Development of an environmental contextual factor item set relevant to global functioning and health in patients with axial Spondyloarthritis

OBJECTIVE

To describe the development of an Environmental contextual factors (EF) Item Set (EFIS) accompanying the disease specific Assessment of SpondyloArthritis international Society Health Index (ASAS HI).

METHOD

First, a candidate item pool was developed by linking items from existing questionnaires to 13 EF previously selected for the ICF/ASAS Core Set. Second, using data from two international surveys, which contained the EF item pool as well as the items from the ASAS HI, the number of EF-items was reduced based on the correlation between the item and the ASAS HI sum score combined with expert opinion. Third, the final English EFIS was translated into 15 languages and cross-culturally validated.

RESULTS

The initial item pool contained 53 EF addressing 4 ICF EF-chapters: products and technology (e1), support and relationship (e3), attitudes (e4) and health services (e5). Based on 1754 responses of axial spondyloarthritis patients in an international survey, 44 of 53 initial items were removed based on low correlations to the ASAS HI or redundancy combined with expert opinion. 9 items of the initial item pool (range correlation 0.21-0.49) form the final EFIS. The EFIS was translated into 15 languages and field tested in 24 countries.

CONCLUSIONS

An EFIS is available complementing the ASAS HI and helps to interpret the ASAS HI results by gaining an understanding of the interaction between a health condition and contextual factors. The EFIS emphasizes the importance of support and relationships, as well as attitudes of the patient and health services in relation to self-reported health.

Experimental Investigations of Micro-Meso Damage Evolution for a Co/WC-Type Tool Material with Application of Digital Image Correlation and Machine Learning

Commercial Co/WC/diamond composites are hard metals and very useful as a kind of tool material, for which both ductile and quasi-brittle behaviors are possible. This work experimentally investigates their damage evolution dependence on microstructural features. The current study investigates a different type of Co/WC-type tool material which contains 90 vol.% Co instead of the usual <50 vol.%. The studied composites showed quasi-brittle behavior. An in-house-designed testing machine realizes the in-situ micro-computed tomography (μCT) under loading. This advanced equipment can record local damage in 3D during the loading. The digital image correlation technique delivers local displacement/strain maps in 2D and 3D based on tomographic images. As shown by nanoindentation tests, matrix regions near diamond particles do not possess higher hardness values than other regions. Since local positions with high stress are often coincident with those with high strain, diamonds, which aim to achieve composites with high hardnesses, contribute to the strength less than the WC phase. Samples that illustrated quasi-brittle behavior possess about 100-130 MPa higher tensile strengths than those with ductile behavior. Voids and their connections (forming mini/small cracks) dominant the detected damages, which means void initiation, growth, and coalescence should be the damage mechanisms. The void appears in the form of debonding. Still, it is uncovered that debonding between Co-diamonds plays a major role in provoking fatal fractures for composites with quasi-brittle behavior. An optimized microstructure should avoid diamond clusters and their local volume concentrations. To improve the time efficiency and the object-identification accuracy in μCT image segmentation, machine learning (ML), U-Net in the convolutional neural network (deep learning), is applied. This method takes only about 40 min to segment more than 700 images, i.e., a great improvement of the time efficiency compared to the manual work and the accuracy maintained. The results mentioned above demonstrate knowledge about the strengthening and damage mechanisms for Co/WC/diamond composites with >50 vol.% Co. The material properties for such tool materials (>50 vol.% Co) is rarely published until now. Efforts made in the ML part contribute to the realization of autonomous processing procedures in big-data-driven science applied in materials science.

The OMERACT Knee Inflammation MRI Scoring System: Validation of quantitative methodologies and tri-compartmental overlays in osteoarthritis

OBJECTIVE

To validate a revised version of the KIMRISS method for quantification of BML and synovitis-effusion in the knee by comparison with an established method, MOAKS.

METHODS

Novel calibration tools were developed for both methods. We compared reliability for status and change scores of BML and synovitis-effusion on baseline and one-year MRI scans.

RESULTS

Significant increase in both BML and synovitis-effusion was evident using KIMRISS but only for synovitis-effusion using MOAKS. Pre-specified targets for acceptable reliability (≥0.80 and ≥0.70 for status and change scores, respectively) were achieved more frequently for KIMRISS for both BML and synovitis.

CONCLUSION

Per OFISA criteria, KIMRISS should progress to assessment of discrimination.

POS1101 THE OMERACT KNEE INFLAMMATION MRI SCORING SYSTEM: VALIDATION OF QUANTITATIVE METHODOLOGIES AND TRI-COMPARTMENTAL OVERLAYS BY COMPARISON WITH THE MRI OSTEOARTHRITIS KNEE SCORE

Background:

Randomized controlled trials have targeted reducing the size of BML and degree of synovitis for the treatment of OA. We have developed the OMERACT Knee Inflammation MRI Scoring System (KIMRISS) and have recently refined it to maximize reliability and sensitivity to change. Innovations include electronic overlays for assessment of BML in 500 subregions, a web-based interface with direct online scoring, and real-time iterative calibration (RETIC) prior to reading exercises. Synovitis-effusion (S-E) is also scored on all consecutive sagittal slices on a web-based interface.

Objectives:

We aimed to test the feasibility, reliability, and responsiveness of KIMRISS versus an established method, MOAKS, in two multi-reader exercises.

Methods:

KIMRISS incorporates web-based graphic overlays for each of femur, tibia, and patella (range 0-500). S-E is recorded as the largest diameter perpendicular to the longest axis of this feature (range 0-100). All scores are pro-rated for a standardized number of MRI slices. In a pre-reading exercise for KIMRISS, readers scored sufficient cases in RETIC to attain scoring proficiency, pre-specified as an ICC of ≥0.80 and ≥0.70 for status and change scores of BML and S-E compared to developer reads. A new web-based scoring platform with overlays designating different subregions for scoring BML was developed for MOAKS. We compared reliability for status and change scores of BML and S-E in 2 international multi-reader exercises of baseline and one-year MRI scans from the Osteoarthritis Initiative: A. 4 expert readers and an OMERACT fellow scored 38 cases selected for MOAKS BML score ≥1. B. 7 expert readers and an OMERACT fellow scored 60 cases selected for MOAKS BML ≥3 and Kellgren-Lawrence (K-L) grade <3. Reliability was assessed by intra-class correlation coefficient (ICC) and Smallest Detectable Change (SDC), responsiveness by the standardized response mean (SRM), and feasibility using the System Usability Scale (SUS scoring range 0-100).

Results:

For exercises A/B, subjects were 55.3%/ 26.7% male, mean(±SD) age 61.7(±9.1)/61.9(8.8) years, and radiographic K-L grade ≤2 in 39.4%/100%. Change was small in both exercises (<5% of scoring range for KIMRISS and MOAKS BML and S-E) with comparable responsiveness (Table 1). Despite this, ICC for change was consistently good to very good for both BML and S-E and consistently better for KIMRISS (Table 1). Mean SUS scores were 88.2 for KIMRISS and 54.3 for MOAKS.

Table 1.

KIMRISS and MOAKS scores in Two International Multi-reader Exercises

MethodMRI featureScores mean (SD)SDC(% of max)P valueSRMBaselineOne-year Follow upChangeEXERCISE AMOAKSBML3.6 (2.9)3.4 (2.3)-0.2 (1.9)1.0 (2.2%)0.72-0.11Synovitis-effusion1.3 (0.8)1.5 (0.8)0.2 (0.4)0.4 (13.3%)0.0170.5KIMRISSBML15.7 (13.3)21.2 (22.5)5.5 (15.3)5.6 (1.1%)0.0220.36Synovitis-effusion21.8 (12.0)24.3 (11.9)2.5 (7.4)2.8 (2.8%)0.0430.34EXERCISE BMOAKSBML4.2 (2.6)3.7 (2.4)-0.5 (2.1)1.1 (2.4%)0.083-0.24Synovitis-effusion1.2 (0.7)1.3 (0.8)0.0 (0.5)0.4 (13.3%)0.590.0KIMRISSBML18.0 (17.5)15.9 (14.3)-2.1 (12.3)5.9 (1.2%)0.19-0.17Synovitis-effusion21.8 (9.3)22.9 (10.8)1.1 (7.1)2.2 (2.2%)0.250.15Intra-class Correlation Coefficients (95%CI)MethodMRI featureExercise AExercise BKIMRISS statusKIMRISS changeBML0.86 (0.78-0.92)0.88 (0.81-0.93)0.80 (0.70-0.87)0.72 (0.64-0.80)MOAKS statusMOAKS changeBML0.71 (0.46-0.85)0.76 (0.64-0.85)0.67 (0.56-0.77)0.69 (0.60-0.78)KIMRISS statusKIMRISS changeSynovitis-effusion0.88 (0.81-0.93)0.87 (0.79-0.92)0.75 (0.52-0.86)0.87 (0.82-0.91)MOAKS statusMOAKS changeSynovitis-effusion0.66 (0.4-0.79)0.52 (0.36-0.67)0.65 (0.52-0.75)0.48 (0.37-0.60)

Conclusion:

The KIMRISS method for scoring BML and Synovitis-Effusion scores highly for feasibility and demonstrates consistently high reliability when compared to MOAKS. Further validation for responsiveness is necessary in cases with greater change in MRI features than in the OAI dataset.

Disclosure of Interests:

None declared.

POS0032 SCORING MRI STRUCTURAL LESIONS IN SACROILIAC JOINTS OF PATIENTS WITH AXIAL SPONDYLOARTHRITIS: HOW MANY SLICES ARE OPTIMAL?

Background:

There is no international consensus on the optimal number of slices for evaluation of MRI structural lesions in the SIJ. An “all slice” method evaluates lesions from the most anterior slice, defined as the first slice with vertical height of ≥1cm of the SIJ joint cavity, up to the most posterior slice, defined as the most posterior slice where ≥1cm vertical height of the cartilaginous portion is still visible. The SPARCC method scores the transitional slice between cartilaginous and ligamentous compartments as the first slice and then an additional 4 slices anterior to the transitional slice.

Objectives:

We aimed to investigate inter-reader reliability, the extent of detection of lesions, and frequency of cases with a positive MRI for structural lesions when using an “all slice” approach versus the SPARCC scoring of 5 central slices.

Methods:

MRI T1W images with DICOM series were available from 148 cases who had MRI performed in the ASAS-Classification Cohort. Seven central readers recorded MRI lesions in an eCRF that recorded global assessments of presence/absence of changes suggestive of axSpA and structural lesions typical of axSpA. Structural lesions per the ASAS definitions were also recorded in consecutive semicoronal slices using the “all slice” approach, but also recording the transitional slice, according to their presence/absence in SIJ quadrants (erosion, fat lesion, sclerosis) or halves (backfill, ankylosis). Structural lesion frequencies were assessed descriptively according to majority agreement (≥4/7) of central readers and also any 2 central readers. Reliability for detection of MRI lesions was compared between central and local readers using the ICC.

Results:

The mean (SD) (range) number of anterior and posterior slices peripheral to the 5 central slices was 1.0 (1.0) (0-4) and 2.2 (1.8) (0-6) per case, respectively. There were 2 cases (1.4%) where ≥2 readers scored structural lesions in peripheral slices but not in the 5 central slices. The mean percentage of the total structural lesion score that was captured by the 5 central slices was >75% for all types of lesions except ankylosis (59%) (Table 1). Inter-reader reliability was greater for all lesions when assessing the 5 central slices and especially for erosion and backfill (Table 1).

Conclusion:

The major component of structural lesion data is captured by assessment of 5 slices, which includes the transitional slice and the subsequent 4 anterior slices. Moreover, reliability for detection of structural lesions is substantially worse in peripheral slices.

MRI Lesion“All slice”Central 5 slicesPeripheral slicesP value central vs peripheral slicesP value“all slice” vs central slicesMean (SD) Lesion Score Per CaseErosion2.4 (4.5) (0-22.9)1.8(3.4) (0-17.1)0.6 (1.4) (0-10.1)<0.001< 0.001Fat lesion2.5 (5.9) (0-34.0)1.8 (4.5) (0-25.1)0.7 (1.8) (0-9.9)< 0.001<0.001Sclerosis2.0 (4.9) (0-39.0)1.5 (3.6) (0-26.1)0.5 (1.5) (0-12.9)< 0.001<0.001Backfill0.5 (1.5) (0-12)0.4 (1.2) (0.0-9.3)0.1 (0.4) (0-2.7)< 0.0010.84Ankylosis0.5 (3.4) (0-30.7)0.3 (2.3) (0-20.0)0.2 (1.2) (0-11.3)0.100.18Mean (SD) (Range) % of Total Lesion Score in Central vs Peripheral slicesErosion100%76.4% (28.9%) (0-100%)23.6% (28.9%) (0-100%)<0.001NAFat lesion100%75.4% (26.5%) (0-100%)24.6% (26.5%) (0-100%)<0.001NASclerosis100%79.5% (22.9%) (0-100%)20.5% (22.9%) (0-100%)<0.001NABackfill100%86.0% (20.2%) (0-100%)14.0% (20.2%)(0-100%)<0.001NAAnkylosis100%59.0% (36.4%) (0-100%)41.0% (36.4%) (0-100%)0.56NAICC of 7 readers (Mean (SD) (Range))MRI lesionAll slicesCentral 5 slicesPeripheral slicesErosion0.54 (0.15) (0.28-0.84)0.58 (0.13) (0.34-0.85)0.40 (0.17) (0.10-0.66)Fat lesion0.61 (0.18) (0.30-0.89)0.63 (0.16) (0.35-0.88)0.52 (0.20) (0.19-0.82)Sclerosis0.73 (0.18) (0.36-0.94)0.73 (0.16) (0.36-0.91)0.67 (0.19) (0.27-0.94)Backfill0.37 (0.21) (0.10-0.85)0.39 (0.19) (0.14-0.83)0.18 (0.23) (0.0-0.80)Ankylosis0.97 (0.02) (0.91-0.99)0.99 (0.01) (0.97-1.0)0.85 (0.10) (0.62-0.98)

Disclosure of Interests:

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

POS0037 DOES IMAGING OF THE SACROILIAC JOINT DIFFER IN PATIENTS PRESENTING WITH UNDIAGNOSED BACK PAIN AND PSORIASIS, ACUTE ANTERIOR UVEITIS, AND COLITIS: AN INCEPTION COHORT STUDY

Background:

Axial spondyloarthritis (axSpA) presents diagnostic challenges incurring a delay of up to a decade and relies considerably on radiographic and MRI evidence of sacroiliitis which has led to the development of classification criteria which also rely on imaging. However, it has been suggested that such criteria may not be appropriate for axSpA patients presenting with other forms of SpA, especially psoriatic, because imaging features may vary in frequency and/or may be atypical. This hypothesis has never been tested in a prospective inception cohort of patients presenting with undiagnosed back pain.

Objectives:

We aimed to compare the spectrum of radiographic and MRI abnormalities in the sacroiliac joint (SIJ) of an inception cohort of patients presenting with undiagnosed back pain and psoriasis, iritis, and colitis.

Methods:

We used data from the prospective multicenter Screening for Axial Spondyloarthritis in Psoriasis, Iritis, and Colitis (SASPIC) Study, which is aimed at early detection of axial SpA in patients referred by the respective specialist after first presenting with these disorders. Consecutive patients ≤45 years of age with ≥3 months undiagnosed back pain with any one of psoriasis, AAU, or colitis undergo routine clinical evaluation by a rheumatologist for axial SpA followed by imaging. In SASPIC I, MRI evaluation of the SIJ was ordered per rheumatologist decision. In SASPIC II, MRI evaluation was ordered for all patients. Radiographs and MRI scans were assessed by two central readers and comparisons of the three groups were based on concordant assessments of imaging features. Evaluation of MRI scans included both global assessment for presence/absence of axSpA with confidence scale (-10 to +10), active and structural lesions typical of axSpA per recent ASAS definitions, and granular assessment of individual lesions according to SIJ quadrants and halves in consecutive semicoronal slices through the SIJ. Groups were compared by ANOVA and the chi-square test.

Results:

A total of 240 patients were recruited, 143 from SASPIC I and 97 from SASPIC II, 101 (42.1%) being diagnosed with axSpA (65.3% male, mean age 34.4 years, mean symptom duration 8.7 years, B27 positive 55.4%). Mean age of colitis (N=101), psoriasis (N=61), iritis (N=78) patients were 33.4, 36.6, 34.3 years, respectively, mean symptom duration was 6.8, 7.2, 9.4 years, respectively, and % males were 45.5%, 52.5%, 51.3%, respectively. There were no significant group differences for unilateral versus bilateral radiographic sacroiliitis and no significant differences in the frequencies, type, or distribution of MRI lesions (Table 1).

Conclusion:

Data from the SASPIC prospective inception cohort does not support the view that imaging of the SIJ differs in psoriatic axSpA, which appears similar to axSpA associated with iritis or colitis. These data support the umbrella concept of axSpA.

Imaging FeatureColitis (n=30)Psoriasis (n=19)Iritis (n=52)P valueUnilateral sacroiliitis (grade ≥2), N(%)1 (3.3%)0 (0%)2 (3.8%)0.69mNY criteria +, N(%)5 (16.7%)6 (31.2%)15 (28.8%)0.39Grade of sacroiliitis, mean(SD)1.8 (2.2)2.1 (2.7)2.2 (2.4)0.76MRI indicative of axSpA, N(%)15 (50.0%)11 (57.9%)32 (61.5%)0.60MRI indicative of axSpA (confidence ≥5/10), N(%)14 (46.7%)10 (52.6%)30 (57.7%)0.63MRI active lesion typical of axSpA, N(%)6 (20.0%)6 (31.6%)18 (34.6%)0.37MRI structural lesion typical of axSpA, N(%)11 (36.7%)7 (36.8%)18 (34.6%)0.98MRI with unilateral lesion (any)2 (6.7%)3 (15.8%)11 (21.2%)0.22MRI with unilateral lesion (BME)1 (3.3%)2 (10.5%)5 (9.6%)0.54MRI with unilateral lesion (Erosion)0 (0%)0 (0%)3 (5.8%)0.23MRI with unilateral lesion (Sclerosis)1 (3.3%)1 (5.3%)3 (5.8%)0.89MRI with unilateral lesion (Fat)0 (0%)0 (0%)0 (0%)NAMRI with iliac lesion17 (56.7%)12 (63.2%)32 (61.5%)0.88MRI with sacral lesion12 (40.0%)11 (57.9%)31 (59.6%)0.21

Disclosure of Interests:

Walter P Maksymowych Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, UCB, Consultant of: Abbvie, BMS, Boehringer, Galapagos, Gilead, Lilly, Novartis, Pfizer, UCB, Grant/research support from: Abbvie, Novartis, Pfizer, Ulrich Weber: None declared, Jon Chan: None declared, Raj Carmona: None declared, James Yeung: None declared, Sibel Aydin: None declared, Jodie Reis: None declared, Liam Martin: None declared, Ariel Masetto: None declared, Olga Ziouzina: None declared, Dianne Mosher: None declared, Stephanie Keeling: None declared, Sherry Rohekar: None declared, Rana Dadashova: None declared, Joel Paschke: None declared, Amanda Carapellucci: None declared, Robert G Lambert: None declared.

Development and Validation of 3 Preliminary MRI Sacroiliac Joint Composite Structural Damage Scores In a 5-year Longitudinal Axial Spondyloarthritis Study

OBJECTIVE

In axial spondyloarthritis (axSpA), sacroiliac joint (SIJ) erosion is often followed by fat metaplasia in an erosion cavity (backfill), and subsequently ankylosis. We aimed to combine the Spondyloarthritis Research Consortium of Canada (SPARCC) SIJ structural score for erosion, backfill, and ankylosis into 3 versions of a novel preliminary axSpA magnetic resonance imaging (MRI) SIJ Composite Structural Damage Score (CSDS) and to test these.

METHODS

Thirty-three patients with axSpA, followed for 5 years after initiation of tumor necrosis factor inhibitor, had MRIs of the SIJs at baseline, and yearly thereafter. Three versions of CSDS were calculated based on different weightings of erosion, backfill, and ankylosis: (1) equal weighting: CSDS_equal = (erosion × 0.5) + backfill + ankylosis; (2) advanced stages weighting more: CSDS_stepwise = (erosion × 1) + (backfill × 4 ) + (ankylosis × 6); and (3) advanced stages overruling earlier stages ("hierarchical") with "<" meaning "overruled by": CSDS_hierarchical = (erosion × 1) < (backfill × 4) < (ankylosis × 6).

RESULTS

At baseline, all CSDS correlated positively with SPARCC fat and ankylosis scores and modified New York radiography grading, and negatively with the Bath Ankylosing Spondylitis Disease Index and SPARCC SIJ inflammation scores. CSDS_stepwise and CSDS_hierarchical (not CSDS_equal) correlated positively with symptom duration and the Bath Ankylosing Spondylitis Metrology Index, and closer with SPARCC ankylosis score and modified New York radiography grading than CSDS_equal. The adjusted annual progression rate for CSDS_stepwise and CSDS_hierarchical (not CSDS_equal) was higher the first year compared with fourth year (P = 0.04 and P = 0.01). Standardized response mean (baseline to Week 46) was moderate for CSDS_hierarchical (0.64) and CSDS_stepwise (0.59) and small for CSDS_equal (0.25).

CONCLUSION

Particularly CSDS_stepwise and CSDS_hierarchical showed construct validity and responsiveness, encouraging further validation in larger clinical trials. The potential clinical implication is assessment of SIJ damage progression by 1 composite score.

Utility of magnetic resonance imaging in Crohn's associated sacroiliitis: A cross-sectional study

OBJECTIVE

Prevalence of sacroiliitis in Crohn's disease (CD) is variable depending on defining criteria. This study utilized standardized sacroiliac joint (SIJ) magnetic resonance imaging (MRI) to identify sacroiliitis in CD patients and its association with clinical and serological markers.

METHODS

Consecutive adult subjects with CD prospectively enrolled from an inflammatory bowel disease clinic underwent SIJ MRI. Data collected included CD duration, history of joint/back pain, human leukocyte antigen-B27 status, Bath Ankylosing Spondylitis Metrology Index (BASMI), Bath Ankylosing Spondylitis Disease Activity Index, Harvey Bradshaw Index (HBI) for activity of CD, Ankylosing Spondylitis Disease Activity Score, and various serologic markers of inflammation. Three blinded readers reviewed MRIs for active and structural lesions according to the Spondyloarthritis Research Consortium of Canada modules.

RESULTS

Thirty-three CD patients were enrolled: 76% female, 80% White, median age 36.4 years (interquartile range 27.2-49.0), moderate CD activity (mean HBI 8.8 ± SD 4.5). Nineteen subjects (58%) reported any back pain, 13 of whom had inflammatory back pain. Four subjects (12%) showed sacroiliitis using global approach and 6 (18%) met Assessment of SpondyloArthritis international Society MRI criteria of sacroiliitis. Older age (mean 51.2 ± SD 12.5 vs. 37.2 ± 14; P = .04), history of dactylitis (50.0% vs. 3.4%, P = .03) and worse BASMI (4.1 ± 0.7 vs. 2.4 ± 0.8, P ≤ .001) were associated with MRI sacroiliitis; no serologic measure was associated.

CONCLUSION

There were 12%-18% of CD patients who had MRI evidence of sacroiliitis, which was not associated with back pain, CD activity or serologic measures. This data suggests that MRI is a useful modality to identify subclinical sacroiliitis in CD patients.

Data-driven definitions for active and structural MRI lesions in the sacroiliac joint in spondyloarthritis and their predictive utility

Objectives

To determine quantitative SI joint MRI lesion cut-offs that optimally define a positive MRI for inflammatory and structural lesions typical of axial SpA (axSpA) and that predict clinical diagnosis.

Methods

The Assessment of SpondyloArthritis international Society (ASAS) MRI group assessed MRIs from the ASAS Classification Cohort in two reading exercises where (A) 169 cases and 7 central readers; (B) 107 cases and 8 central readers. We calculated sensitivity/specificity for the number of SI joint quadrants or slices with bone marrow oedema (BME), erosion, fat lesion, where a majority of central readers had high confidence there was a definite active or structural lesion. Cut-offs with ≥95% specificity were analysed for their predictive utility for follow-up rheumatologist diagnosis of axSpA by calculating positive/negative predictive values (PPVs/NPVs) and selecting cut-offs with PPV ≥ 95%.

Results

Active or structural lesions typical of axSpA on MRI had PPVs ≥ 95% for clinical diagnosis of axSpA. Cut-offs that best reflected a definite active lesion typical of axSpA were either ≥4 SI joint quadrants with BME at any location or at the same location in ≥3 consecutive slices. For definite structural lesion, the optimal cut-offs were any one of ≥3 SI joint quadrants with erosion or ≥5 with fat lesions, erosion at the same location for ≥2 consecutive slices, fat lesions at the same location for ≥3 consecutive slices, or presence of a deep (i.e. &gt;1 cm depth) fat lesion.

Conclusion

We propose cut-offs for definite active and structural lesions typical of axSpA that have high PPVs for a long-term clinical diagnosis of axSpA for application in disease classification and clinical research.

The three major axes of terrestrial ecosystem function

The leaf economics spectrum^1,2 and the global spectrum of plant forms and functions³ revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species². Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities⁴. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability^4,5. Here we derive a set of ecosystem functions⁶ from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems^7,8.

Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC-based T estimates show higher correlation to sap flow-based T than EC-based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high-quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data-based estimates of ecosystem T permitting a data-driven perspective on the role of plants' water use for global water and carbon cycling in a changing climate.

Drought and heatwave impacts on semi-arid ecosystems' carbon fluxes along a precipitation gradient

The inter-annual variability (IAV) of the terrestrial carbon cycle is tightly linked to the variability of semi-arid ecosystems. Thus, it is of utmost importance to understand what the main meteorological drivers for the IAV of such ecosystems are, and how they respond to extreme events such as droughts and heatwaves. To shed light onto these questions, we analyse the IAV of carbon fluxes, its relation with meteorological variables, and the impact of compound drought and heatwave on the carbon cycle of two similar ecosystems, along a precipitation gradient. A four-year long dataset from 2016 to 2019 was used for the FLUXNET sites ES-LMa and ES-Abr, located in central (39°56'25″ N 5°46'28″ W) and southeastern (38°42'6″ N 6°47'9″ W) Spain. We analyse the physiological impact of compound drought and heatwave on the dominant tree species, Quercus ilex. Our results show that the gross primary productivity of the wetter ecosystem was less sensitive to changes in soil water content, compared to the dryer site. Still, the wetter ecosystem was a source of CO₂ each year, owing to large ecosystem respiration during summer; while the dry site turned into a CO₂ sink during wet years. Overall, the impact of the summertime compound event on annual CO₂ fluxes was marginal at both sites, compared to drought events during spring or autumn. This highlights that drought timing is crucial to determine the annual carbon fluxes in these semi-arid ecosystems. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Impacts of extreme summers on European ecosystems: a comparative analysis of 2003, 2010 and 2018

In Europe, three widespread extreme summer drought and heat (DH) events have occurred in 2003, 2010 and 2018. These events were comparable in magnitude but varied in their geographical distribution and biomes affected. In this study, we perform a comparative analysis of the impact of the DH events on ecosystem CO₂ fluxes over Europe based on an ensemble of 11 dynamic global vegetation models (DGVMs), and the observation-based FLUXCOM product. We find that all DH events were associated with decreases in net ecosystem productivity (NEP), but the gross summer flux anomalies differ between DGVMs and FLUXCOM. At the annual scale, FLUXCOM and DGVMs indicate close to neutral or above-average land CO₂ uptake in DH2003 and DH2018, due to increased productivity in spring and reduced respiration in autumn and winter compensating for less photosynthetic uptake in summer. Most DGVMs estimate lower gross primary production (GPP) sensitivity to soil moisture during extreme summers than FLUXCOM. Finally, we show that the different impacts of the DH events at continental-scale GPP are in part related to differences in vegetation composition of the regions affected and to regional compensating or offsetting effects from climate anomalies beyond the DH centres. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

MRI of the sacroiliac joints in athletes: recognition of non-specific bone marrow oedema by semi-axial added to standard semi-coronal scans

OBJECTIVE

Assessment of combined semi-axial and semi-coronal SI joint MRI in two cohorts of young athletes to explore frequency and topography of non-specific bone marrow oedema (BMO), its association with four constitutional SI joint features, and potential restriction of false-positive assignments of Assessment of SpondyloArthritis International Society-defined sacroiliitis on standard semi-coronal scans alone.

METHODS

Combined semi-axial and semi-coronal SI joint MRI scans of 20 recreational runners before/after running and 22 elite ice-hockey players were evaluated by three blinded readers for BMO and its association with four constitutional SI joint features: vascular partial volume effect, deep iliac ligament insertion, fluid-filled bone cyst and lumbosacral transitional anomaly. Scans of TNF-treated spondyloarthritis patients served to mask readers. We analysed distribution and topography of BMO and SI joint features across eight anatomical SI joint regions (upper/lower ilium/sacrum, subdivided in anterior/posterior slices) descriptively, as concordantly recorded by ⩾2/3 readers on both MRI planes. BMO confirmed on both scans was compared with previous evaluation of semi-coronal MRI alone, which met the Assessment of SpondyloArthritis International Society definition for active sacroiliitis.

RESULTS

Perpendicular semi-axial and semi-coronal MRI scans confirmed BMO in the SI joint of every fourth young athlete, preferentially in the anterior upper sacrum. BMO associated with four constitutional SI joint features was observed in 20-36% of athletes, clustering in the posterior lower ilium. The proportion of Assessment of SpondyloArthritis International Society-positive sacroiliitis recorded on the semi-coronal plane alone decreased by 33-56% upon amending semi-axial scans.

CONCLUSION

Semi-axial combined with standard semi-coronal scans in MRI protocols for sacroiliitis facilitated recognition of non-specific BMO, which clustered in posterior lower ilium/anterior upper sacrum.

Nutrients and water availability constrain the seasonality of vegetation activity in a Mediterranean ecosystem

Anthropogenic nitrogen (N) deposition and resulting differences in ecosystem N and phosphorus (P) ratios are expected to impact photosynthetic capacity, that is, maximum gross primary productivity (GPP_max ). However, the interplay between N and P availability with other critical resources on seasonal dynamics of ecosystem productivity remains largely unknown. In a Mediterranean tree-grass ecosystem, we established three landscape-level (24 ha) nutrient addition treatments: N addition (NT), N and P addition (NPT), and a control site (CT). We analyzed the response of ecosystem to altered nutrient stoichiometry using eddy covariance fluxes measurements, satellite observations, and digital repeat photography. A set of metrics, including phenological transition dates (PTDs; timing of green-up and dry-down), slopes during green-up and dry-down period, and seasonal amplitude, were extracted from time series of GPP_max and used to represent the seasonality of vegetation activity. The seasonal amplitude of GPP_max was higher for NT and NPT than CT, which was attributed to changes in structure and physiology induced by fertilization. PTDs were mainly driven by rainfall and exhibited no significant differences among treatments during the green-up period. Yet, both fertilized sites senesced earlier during the dry-down period (17-19 days), which was more pronounced in the NT due to larger evapotranspiration and water usage. Fertilization also resulted in a faster increase in GPP_max during the green-up period and a sharper decline in GPP_max during the dry-down period, with less prominent decline response in NPT. Overall, we demonstrated seasonality of vegetation activity was altered after fertilization and the importance of nutrient-water interaction in such water-limited ecosystems. With the projected warming-drying trend, the positive effects of N fertilization induced by N deposition on GPP_max may be counteracted by an earlier and faster dry-down in particular in areas where the N:P ratio increases, with potential impact on the carbon cycle of water-limited ecosystems.

SAT0378 THE RELATIVE DIAGNOSTIC UTILITY OF INFLAMMATORY BACK PAIN CRITERIA IN AN INCEPTION COHORT OF PATIENTS WITH PSORIASIS, IRITIS, AND COLITIS PRESENTING WITH UNDIAGNOSED BACK PAIN

Background:

Clinicians rely on the elicitation of features of inflammatory back pain (IBP) for diagnosis of axial spondyloarthritis (axSpA) but the utility of IBP criteria in patients presenting with extra-articular features of axSpA remains unclear. Assessment of utility should include not only rheumatologist diagnosis as benchmark but imaging to address the circularity between elicitation of IBP and clinical diagnosis.

Objectives:

To assess the diagnostic utility of all criteria for IBP in patients with psoriasis, iritis, or colitis and undiagnosed back pain using the rheumatologist diagnosis and imaging as benchmarks.

Methods:

Consecutive patients (n=246) with undiagnosed back pain ≤45 years of age, ≥3 months, with any one of psoriasis (n=46), acute anterior uveitis (AAU)(n=73), or colitis (n=127) had diagnostic evaluation by a rheumatologist. Majority central reader assessment of MRI indicative of axSpA and diagnosis by the rheumatologist were external standards for testing the utility of these IBP criteria: ASAS, Berlin, Calin, rheumatologist global for IBP >5 (0-10 scale).

Results:

AxSpA was diagnosed in 44.4%, 61.6%, and 41.8% of patients with psoriasis, iritis, and IBD, respectively. Diagnostic utility for all IBP criteria was comparably poor (Table 1). MRI was indicative of axSpA in 21.2%, 43.5%, and 19.7% of patients with psoriasis, iritis, and IBD. The utility of the IBP criteria was even worse using MRI as the external reference (Table 2), especially in patients with psoriasis. Only 14% of psoriasis patients with a positive MRI reported “improvement with exercise but not rest” as compared to 70% and 62% of patients with iritis and IBD, respectively.

Table 1.

Rheumatologist diagnosis as external reference.

SensitivitySpecificityLR+LR-PsoriasisASAS IBP65.00%52.00%1.350.67Berlin IBP80.00%36.00%1.250.56Calin IBP80.00%28.00%1.110.71All 3 criteria sets60.00%56.00%1.360.71IBP global >585.00%36.00%1.330.42AAUASAS IBP84.44%42.86%1.480.36Berlin IBP80.00%57.14%1.870.35Calin IBP93.33%17.86%1.140.37All 3 criteria sets77.78%60.71%1.980.37IBP global >586.67%57.14%2.020.23IBDASAS IBP78.43%45.07%1.430.48Berlin IBP82.35%52.11%1.720.34Calin IBP84.31%19.72%1.050.80All 3 criteria sets70.59%57.75%1.670.51IBP global >580.39%66.20%2.380.30Table 2.

Central assessment that MRI is indicative of axSpA as external reference.

SensitivitySpecificityLR+LR-PsoriasisASAS IBP28.57%38.46%0.461.86Berlin IBP42.86%15.38%0.513.71Calin IBP71.43%23.08%0.931.24All 3 criteria sets14.29%42.31%0.252.03IBP global >585.71%23.08%1.110.62AAUASAS IBP75.00%26.92%1.030.93Berlin IBP70.00%38.46%1.140.78Calin IBP90.00%15.38%1.060.65All 3 criteria sets65.00%38.46%1.060.91IBP global >575.00%38.46%1.220.65IBDASAS IBP92.31%37.74%1.480.20Berlin IBP76.92%39.62%1.270.58Calin IBP92.31%16.98%1.110.45All 3 criteria sets76.92%45.28%1.410.51IBP global >592.31%47.17%1.750.16

Conclusion:

All IBP criteria have poor diagnostic utility for diagnosis of axSpA, especially in patients with psoriasis. This reinforces the desirability of less subjective assessment tools, especially imaging.

Disclosure of Interests:

Georg Kröber: None declared, Ulrich Weber: None declared, Raj Carmona: None declared, James Yeung: None declared, Jon Chan: None declared, Sibel Aydin: None declared, Liam Martin: None declared, Ariel Masetto: None declared, Stephanie Keeling: None declared, Olga Ziouzina: None declared, Sherry Rohekar: None declared, Rana Dadashova: None declared, Joel Paschke: None declared, Amanda Carapellucci: None declared, Robert G Lambert: None declared, Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB

FRI0298 ASAS MODIFICATION OF THE BERLIN ALGORITHM AND THE DUET ALGORITHM FOR DIAGNOSING AXIAL SPONDYLOARTHRITIS: RESULTS FROM THE SCREENING IN AXIAL SPONDYLOARTHRITIS FOR PSORIASIS, IRITIS, AND COLITIS COHORT

Background:

Patients presenting with back pain and psoriasis, iritis, or colitis, represent a high-risk population for the presence of axial spondyloarthritis (axSpA). The Dublin Evaluation Tool (DUET)1, the Berlin algorithm2, and the ASAS modification of this algorithm3are recommended referral strategies aimed at early diagnosis of axSpA. DUET was developed for patients presenting with AAU. Validation of these algorithms in inception cohorts is limited.

Objectives:

1. To assess the performance of referral algorithms for diagnosis of axSpA when tested against the final local rheumatologist diagnosis in an inception cohort of patients presenting with undiagnosed back pain and extra-articular manifestations. 2. To determine whether different criteria for inflammatory back pain (IBP) impact the performance of the algorithms.

Methods:

The multicenter Screening for Axial Spondyloarthritis in Psoriasis, Iritis, and Colitis (SASPIC) Study at 11 sites is aimed at early detection of axial SpA in patients presenting with undiagnosed back pain to the rheumatologist. Consecutive patients ≤45 years of age with ≥3 months undiagnosed back pain with any one of psoriasis, acute anterior uveitis (AAU), or colitis diagnosed by the relevant specialist undergo routine clinical evaluation by a rheumatologist for axial SpA. The rheumatologist determines the presence or absence of axial SpA at 3 consecutive stages: 1. After the clinical evaluation; 2. After the results of labs (B27, CRP) and radiography; 3. After the results of MRI evaluation. Final diagnosis by the rheumatologist was used as external standard to test the performance of the algorithms. We tested the following criteria for IBP in the algorithm: ASAS, Berlin, rheumatologist global for likelihood of IBP >5 (0-10 scale), and DUET algorithm in AAU patients.

Results:

A total of 246 patients were recruited, 73 presented with iritis, 46 with psoriasis, and 127 with colitis, 47.6% were diagnosed with axSpA. The diagnosis of axSpA was established in 45.7%, 61.6%, and 40.2% of patients with psoriasis, AAU, and IBD, respectively. The performance of the ASAS-modification of the Berlin algorithm was superior to the original algorithm as reported previously3, primarily for enhanced sensitivity, and this was observed irrespective of the criteria used to define IBP (Table 1). Conversely, the performance of the Duet algorithm in the subset of patients with AAU was substantially worse than previously reported1.

Conclusion:

The ASAS modification of the Berlin algorithm is the preferred referral strategy for patients presenting with undiagnosed back pain to the rheumatologist.

References:

[1]Haroon M, et al. Ann Rheum Dis 2015; 74: 1990-5

[2]Poddubnyy D, et al. J Rheumatol 2011; 38: 2452–60

[3]Van den Berg R, et al. Ann Rheum Dis 2013;72:1646–53

AlgorithmSensitivity (%)Specificity (%)Correct diagnosis (%)False negative (%)False positive (%)Original Berlin(ASAS criteria for IBP)65.376.671.116.712.2Original Berlin(Berlin criteria for IBP)64.476.670.717.112.2Original Berlin(IBP global >5)67.878.173.215.411.4ASAS Modification of Berlin algorithm (ASAS criteria for IBP)73.775.874.812.612.6ASAS Modification of Berlin algorithm (Berlin criteria for IBP)73.775.074.412.613.0ASAS Modification of Berlin algorithm(IBP global >5)76.377.376.811.411.8DUET84.450.071.29.619.2

Disclosure of Interests:

Ulrich Weber: None declared, Georg Kröber: None declared, Raj Carmona: None declared, James Yeung: None declared, Jon Chan: None declared, Sibel Aydin: None declared, Liam Martin: None declared, Ariel Masetto: None declared, Stephanie Keeling: None declared, Olga Ziouzina: None declared, Sherry Rohekar: None declared, Rana Dadashova: None declared, Amanda Carapellucci: None declared, Joel Paschke: None declared, Robert G Lambert: None declared, Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB

FRI0302 WHAT IS THE IMPACT OF DISCREPANCY BETWEEN CENTRAL AND LOCAL READERS IN EVALUATION OF MRI SCANS ON THE CLASSIFICATION OF AXIAL SPONDYLOARTHRITIS? DATA FROM THE ASAS CLASSIFICATION COHORT STUDY

Background:

Active MRI lesions typical of axial spondyloarthritis (axSpA) were reported in 61.6% and 2.2% of axSpA and not-axSpA patients, respectively, from the ASAS classification cohort (ASAS-CC)1. Discrepancy between local and central reader evaluation of MRI scans could result in differences in numbers of patients fulfilling the imaging arm of the ASAS classification criteria. But final classification may not be impacted if discrepant patients still fulfill the clinical arm.

Objectives:

We aimed to assess the impact of reader discrepancy in detection of active MRI lesions on the number of patients classified as having axSpA in patients recruited to the ASAS-CC.

Methods:

MRI images of the sacroiliac joints (SIJs) were available from 252 cases in the ASAS-CC, and these also had clinical and radiographic data. Seven central readers from the ASAS-MRI group recorded MRI lesions in an eCRF that included active lesions typical of axSpA in the SIJ (MRI-active) that was worded exactly the same as in the original ASAS-CC eCRF permitting comparisons between central and local site readers. Active lesions were deemed to be present according to majority agreement (≥4/7) of central readers and also any 2 central readers. We calculated the number of patients that were classified differently after central evaluation for overall fulfilment of the ASAS criteria and for the imaging arm.

Results:

Discordance between central and local readers for detection of MRI-active was recorded in 45(17.8%) and 47(18.2%) of cases according to 2-reader and majority (≥4/7) central reader data, respectively (kappa (95%CI) of 0.64 (0.54-0.73) and 0.62 (0.53-0.72). With central reading as external standard the false-positive rate for active lesions was 26.9%% and 32.2% (‘local overcall’) for 2-reader and majority reader data, respectively. There were 159(63.1%) patients who fulfilled the ASAS axSpA criteria based on local-reading, and 148(58.7%) and 143(56.7%) patients based on 2-reader and majority central-reading, respectively (Table). When fulfillment of the imaging arm was the primary consideration (irrespective of the clinical arm), 126 (50%) patients fulfilled the criteria based on local-reading, and 111 (44%) and 102 (40.5%) patients based on 2-reader and majority central-reading, respectively.

Conclusion:

Despite substantial overcall for positive MRI SIJ inflammation by local readers, the number of patients classified as having axSpA did not change substantially. This is due to the alternate mechanism for classification through the clinical arm.

References:

[1]Rudwaleit et al. Ann Rheum Dis 2009;68: 777-83

Impact of Central Vs. Local Reader SIJ MRI Inflammation Assessment on SpA Classification in cases with all clinical, radiographic, and central and local MRI inflammation data available (n=252)MRI assessment usedSpA Classification = Yes N(%)SpA Classification = No N(%)Imaging Arm SpA Classification = Yes N(%)Imaging Arm SpA Classification = No N(%)Local Reader MRI positive159 (63.1%)93 (36.9%)126 (50%)126 (50%)>2 Central Reader MRI positive148 (58.7%)104 (41.3%)111 (44.0%)141 (56.0%)Majority Central Reader (≥4/7) MRI positive143 (56.7%)109 (43.2%)102 (40.5%)150 (59.5%)

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Susanne Juhl Pedersen Grant/research support from: Novartis, Ulrich Weber: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Joel Paschke: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Robert G Lambert: None declared

OP0079 PRELIMINARY DEFINITION OF A POSITIVE MRI FOR STRUCTURAL LESIONS IN THE SACROILIAC JOINTS IN AXIAL SPONDYLOARTHRITIS

Background:

There is lack of international consensus as to what defines a structural lesion on MRI of the sacroiliac joints (SIJ) typical of axial spondyloarthritis (axSpA). The ASAS MRI group has generated updated consensus lesion definitions that describe each of the MRI lesions in the SIJ1. These definitions have been evaluated by 7 readers from the ASAS-MRI group on MRI images from the ASAS Classification Cohort.

Objectives:

We aimed to identify quantitative cut-offs based on numbers of slices and SIJ quadrants that define a positive MRI for structural lesions typical of axSpA, the gold standard being majority central reader decision as to the presence of a structural lesion typical of axSpA with high confidence.

Methods:

MRI structural lesions meeting ASAS definitions were recorded in an eCRF that comprises global assessment (structural lesion typical of axSpA present/absent and degree of confidence (-4 (absent) to +4 (present)), and detailed scoring of lesions per SIJ quadrant. Detailed scoring was based only on assessment of DICOM images (n =148). We calculated sensitivity and specificity for numbers of SIJ quadrants and consecutive slices with erosion, sclerosis, and fat lesions where a majority of readers (≥4/7) agreed as to the presence of a structural lesion typical of axSpA with high confidence (≥ +3). We tested candidate lesion definitions for predictive diagnostic utility in cases assessed after 4.4 years of follow up by the local rheumatologist.

Results:

Structural lesions typical of axSpA were observed by majority read in 33 (32.4%) of 102 cases diagnosed with axSpA, and 3 (6.8%) of 44 cases without axSpA and 29 cases were assigned a high degree of confidence (≥ +3) by a majority of readers. Cut-offs achieving specificity of 95% were erosion in ≥2 consecutive slices (sensitivity 83%), erosion ≥3 SIJ quadrants (sensitivity 90%), and fat lesion (≥1cm horizontal depth) in ≥1 SIJ quadrant (sensitivity 59%) (Table). These had very high positive predictive values (>95%) for diagnosis of axSpA in cases diagnosed by the rheumatologist after 4.4 years follow up.

Conclusion:

ASAS-defined erosion in ≥2 consecutive slices or in ≥3 SIJ quadrants and ASAS-defined fat lesion with depth >1cm in ≥1 SIJ quadrant are high priority candidates for defining an MRI structural lesion typical of axSpA. This will require similar assessment in additional axSpA cohorts.

References:

[1]Maksymowych et al. Ann Rheum Dis 2019; 78:1550-8.

Table 1.

Majority readers agree structural lesion indicative of axSpA is present with confidence ≥3/4 is the gold-standard external reference

SensitivitySpecificityErosion Score ≥1 SIJ qdr93.1 (77.2-99.2)80.6 (72.4-87.3)Erosion Score ≥2 SIJ qdr93.1 (77.2-99.2)90.8 (84.1-95.3)Erosion Score ≥3 SIJ qdr89.7 (72.6-97.8)95.8 (90.5-98.6)Erosion in 2 consecutive slices82.8 (64.2-94.2)95.0 (89.3-98.1)Fat lesion ≥1 SIJ qdr82.8 (64.2-94.2)81.5 (73.4-88.0)Fat lesion ≥2 SIJ qdr69.0 (49.2-84.7)86.6 (79.1-92.1)Fat lesion ≥3 SIJ qdr62.1 (42.3-79.3)91.6 (85.1-95.9)Fat lesion in 2 consecutive slices55.2 (35.7-73.6)93.3 (87.2-97.1)Fat lesion (>1cm depth) ≥158.6 (38.9-76.5)95.0 (89.3-98.1)Fat lesion (>1cm depth) ≥255.2 (35.7-73.6)95.8 (90.5-98.6)Fat lesion (>1cm depth) ≥351.7 (32.5-70.6)97.5 (92.8-99.5)Fat lesion (>1cm depth) in 2 consecutive slices48.3 (29.4-67.5)97.5 (92.8-99.5)

Table. SIJ qdr: sacroiliac joint quadrant

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Xenofon Baraliakos: None declared, Ulrich Weber: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Susanne Juhl Pedersen Grant/research support from: Novartis, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Joel Paschke: None declared, Robert G Lambert: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB

SAT0384 REPLACEMENT OF RADIOGRAPHIC SACROILITIS BY MRI STRUCTURAL LESIONS: WHAT IS THE IMPACT ON CLASSIFICATION OF AXIAL SPONDYLOARTHRITIS IN THE ASAS CLASSIFICATION COHORT?

Background:

Classification of axial spondyloarthritis (axSpA) is based on either an imaging or clinical arm. Radiographic or MRI evidence of sacroiliitis can be applied for the imaging arm. However, it is well-established that reliability and sensitivity of radiographic sacroiliitis is inadequate.

Objectives:

To assess the impact of replacing radiographic sacroiliitis with MRI structural lesions (MRI-S) typical of axSpA on the number of patients classified as having axSpA in patients with undiagnosed back pain recruited to the ASAS Classification Cohort (ASAS-CC).

Methods:

MRI images of the sacroiliac joint (SIJ) were available from 217 cases in the ASAS-CC, which also had clinical, laboratory, and radiographic data. Seven central readers from the ASAS-MRI group recorded MRI lesions in an eCRF that included active (MRI-A) and structural (MRI-S) lesions typical of axSpA. MRI-A was deemed to be present according to majority agreement (≥4/7) of central readers. MRI-S was deemed to be present according to the majority (majority reader MRI-S) and also according to at least 2 central readers (≥2-reader MRI-S). We calculated the number of patients that were classified differently after replacement of radiographs by MRI-S for overall fulfillment of the ASAS criteria and for the imaging arm.

Results:

In total, 119 (54.8%) cases fulfilled the axSpA criteria based on local reading of radiographic sacroiliitis and central reading of active inflammation on MRI. This changed to 125 (57.6%) and 118 (54.4%) of cases after replacement of radiographic sacroiliitis by ≥2-reader and majority reader MRI-S, respectively (Table). A total of 13 (6.0%) and 7 (3.2%) cases who were classified as not having axSpA were re-classified as having axSpA after replacing radiographic sacroiliitis with ≥2-reader and majority reader MRI-S, respectively. Conversely, 7 (3.2%) and 8 (3.7%) cases were re-classified as not having axSpA after substitution by ≥2-reader and majority reader MRI-S, respectively. When fulfillment of the imaging arm was the primary consideration (irrespective of the clinical arm), the number of patients reclassified from not axSpA to axSpA was 25 (11.5%) by ≥2-reader and 13 (6.0%) by majority reader MRI-S, while 8 (3.7%) and 11 (5.1%) were reclassified from axSpA to not axSpA.

Conclusion:

The number of patients classified as having axSpA does not change substantially when MRI-S replaces radiographic sacroiliitis. However, it remains possible that MRI structural lesions can influence the final diagnosis, the gold standard for assessment of the performance of the ASAS criteria.

Impact of Replacement of Radiographic Sacroilitis by MRI Structural Lesions on SpA Classification in cases with all clinical, radiographic, and central and local MRI inflammation data available (n=217)

MRI assessment usedSpA Classification=Yes N(%)SpA Classification=No N(%)Imaging Arm SpA Classification=Yes N(%)Imaging Arm SpA Classification=No N(%)Radiographic Sacroiliitis + Majority Central Reader MRI Inflammation Positive119 (54.8%)97 (44.7%)83(38.2%)134 (61.8%)Replace Radiographic Sacroiliitis with ≥2 Central Reader MRI Structural Positive125 (57.6%)92 (42.4%)100 (46.1%)117 (53.9%)Replace Radiographic Sacroiliitis with Majority Central Reader MRI Structural Positive118 (54.4%)99 (45.6%)85 (39.2%)132 (60.8%)

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Robert G Lambert: None declared, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Joel Paschke: None declared, Susanne Juhl Pedersen Grant/research support from: Novartis, Ulrich Weber: None declared

FRI0317 CONSENSUS DEFINITIONS FOR MRI LESIONS IN THE SPINE OF PATIENTS WITH AXIAL SPONDYLOARTHRITIS: FIRST ANALYSIS FROM THE ASSESSMENTS IN SPONDYLOARTHRITIS INTERNATIONAL SOCIETY CLASSIFICATION COHORT

Background:

A recent consensus from the ASAS MRI group has culminated in updated spine lesion definitions for axial spondyloarthritis (ASAS_MRI_defn)1. There has been no central reader evaluation of MRI scans from the ASAS Classification Cohort (ASAS-CC)2to determine the spectrum of MRI lesions in the spine in this cohort.

Objectives:

To determine the spectrum of active and structural lesions on MRI images of the spine from the ASAS-CC according to the consensus ASAS_MRI_defnupdate.

Methods:

ASAS_MRI_defnwere recorded by 9 central readers in an eCRF for global assessment and detailed scoring of each discovertebral unit and postero-lateral structures. Vertebral corner bone marrow edema (VCBME) and corner fat (VCFAT) lesions were recorded if present on 2 slices; facet joint, lateral, and posterior inflammatory lesions were recorded if present on a single slice. Vertebral corner erosion, bone spurs, and ankylosis were each scored on a single slice. Comparison of active and structural lesion frequencies by local rheumatologist diagnosis of axSpA was assessed descriptively according to ≥2 and majority reader (≥5/9) concordant data.

Results:

MRI scans of the spine were available from 69 cases with axSpA diagnosed in 44/64 (68.8%). VCBME was most frequent with ≥1 lesion in 32(46.4%) and 19 (27.5%) by ≥2 and ≥5/9 readers, respectively. VCFAT was the most frequent structural lesion with ≥1 lesion in 24 (34.8%) and 14 (20.3%) by ≥2 and ≥5/9 readers, respectively. There were significantly more VCBME lesions in axSpA patients than non-axSpA (mean(SD):1.8(2.7) vs 0.3 (0.5)) (p<0.001) while differences in VCFAT were not significant (Table). The presence of ≥2 VCBME had 90-95% specificity for axSpA. Significantly more VCBME and VCFAT were observed in the setting of radiographic sacroiliitis (modified New York criteria (mNY)).

Conclusion:

Spine lesions on MRI are relatively frequent in patients with undiagnosed back pain presenting to the rheumatologist. The presence of ≥2 VCBME, but not VCFAT, may have some diagnostic utility.

References:

[1]Maksymowych WP, et al. Arthritis Rheumatol 70 (suppl 10): 654, 2018

[2]Rudwaleit et al. Ann Rheum Dis 2009;68: 777-83

Vertebral Corner MRI lesionsmajority of readers (>=5)≥2 readersaxSpA=Yes (n=44)axSpA=No (n=20)p-valueaxSpA=Yes (n=44)axSpA=No (n=20)p-valueCorner Fat ≥112 (27.3%)2 (10%)0.1917 (38.6%)7 (35%)0.78Corner Fat ≥210 (22.7%)2 (10%)0.3113 (29.5%)4 (20%)0.64Corner Fat ≥38 (18.2%)1 (5%)0.2510 (22.7%)3 (15%)0.74Corner Fat ≥47 (15.9%)1 (5%)0.429 (20.5%)2 (10%)0.48Corner BME ≥117 (38.6%)1 (5%)0.00625 (54.5%)6 (30%)0.047Corner BME ≥215 (34.1%)1 (5%)0.01319 (43.2%)2 (10%)0.009Corner BME ≥311 (25%)0 (0%)0.01316 (36.4%)1 (5%)0.008Corner BME ≥48 (18.2%)0 (0%)0.09412 (27.3%)1 (5%)0.048mNY=Yes (n=10)mNY=No (n=49)p-valuemNY=Yes (n=10)mNY=No (n=49)p-valueCorner Fat ≥15 (50%)9 (18.4%)0.0475 (50%)17 (34.7%)0.48Corner Fat ≥25 (50%)7 (14.3%)0.0225 (50%)11 (22.4%)0.12Corner Fat ≥34 (40%)5 (10.2%)0.0364 (40%)9 (18.4%)0.20Corner Fat ≥44 (40%)4 (8.2%)0.0224 (40%)7 (14.3%)0.079Corner BME ≥15 (50%)11 (22.4%)0.1167 (70%)22 (44.9%)0.18Corner BME ≥25 (50%)9 (18.4%)0.0475 (50%)14 (28.6%)0.27Corner BME ≥35 (50%)6 (12.2%)0.0145 (50%)11 (22.4%)0.12Corner BME ≥45 (50%)3 (6.1%)0.0025 (50%)7 (14.3%)0.022

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Iris Eshed: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Susanne Juhl Pedersen Grant/research support from: Novartis, Ulrich Weber: None declared, Manouk de Hooge: None declared, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Robert G Lambert: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen