

The fields highlighted in red indicate that disease activity categories do not match. DAPSA = Disease activity index for Psoriatic Arthritis, Q-DAPSA = DAPSA calculated based on a quick quantitative CRP

Figure 1.

Bland-Altman plot for Q-DAPSA and DAPSA

Acknowledgements:

The authors would like to deeply thank Braun T, Doerwald C, Deter N, Höppner C, Lackinger J, Lorenz C, Lunkwitz K, Mandt B, Sron S and Zernicke J for their practical support and coordinating the study.

Funding statement:

The AQUA study was supported by an unrestricted research grant from Novartis. Testing kits were provided free of charge from Aidian Oy, Finland.

Disclosure of Interests:

None declared.

POS1007 OPTIMIZING A REFERRAL STRATEGY FOR PATIENTS WITH A HIGH PROBABILITY OF AXIAL SPONDYLOARTHRITIS: THE ROLE OF AGE AND SYMPTOM DURATION

Background:

One of the most important prerequisites for a timely diagnosis of axial spondyloarthritis (axSpA) is the early referral of a patient with back pain to a rheumatologist. In the past years a number of referral strategies has been proposed, most of them in line with the ASAS referral recommendations [1] and with a similar performance – about 30-40% of the referred patients can be diagnosed with axSpA after examination by a rheumatologist. In addition to physician-based strategies, an online self-referral (OSR) strategy has been recently proposed and evaluated about 20% of the patients being diagnosed with axSpA after rheumatologic evaluation [2].

Objectives:

The objective of the current analysis was to investigate the role of age and symptom duration for the optimization of a physician-based and an OSR strategy for axSpA.

Methods:

In the OptiRef study, patients with chronic back pain and suspicion of axSpA either referred by primary care physicians /orthopedists using the Berlin referral tool (=physician based) or based on a referral recommendation of an OSR were evaluated by rheumatologists in a specialized center [2]. All patients underwent a structured examination including imaging that resulted into the final diagnosis of axSpA or no axSpA. The relationship between age, symptom duration and the likelihood of axSpA diagnosis was evaluated in this analysis.

Results:

A total of 360 patients (180 presented via the OSR and 180 referred by the physician based referral strategy) were included in this analysis. Patient’s characteristics are shown in Table 1. A total of 71 patients (39.4%) in the physician-based group and 35 patients (19.4%) in the OSR group were finally diagnosed with axSpA. The heatmaps depicting the relationship between the proportions of patients diagnosed with axSpA and age plus symptom duration (Figure 1) showed a clear decline of the axSpA probability with increasing age. In the physician-referred group, however, axSpA was diagnosed even in patients who were above 50 years at the time-point of the examination, while there were only few patients with axSpA in the self-referred group aged 40-49 years, and none in the age group ≥50 years. Interestingly, there was no clear relationship between symptom duration and probability of the diagnosis: axSpA was diagnosed in a substantial proportion of patients even with a long history of back pain (>12 years) in both subgroups.

Conclusion:

The probability of axSpA is high in patients suffering from back pain and aged <40 years with a substantial decline thereafter. Therefore, a referral strategy based on self-evaluation of symptoms should be more focused on a younger patient population, while physician-based strategies do not require such a restriction.

References:

[1]Poddubnyy D, et al. Ann Rheum Dis 2015 Aug; 74(8):1483-1487.

[2]Proft F, et al. Semin Arthritis Rheum. 2020; 50(5):1015-1021.

Table 1.

Patient characteristics

TotalN=360Berlin toolN=180Self-referralN=180p-valueDiagnosis of axial SpA, n (%)106 (29.4%)71 (39.4%)35 (19.4%)<0.0001Age, years, mean (SD)36.9 (10.4)37.2 (11.5)36.6 (9.2)>0.99Male sex, n (%)177 (49.2%)100 (55.6%)77 (42.8%)0.02Back pain duration, years, mean (SD)7.9 (7.6)6.5 (6.9)9.2 (8.1)<0.0001HLA-B27 positive, n (%)141 (40.9%)104 (59.8%)37 (21.6%)<0.0001CRP elevation, n (%)52 (14.8%)34 (19.4%)18 (10.2%)0.02Inflammatory back pain, n (%)204 (56.7%)103 (57.2%)101 (56.1%)0.92Figure 1.

Heatmaps depicting the proportions of patients diagnosed with axSpA in relation to age and symptom duration in the physician-based (A) and OSR (B) groups.

Acknowledgements:

We would like to thank all orthopaedists and primary care physicians who referred their patients. Further, we thank Dr. Anne-Katrin Weber and Dr. Susanne Lüders for the data collection support, Annegret Langdon for the data management support and Torsten Karge for set-up and support of the online screening tool.

Funding statement

The OptiRef study was supported by an unrestricted research grant from Novartis.

Disclosure of Interests:

None declared.

POS0988 FACTORS ASSOCIATED WITH PAIN INTENSITY IN AXIAL SPONDYLOARTHRITIS. RESULTS FROM THE EUROPEAN MAP OF AXIAL SPONDYLOARTHRITIS (EMAS)

Background:

Pain is a hallmark of axial spondyloarthritis (axSpA) and can significantly deteriorate patients’ health status.

Objectives:

This analysis aims to investigate factors associated with pain intensity in a large sample of European axSpA patients.

Methods:

2,846 unselected patients participated in EMAS, a cross-sectional study (2017-2018) across 13 European countries. Data from 2,636 participants who reported pain were analysed. Pain was measured by the mean of two BASDAI questions (range 0 “no pain” to 10 “most severe pain”): “How would you describe the overall level of AS neck, back or hip pain you have had?” and “How would you describe the overall level of pain/swelling in joints other than neck, back, hips you have had?”. Linear regression analysis was applied to identify associations between pain intensity and sociodemographic factors, patient-reported outcomes [BASDAI (0-10), spinal stiffness (3-12), functional limitation (0-54), mental health using the 12-item General Health Questionnaire GHQ-12 (0-12)], work life, physical activity and comorbidities, for which 850 patients were included.

Results:

The mean age of the sample was 44 years, 61.4% were female, 49.4% had a university degree and 67.7% were married. The average reported pain intensity was 5.3 (±2.2); 76.2% reported pain intensity ≥4, with the greatest intensity reported by women (5.5 vs 4.9, p<0.001), those not university educated (5.6 vs 5.0, p<0.001), separated or divorced compared to singles (5.8 vs 5.2, p=0.004), and not physically active (5.7 vs 5.2, p<0.001). In addition, employed patients who experienced work-related issues reported greater pain (5.2 vs 3.9) as did those who experienced/ believed they would face difficulties finding work due to axSpA (5.9 vs 4.3), and those whose employment choice was determined by axSpA (5.7 vs 4.9; all p<0.001). Moreover, associations with anxiety (5.9 vs 5.0), depression (6.1 vs 5.0) and sleep disorders (5.9 vs 4.9; all p<0.001) were also found. The multiple linear regression model showed that those with higher pain intensity reported at least one work-related issue (B=0.65), difficulties finding work due to axSpA (B=0.48), not having attended university (B=0.38), greater spinal stiffness (B= 0.29), being female (B=0.26) and poorer mental health (GHQ-12) (B=0.10) (Table 1).

Table 1.

Regression analysis of the variables associated with pain intensity (0-10 NRS), n=850

UnivariableMultivariableB95% CIB95% CIGender. Female10.6040.432, 0.7750.2600.003, 0.517Educational level. No University20.6710.504, 0.8380.3760.118,0.634Marital Status. Divorced/Separated30.4950.209, 0.780-0.044-0.468, 0.380Body Mass Index. Obese40.362-0.097, 0.821NANAGHQ-12 (0-12)0.1820.163, 0.2010.1000.064, 0.137Functional Limitation (0-54)0.0360.030, 0.0410.009-0.001, 0.018Spinal Stiffness (3-12)0.3570.326, 0.3880.2880.234, 0.342Diagnostic Delay, years0.0200.010, 0.030-0.015-0.032, 0.002Work-Related Issues. Yes1.3381.095, 1.5820.6540.338, 0.970Difficulty finding job due to axSpA. Yes1.5681.362, 1.7740.4760.176, 0.776Work choice determinate by axSpA. Yes0.8080.633, 0.9830.199-0.069, 0.467Physical activity. No0.4940.263, 0.725-0.128-0.497, 0.242Anxiety diagnosis. Yes0.9350.753, 1.117-0.047-0.416, 0.321Depression diagnosis. Yes1.1070.919, 1.2950.115-0.270, 0.500Sleep disorder diagnosis. Yes1.0420.871, 1.213-0.091-0.392, 0.211

1Female vs Male; 2No university studies (no schooling, primary and high school) vs University studies; 3Divorced/separated vs single, married and widow; 4Obese vs not obese (underweight, normal and overweight).

Conclusion:

Pain was most strongly associated with working life impairment, as well as with spinal stiffness. Pain was also associated with suffering from depression, anxiety and sleep disorders. Understanding how pain affects individuals and shared-decision making between rheumatologists and patients are essential for long-term disease management and preserving quality of life of axSpA patients.

Acknowledgements:

This study was supported by Novartis Pharma AG. The authors would like to thank all patients who participated in the EMAS study.

Disclosure of Interests:

Marco Garrido-Cumbrera: None declared, Victoria Navarro-Compán Grant/research support from: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Christine Bundy Consultant of: Abbvie, Celgene, Janssen, Lilly, Novartis, and Pfizer, Laura Christen Employee of: Novartis Pharma AG, Raj Mahapatra: None declared, Souzi Makri: None declared, Carlos Jesús Delgado-Domínguez: None declared, José Correa-Fernández: None declared, Pedro Plazuelo-Ramos: None declared, Denis Poddubnyy Consultant of: Abbvie, BMS, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: Abbvie, MSD, Novartis, and Pfizer.

POS0979 ASSOCIATION BETWEEN HIGHER INTAKE OF CARBOHYDRATES AND FREE SUGAR WITH HIGHER DISEASE ACTIVITY IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS

Background:

Diet has been previously described as an impact factor on the course of rheumatic diseases, such as rheumatoid arthritis and systemic lupus erythematosus (SLE). It has been previously reported that dietary sugar intake may contribute to subclinical inflammation and disease activity in SLE. However, there is very little investigation on the possible association between nutritional parameters and their influence on spondyloarthritis (SpA).

Objectives:

To investigate the possible impact of nutritional parameters on the disease activity in patients with SpA.

Methods:

Patients with radiographic axial SpA and starting a biological therapy were recruited between 2015 and 2019 in an extension of the prospective German Spondyloarthritis Inception Cohort (GESPIC). Dietary habits were collected at baseline using the country-specific validated food frequency questionnaire (FFQ) developed for the use in the German Health examination Survey for Adults 2008-2011. The FFQ includes questions about the frequency and amount of 53 food items, consumed during the past 4 weeks, and enabled to compute individual mean consumptions of foods in grams per day. Total energy intake (in Kcal per day) and nutritional parameters: carbohydrates, free sugars, total fats, saturated fats, mono and poly-unsaturated fats, proteins and dietary fiber, were calculated for each patient using a nutrition organization software and the database of Federal Food Code (Bundeslebensmittelschlüssel), version 3.02. Disease activity measures (BASDAI, CRP and ASDAS), as well as height, weight and body mass index (BMI) were assessed at baseline before starting the biological treatment.

Results:

A total of 104 patients from 129 patients with axial SpA enrolled in the cohort were included in this nutritional analysis. The mean age (mean±SD) was 37.0±11.0 years old with symptoms duration of 11.3±9.9 years, 68.3% were males, and 86.5% were HLA-B27 positive. Patients presented BMI of 25.1±4.3 kg/m2, BASDAI 5.6±1.4, CRP 14.0±18.2 mg/l, and ASDAS 3.5±1.0.

In the univariable and multivariable regression analysis, a higher energy intake and carbohydrates were associated with higher disease activity, measured by ASDAS, BASDAI and CRP. This association was attributable to the full intake of carbohydrates and specifically to the total of free sugars (monosaccharides and disaccharides) and the decrease of dietary fiber as shown in the multivariable analyses (Figure 1). This effect was independent of age, sex, smoker status and BMI.

Conclusion:

A higher intake of carbohydrates and a higher consumption of free sugars are associated with higher disease activity in patients with AS.

Figure 1.

Multivariable linear regression analysis of the association between CRP and nutritional parameters in patients with radiographic axial SpA (n=104), adjusted for age, sex, body mass index and smoker status. Model 1 included variable of total energy intake, model 2 included variable of total intake of carbohydrates (CH) and model 3 included variable of free-sugar (monosaccharides and disaccharides).

B, linear regression coefficient; CH, carbohydrates; CI, confidence interval; MS-FA, monosaturated fatty acids; PuS-FA, polyunsaturated fatty acids, S-FA, saturated fatty acids.

Disclosure of Interests:

None declared.

Choose wisely: imaging for diagnosis of axial spondyloarthritis

Objective

To assess the diagnostic accuracy of radiography (X-ray, XR), CT and MRI of the sacroiliac joints for diagnosis of axial spondyloarthritis (axSpA).

Methods

163 patients (89 with axSpA; 74 with degenerative conditions) underwent XR, CT and MR. Three blinded experts categorised the imaging findings into axSpA, other diseases or normal in five separate reading rounds (XR, CT, MR, XR +MR, CT +MR). The clinical diagnosis served as reference standard. Sensitivity and specificity for axSpA and inter-rater reliability were compared.

Results

XR showed lower sensitivity (66.3%) than MR (82.0%) and CT (76.4%) and also an inferior specificity of 67.6% vs 86.5% (MR) and 97.3% (CT). XR +MR was similar to MR alone (sensitivity 77.5 %/specificity 87.8%) while CT+MR was superior (75.3 %/97.3%). CT had the best inter-rater reliability (kappa=0.875), followed by MR (0.665) and XR (0.517). XR +MR was similar (0.662) and CT+MR (0.732) superior to MR alone.

Conclusions

XR had inferior diagnostic accuracy and inter-rater reliability compared with cross-sectional imaging. MR alone was similar in diagnostic performance to XR+MR. CT had the best accuracy, strengthening the importance of structural lesions for the differential diagnosis in axSpA.

POS0900 SECUKINUMAB 150 MG PROVIDES SUSTAINED IMPROVEMENT IN SIGNS AND SYMPTOMS OF NON-RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS: 2-YEAR RESULTS FROM THE PREVENT STUDY

Background:

Axial spondyloarthritis (axSpA) is an inflammatory disease characterised by chronic back pain, and it comprises radiographic axSpA and non-radiographic axSpA (nr-axSpA).1 Secukinumab (SEC) 150 mg, with (LD) or without loading (NL), dose significantly improved the signs and symptoms of patients with nr-axSpA in the PREVENT (NCT02696031) study through Week 52.2

Objectives:

To report the long-term clinical efficacy and safety of secukinumab from the PREVENT study through 2 years.

Methods:

A detailed study design, key primary and secondary endpoints have been reported previously.2 In total, 555 patients fulfilling ASAS criteria for axSpA plus abnormal C-reactive protein (CRP) and/or MRI, without evidence of radiographic changes in sacroiliac (SI) joints according to modified New York Criteria for AS were randomised (1:1:1) to receive SEC 150 mg with LD, NL, or placebo (PBO) at baseline. LD patients received SEC 150 mg at Weeks 1, 2, 3, and 4, and then every 4 weeks (q4wk) starting at Week 4. NL patients received SEC 150 mg at baseline and PBO at weeks 1, 2, and 3, and then 150 mg q4wk. 90% patients were anti-tumour necrosis factor (anti-TNF) naïve, 57% had elevated CRP and 73% had evidence of SI joint inflammation on MRI. All images were assessed centrally before inclusion. All patients continued to receive open-label SEC 150 mg treatment after Week 52. Efficacy assessments through Week 104 included ASAS40 in anti-TNF-naïve patients, ASAS40, BASDAI change from baseline, BASDAI50, ASAS partial remission, and ASDAS-CRP inactive disease in the overall population. The safety analyses included all patients who received ≥1 dose of study treatment for the entire treatment period up to Week 104. Data are presented as observed.

Results:

Overall, 438 patients completed 104 weeks of study: 78.9% (146/185; LD), 77.7% (143/184; NL) and 80.1% (149/186; PBO). Efficacy results at Week 52 were sustained through Week 104 and are reported in the Table 1. The safety profile was consistent with the previous reports with no deaths reported during the entire treatment period up to Week 104.2

Conclusion:

Secukinumab 150 mg demonstrated sustained improvement in the signs and symptoms of patients with nr-axSpA through 2 years. Secukinumab was well tolerated with no new or unexpected safety signals.

References:

[1]Strand V, et al. J Clin Rheumatol. 2017; 23(7):383–91.

[2]Deodhar A, et al. Arthritis Rheumatol. 2020. Online ahead of print.

Figure 1.

ASAS40 response was maintained through Week 104 in the overall population

Table 1.

Summary of clinical efficacy (Observed data)

EndpointsWeekSEC 150 mg LD(N=185)SEC 150 mg NL(N=184)PBO-SEC 150 mg(N=186)*ASAS40 in anti-TNF-naïve patients, n/M (%)52a90/137 (65.7)95/145 (65.5)85/151 (56.3)10478/123 (63.4)83/123 (67.5)83/134 (61.9)BASDAI change from baseline, mean±SD52a−3.7±2.8−3.7±2.6−3.3±2.4104−4.1±2.6−3.9±2.6−3.7±2.5BASDAI50, n/M (%)52a90/153 (58.8)92/163 (56.4)90/161 (55.9)10488/137 (64.2)84/136 (61.8)87/142 (61.3)ASAS partial remission,n/M (%)52a46/152 (30.3)56/163 (34.4)46/161 (28.6)10451/137 (37.2)50/135 (37.0)50/142 (35.2)ASDAS CRP inactive disease, n/M (%)52a49/152 (32.2)58/163 (35.6)48/160 (30.0)10450/132 (37.9)53/133 (39.8)53/142 (37.3)

*For anti-TNF-naïve patients, N=164, LD; 166, NL; 171, PBO-SEC.

a total number of evaluable patients including open-label SEC and standard of care (SOC; 2 patients in LD, 1 patient in NL continued on SOC). After Week 52, only patients who continued to receive open-label SEC are presented.

ASAS, Assessment of SpondyloArthritis International Society; ASDAS, Ankylosing Spondylitis Disease Activity Score; BASDAI, Bath Ankylosing Spondylitis Disease Activity Index; M, number of patients with evaluation; N, total randomised patients; n, number of patients who are responders; SD, standard deviation

Disclosure of Interests:

Denis Poddubnyy Speakers bureau: AbbVie, BMS, Eli Lilly, MSD, Novartis, Pfizer, UCB, Consultant of: AbbVie, Biocad, BMS, Eli Lilly, Gilead, MSD, Novartis, Pfizer, Samsung Bioepis, UCB, Grant/research support from: AbbVie, MSD, Novartis, Pfizer, Atul Deodhar Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myer Squibb (BMS), Eli Lilly, GSK, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, GSK, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Eli Lilly, GSK, Novartis, Pfizer, and UCB, Xenofon Baraliakos Speakers bureau: AbbVie, BMS, Celgene, Chugai, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, BMS, Celgene, Chugai, Galapagos, Gilead, MSD, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie and Novartis, Ricardo Blanco Speakers bureau: AbbVie, Pfizer, Roche, Bristol-Myers, Janssen, UCB pharma and MSD and Eli Lilly, Consultant of: AbbVie, Pfizer, Roche, Bristol-Myers, Janssen, UCB pharma and MSD, Grant/research support from: AbbVie, MSD, and Roche, Eva Dokoupilova Grant/research support from: AbbVie, Affibody AB, Eli Lilly, Galapagos, Gilead, GSK, Hexal AG, MSD, Novartis, Pfizer, R-Pharm, Sanofi-Aventis, and UCB, Stephen Hall Speakers bureau: Novartis, Merck, Janssen, Pfizer, Eli Lilly, and UCB, Consultant of: Novartis, Merck, Janssen, Pfizer, Eli Lilly, and UCB, Grant/research support from: AbbVie, UCB, Janssen, and Merck, Alan Kivitz Shareholder of: Pfizer, Sanofi, Novartis, Amgen, GlaxoSmithKline, Gilead Sciences, Inc., Speakers bureau: Celgene, GlaxoSmithKline, Eli Lilly, Merck, Novartis, Pfizer, Sanofi, Genzyme, Flexion, AbbVie, UCB, Consultant of: AbbVie, Boehringer Ingelheim, Flexion, Janssen, Pfizer, Sanofi, Regeneron, SUN Pharma Advanced Research, Gilead Sciences, Inc., Marleen G.H. van de Sande Speakers bureau: Novartis, MSD, Consultant of: Abbvie, Novartis, Eli Lily, Grant/research support from: Novartis, Eli Lilly, Janssen, UCB, Anna Stefanska Shareholder of: Novartis, Employee of: Novartis, Patricia Pertel Shareholder of: Novartis, Employee of: Novartis, Hanno Richards Shareholder of: Novartis, Employee of: Novartis, Juergen Braun Speakers bureau: Abbvie (Abbott), Amgen, BMS, Boehringer, Celgene, Celltrion, Centocor, Chugai, EBEWE Pharma, Medac, MSD (Schering-Plough), Mundipharma, Novartis, Pfizer (Wyeth), Roche, Sanofi-Aventis and UCB pharma, Eli Lilly, Consultant of: Abbvie (Abbott), Amgen, BMS, Boehringer, Celgene, Celltrion, Centocor, Chugai, EBEWE Pharma, Medac, MSD (Schering-Plough), Mundipharma, Novartis, Pfizer (Wyeth), Roche, Sanofi-Aventis and UCB, Eli Lilly, Grant/research support from: Abbvie (Abbott), Amgen, BMS, Boehringer, Celgene, Celltrion, Centocor, Chugai, Medac, MSD (Schering-Plough), Mundipharma, Novartis, Pfizer (Wyeth), Roche, Sanofi-Aventis and UCB, Eli Lilly

Continuing versus withdrawing ixekizumab treatment in patients with axial spondyloarthritis who achieved remission: efficacy and safety results from a placebo-controlled, randomised withdrawal study (COAST-Y)

Objectives

The objective of COAST-Y was to evaluate the effect of continuing versus withdrawing ixekizumab (IXE) in patients with axial spondyloarthritis (axSpA) who had achieved remission.

Methods

COAST-Y is an ongoing, phase III, long-term extension study that included a double-blind, placebo (PBO)-controlled, randomised withdrawal-retreatment period (RWRP). Patients who completed the originating 52-week COAST-V, COAST-W or COAST-X studies entered a 24-week lead-in period and continued either 80 mg IXE every 2 (Q2W) or 4 weeks (Q4W). Patients who achieved remission (an Ankylosing Spondylitis Disease Activity Score (ASDAS)<1.3 at least once at week 16 or week 20, and <2.1 at both visits) were randomly assigned equally at week 24 to continue IXE Q4W, IXE Q2W or withdraw to PBO in a blinded fashion. The primary endpoint was the proportion of flare-free patients (flare: ASDAS≥2.1 at two consecutive visits or ASDAS>3.5 at any visit) after the 40-week RWRP, with time-to-flare as a major secondary endpoint.

Results

Of 773 enrolled patients, 741 completed the 24-week lead-in period and 155 entered the RWRP. Forty weeks after randomised withdrawal, 83.3% of patients in the combined IXE (85/102, p<0.001), IXE Q4W (40/48, p=0.003) and IXE Q2W (45/54, p=0.001) groups remained flare-free versus 54.7% in the PBO group (29/53). Continuing IXE significantly delayed time-to-flare versus PBO, with most patients remaining flare-free for up to 20 weeks after IXE withdrawal.

Conclusions

Patients with axSpA who continued treatment with IXE were significantly less likely to flare and had significantly delayed time-to-flare compared with patients who withdrew to PBO.

Unveiling axial involvement in psoriatic arthritis: An ancillary analysis of the ASAS-perSpA study

OBJECTIVE

To determine the clinical profile of axial psoriatic arthritis (PsA) in a worldwide setting. Secondly, to identify factors associated with the development of axial involvement in patients with PsA.

METHODS

Data from 3684 patients with axial spondyloarthritis (axSpA) or PsA from the ASAS-perSpA study were analysed. The ASAS-perSpA is a cross-sectional study that recruited consecutive patients with SpA (as diagnosed by their rheumatologist) from 68 centers worldwide and collected patient and disease data. First, 2651 axSpA patients and 367 PsA patients with any history of axial involvement (axPsA) were compared using logistic regression to later identify predictive factors for rheumatologist diagnosis of axPsA. Secondly, 367 axPsA patients were compared with 666 PsA patients lacking axial involvement (peripheral PsA [pPsA]) and the characteristics associated with axial manifestations were explored by logistic regression analysis.

RESULTS

Patients with axPsA were older and less frequently males or HLA*B27 positive in comparison with axSpA patients. Additionally, while patients with axPsA had more peripheral manifestations and psoriasis, other extra-musculoskeletal manifestations (IBD and uveitis) were more frequent in those with axSpA. In the multivariable analysis, older age at diagnosis (OR = 1.04), peripheral arthritis (OR = 7.32) and dactylitis (OR = 2.82) were significantly associated with the diagnosis of axPsA. However, uveitis (OR = 0.22), IBD (OR = 0.12), HLA*B27 carriership (OR = 0.26) or sacroiliitis on imaging (OR = 0.5) were inversely associated with axPsA diagnosis as compared to axSpA. Axial involvement in patients with PsA was significantly associated with male gender (OR = 1.68), elevated CRP (OR = 2.87) and the absence of psoriasis (OR = 0.33).

CONCLUSION

In this worldwide setting axPsA was defined by rheumatologists as a unique phenotype, with disease features lying between axSpA and pure pPsA.