OP0147 RHEUMATIC? - A DIGITAL DIAGNOSTIC DECISION SUPPORT TOOL FOR INDIVIDUALS SUSPECTING RHEUMATIC DISEASES: A MULTICENTER VALIDATION STUDY

Background:

Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations for individuals suspecting a rheumatic disease.1,2 The tool can be used by people suspicious for rheumatic diseases resulting in individual advise on eventually seeking further health care.

Objectives:

We tested Rheumatic? for its ability to differentiate symptoms from immune-mediated diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.

Methods:

The performance of Rheumatic? was tested using data from 175 patients from three university rheumatology centers covering two different settings:

A.Risk-RA phase setting. Here, we tested whether Rheumatic? could predict the development of arthritis in 50 at risk-individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity from the KI (Karolinska Institutet)

B.Early arthritis setting. Here, we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic disease in i) EUMC (Erlangen) n=52 patients and ii) LUMC (Leiden) n=73 patients.

In each setting, we examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC).

Results:

In setting A, the total test score clearly differentiated between individuals developing arthritis or not, median 245 versus 163, P < 0.0001, AUC-ROC = 75.3 (Figure 1). Also within patients with arthritis the Rheumatic? total score was significantly higher in patients developing an immune-mediated arthritic disease versus those who did not: median score EUMC 191 versus 107, P < 0.0001, AUC-ROC = 79.0, and LUMC 262 versus 212, P < 0.0001, AUC-ROC = 53.6.

Figure 1.

(Area under) the receiver operating curve for the total Rheumatic? score

Conclusion:

Rheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. A following subject of research is how the tool performs in a population-wide setting.

References:

[1]Knitza J. et al. Mobile Health in Rheumatology: A Patient Survey Study Exploring Usage, Preferences, Barriers and eHealth Literacy. JMIR mHealth and uHealth. 2020.

[2]https://rheumatic.elsa.science/en/

Acknowledgements:

This project has received funding from EIT Health. EIT Health is supported by the European Institute of Innovation and Technology (EIT), a body of the European Union that receives support from the European Union’s Horizon 2020 Research and Innovation program.

This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777357, RTCure.

Disclosure of Interests:

Rachel Knevel: None declared, Johannes Knitza: None declared, Aase Hensvold: None declared, Alexandra Circiumaru: None declared, Tor Bruce Employee of: Ocean Observations, Sebastian Evans Employee of: Elsa Science, Tjardo Maarseveen: None declared, Marc Maurits: None declared, Liesbeth Beaart- van de Voorde: None declared, David Simon: None declared, Arnd Kleyer: None declared, Martina Johannesson: None declared, Georg Schett: None declared, Thomas Huizinga: None declared, Sofia Svanteson Employee of: Elsa Science, Alexandra Lindfors Employee of: Ocean Observations, Lars Klareskog: None declared, Anca Catrina: None declared

POS0709 LUPUS FOG IS NOT DISSOCIATIVE FOG

Background:

The presence of a ‘fog’ is frequently reported by patients with systemic lupus erythematosus (SLE). However, little is known about this lupus fog: it is thought to be a result of cognitive dysfunction, but fogs can also be the result of dissociation. The Dissociative Experience Scale-II (DES) is a standardized tool to study dissociation. In the general adult population, scores range from 4.4-14.1-3

Objectives:

We aimed to study the prevalence of dissociative symptoms including dissociative fog in patients with SLE and neuropsychiatric symptoms.

Methods:

Patients visiting the tertiary referral center for neuropsychiatric systemic lupus erythematosus (NPSLE) of the LUMC between 2007-2019 were included. All patients underwent a standardized multidisciplinary assessment. Patients were classified as NPSLE if neuropsychiatric symptoms were attributed to SLE and immunosuppressive or anticoagulant therapy was initiated, otherwise patients were classified as minor/non-NPSLE. Dissociation was studied using the DES. The DES separates different types of dissociative symptoms: amnesia, absorption/imagination and derealization/depersonalization. It also contains one question regarding evaluating the presence of a dissociative fog: “Some people sometimes feel as if they are looking at the world through a fog, so that people and objects appear far away or unclear”. All statements (n = 28) regarding dissociative symptoms are rated from ‘none of the time’ to ‘all of the time’ (0-100%); scores >25 are considered abnormal. A multiple regression analysis (MRA) were performed to compare dissociation in patients with and without NPSLE. DES results are presented as median (range) and MRA as odds ratio (OR) and 95% confidence interval (CI).

Results:

DES questionnaires were available for 337 patients, of which 97 had the diagnosis NPSLE (29%). Mean age in patients with NPSLE was 41 ± 13 years and 84% was female. In minor/non-NPSLE, median age was 44 ± 14 years and 87% was female.

Median dissociation was 7 (0-75) and did not differ between patients with minor/non-NPSLE and NPSLE (OR: 1.0 (95% CI: -0.9; 1.1)). The most common type of dissociation was absorption/imagination (median: 12, range 0-75) and depersonalization/derealization was infrequent (median: 1, range 0-84). 43 patients (13%) had an abnormal score (>25) on the dissociative fog question.

Conclusion:

Dissociative symptoms are within normal range in patients with SLE and neuropsychiatric symptoms, regardless of underlying etiology. Dissociative fog seems uncommon and therefore lupus fog is most likely not the result of dissociation.

References:

[1]Bernstein EM and Putnam FW. Development, reliability, and validity of a dissociation scale. J Nerv Ment Dis 1986; 174: 727-735. 1986/12/01. DOI: 10.1097/00005053-198612000-00004.

[2]Maaranen P, Tanskanen A, Honkalampi K, et al. Factors associated with pathological dissociation in the general population. Aust N Z J Psychiatry 2005; 39: 387-394. 2005/04/30. DOI: 10.1080/j.1440-1614.2005.01586.x.

[3]van IJzendoorn MH and Schuengel C. The measurement of dissociation in normal and clinical populations: Meta-analytic validation of the Dissociative Experiences Scale (DES). Clinical Psychology Review 1996; 16: 365-382. DOI: 10.1016/0272-7358(96)00006-2.

Table 1.

Presence of dissociation in patients with SLE and neuropsychiatric symptoms

Total cohort(n = 337)Minor/non-NPSLE(n = 240)NPSLE(n = 97)DES (median, range)Total questionnaire7 (0 - 75)8 (0 - 66)6 (0 – 75)Amnesia5 (0 - 76)5 (0 - 68)4 (0 - 76)Absorption/imagination12 (0 – 75)13 (0 – 75)10 (0 – 73)Depersonalization/derealization1 (0 – 84)1 (0 – 73)1 (0 – 84)Dissociative fog* 0 (0-100)0 (0-100)0 (0-100)

DES = Dissociative Experience Scale NPSLE = neuropsychiatric systemic lupus erythematosus.

*Dissociative fog is question 28 of the DES-II

Disclosure of Interests:

None declared

POS0708 PSYCHIATRIC DISORDERS IN PATIENTS WITH DIFFERENT PHENOTYPES OF NEUROPSYCHIATRIC SYSTEMIC LUPUS ERYTHEMATOSUS (NPSLE)

Background:

Patients with systemic lupus erythematosus (SLE) may present with psychiatric disorders. These are important to recognize, as they influence quality of life and treatment outcomes and strategies.

Objectives:

We aimed to study the frequency of psychiatric morbidity as classified by the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) in patients with SLE and neuropsychiatric symptoms of different origins.

Methods:

In the neuropsychiatric SLE (NPSLE) clinic of the Leiden University Medical Center, patients undergo a standardized multidisciplinary assessment by a neurologist, neuropsychologist, vascular internal medicine, rheumatologist, physician assistant and psychiatrist. After two weeks, a multidisciplinary consensus meeting takes place, in which the symptoms are attributed to SLE requiring treatment (major NPSLE) or to minor involvement of SLE or other causes (minor/non-NPSLE). Consecutive patients visiting the NPSLE clinic between 2007-2019 were included. Data of psychiatric evaluation and current medication use were extracted from medical records. The presence of cognitive dysfunction was established during formal neuropsychological assessment.

Results:

371 consecutive SLE patients were included, of which 110 patients had major NPSLE (30%). Mean age was 44 ± 14 years and 87% was female.

The most frequently diagnosed psychiatric disorders in the total group were cognitive dysfunction (42%) and depression (23%), as shown in Table 1. Furthermore, anxiety was present in 5% and psychotic disorders in 4% of patients. In patients with minor/non-NPSLE, especially depression (26% vs 15%) and anxiety (6% vs 2%) were more common than in major NPSLE. Cognitive dysfunction (54% vs 36%) and psychotic disorders (6% vs 4%) were more common in patients with major NPSLE than minor/non-NPSLE.

Psychiatric medication was used in 33% of patients, of which antidepressants and benzodiazepines the most frequently (both: 18% in both subgroups). Antipsychotics were more often used in patients with NPSLE (10% vs 7%) and benzodiazepines more often in minor/non-NPSLE (20% vs 14%).

In addition, 17 patients (5%) had a history of suicide attempt, which was more common in patients with minor/non-NPSLE than major NPSLE (6% vs 2%).

Conclusion:

Psychiatric morbidity, especially cognitive dysfunction and depression, are common in patients with lupus and differ between underlying cause of the neuropsychiatric symptoms (minor/non-NPSLE vs major NPSLE).

Table 1.

Presence of psychiatric diagnoses in patients with SLE and neuropsychiatric symptoms

All patients(n = 371)Minor/non-NPSLE(n = 261)Major NPSLE(n = 110)DSM V diagnosis, n (%)Neurodevelopmental disorder5 (1)2 (1)3 (2)Schizophrenia Spectrum and Other Psychotic Disorders16 (4)10 (4)6 (6)Bipolar and related disorders7 (2)5 (2)2 (2)Depressive disorders84 (23)68 (26)16 (15)Anxiety disorders17 (5)15 (6)2 (2)Obsessive-Compulsive and Related Disorders1 (0)1 (0)0 (0)Trauma- and Stressor-Related Disorders16 (4)12 (5)4 (3)Dissociative Disorders2 (1)2 (1)0 (0)Somatic Symptom and Related Disorders1 (0)1 (0)0 (0)Feeding and Eating Disorders0 (0)1 (0)0 (0)Elimination Disorders0 (0)0 (0)0 (0)Sleep-wake disorders2 (1)2 (1)0 (0)Sexual dysfunctions0 (0)0 (0)0 (0)Gender dysphoria0 (0)0 (0)0 (0)Disruptive, Impulse-Control, and Conduct Disorder0 (0)0 (0)0 (0)Substance-related and addictive disorders9 (2)8 (3)1 (1)Cognitive dysfunction154 (42)95 (36)59 (54)Personality disorders10 (3)9 (3)1 (1)Paraphilic disorders0 (0)0 (0)0 (0)Other mental disorders12 (3)7 (3)5 (5)Medication-Induced Movement Disorders and Other Adverse Effects of Medication0 (0)0 (0)0 (0)Unknown3 (1)3 (1)0 (0)

NPSLE = neuropsychiatric systemic lupus erythematosus.

Disclosure of Interests:

None declared

POS0479 THE IMPACT OF FLARES ON PATIENT REPORTED OUTCOMES IN RHEUMATOID AND UNDIFFERENTIATED ARTHRITIS PATIENTS – A SUB-ANALYSIS OF THE IMPROVED STUDY

Background:

In rheumatoid arthritis (RA) patients in low disease activity, flares are associated with symptom deterioration. Patients in clinical remission may flare but still have low disease activity. How does this affect patient reported outcomes?

Objectives:

To evaluate the prevalence of disease flares in patients treated to target drug free remission, and to study the impact of disease flares on patient-reported outcomes (PROs) for flares with different impact on disease activity.

Methods:

In the IMPROVED study 610 patients with rheumatoid arthritis (RA) or undifferentiated arthritis (UA) were treated to target drug free remission (DAS <1.6) for 5 years. As soon as DAS was <1.6, treatment was tapered to discontinuation. Patients with at least 8 months follow-up were selected. A flare was defined according to three definitions; A) DAS ≥1.6 and ≥0.6 increase from the previous visit regardless of the previous DAS; B) minor flare from remission; a DAS ≥1.6 with <0.6 increase and previous DAS <1.6; C) major flare from remission; a DAS ≥1.6 with ≥0.6 increase and previous DAS <1.6. Linear mixed models were used to compare functional ability, measured by the health assessment questionnaire (HAQ), at visits where a flare occurred versus visits without a flare. Fisher’s exact test were used to compare percentages with ≥0.22 HAQ increases between groups with and without LDA at the moment of flare. A generalized linear mixed model was used to calculate the odds ratio for a deterioration of ≥20 mm in VAS of PROs global health (GH), disease activity, pain and morning stiffness (from the preceding visit) during a flare.

Results:

Of the 585 patients with sufficient follow-up, 75% experienced a flare A, 26% a flare B, and 68% a flare C, at least once. Most flares were observed after t=8 and t=12 months. In 55%, 100%, and 69% of visits with a flare A, B or C, the patients were still in LDA (DAS=<2.4). In 55% of the visits where a flare was associated with a DAS increase ≥0.6 (flare A & C) there was also clinically relevant increase in HAQ of ≥0.22. The mean difference in HAQ was 0.27 with flare A (p<0.01), 0.03 with flare B (p=0.72) and 0.18 with flare C (p<0.01). If was DAS >2.4 (LDA) at the moment of flare, HAQ increased ≥0.22 in 68% of all flares A, and 77% of all flares C (p-values <0.01, compared to flares where patients were still in LDA, DAS=<2.4). The odds ratios of a >20 mm deterioration in VAS global health, VAS disease activity, VAS pain and VAS morning stiffness was significant ≥1 for flares with a ≥0.6 increase in DAS (flares A and C), and ≤1 for minor flares (B) (table 1).

Conclusion:

In early arthritis patients, during 5 years treated to target drug free DAS-remission, disease flares with loss of DAS-remission were common. Although the majority of patients who flared were still in LDA, most reported more pain, morning stiffness, increased disease activity and a diminished global health. On average, deterioration in HAQ only exceeded the minimum clinically important difference (delta HAQ >=0.22) in case of a ≥0.6 increase in DAS, independent of the previous DAS. Depending on the definition of flare, up to 45% of patients lost DAS LDA, and in this group the functional deterioration significantly more often exceeded the MCID as compared to the patients that flared but were still in LDA. More research is needed to find out which patients are most at risk for clinically relevant flares, and to evaluate the impact of flares in patients with remission on long term outcomes.

Table 1.

Odds Ratios and 95% confidence intervals for > 20 mm increase in PROs on 100mm visual analogue scales

Flare AFlare B (minor)Flare C (major)Prevalence ≥20 mmaOR(95% CI)Prevalence ≥20 mmaOR(95% CI)Prevalence ≥20 mmaOR(95% CI)Global health62%2.1 (1.5; 2.8)45%0.5 (0.4; 0.7)62%1.4 (1.1; 1.8)Disease activity62%2.5 (1.7; 3.8)45%0.4 (0.3; 0.6)62%2.1 (1.4; 3.0)Pain87%2.0 (1.3; 3.1)78%0.5 (0.3; 0.8)87%1.8 (1.2; 2.5)Morning stiffness84%1.7 (1.1; 2.6)77%0.6 (0.4; 0.9)86%2.1 (1.5; 2.9)

a The prevalence of >20 mm deterioration in VAS PRO’s during a visit with a flare.

Acknowledgements:

We would like to thank all patients for their contribution as well as the rheumatologists who participated in the IMPROVED-study group. We would also like to thank all other rheumatologists and trainee rheumatologists who enrolled patients in these studies, and all research nurses for their contributions.

Disclosure of Interests:

Johanna M. Maassen: None declared, Sytske Anne Bergstra: None declared, Petronella DM de Buck: None declared, M. van Oosterhout: None declared, Thomas Huizinga: None declared, Cornelia Allaart Grant/research support from: the IMPROVED study was designed by the investigators and financially supported by AbbVie in the first year.

POS0386 EVOLUTION OF ANTI-MODIFIED PROTEIN ANTIBODY RESPONSES CAN BE DRIVEN BY CONSECUTIVE EXPOSURE TO DIFFERENT POST-TRANSLATIONAL MODIFICATIONS

Background:

Besides anti-citrullinated protein antibodies (ACPA), rheumatoid arthritis patients (RA) often display autoantibody reactivities against other post-translationally modified (PTM) proteins, more specifically carbamylated and acetylated proteins. Immunizing mice with one PTM results in an anti-modified protein antibody (AMPA) response recognizing multiple PTMs. Furthermore, human AMPA, isolated based on their reactivity to one PTM, cross-react with other PTMs at the monoclonal and polyclonal level. However, it is unclear whether the AMPA reactivity profile is “fixed” in time, or whether consecutive exposure to different PTMs can shape the evolving AMPA-response.

Objectives:

To investigate the evolution of the AMPA response in mice with controlled exposure to PTMs as well as in AMPA-positive humans.

Methods:

Mice were immunized with acetylated (or carbamylated) protein (ovalbumin) twice or cross-immunized with an acetylated and then a carbamylated protein (or vice versa) and their serum was analyzed for AMPA responses with ELISA using a different backbone protein (fibrinogen) bearing the same modifications. Longitudinally collected serum samples of human individuals at risk of RA and with early RA were tested to investigate the evolution of the AMPA responses in humans.

Results:

Mice immunized twice with either solely acetylated or solely carbamylated ovalbumin (AcOVA or CaOVA) developed reactivity against both acetylated and carbamylated antigens. Irrespective of the PTM used for the first immunization, a booster immunization with the other PTM resulted in increased titers to the second/booster PTM (Figure 1A), suggesting that immunization with a defined PTM-antigen leads to the generation of anti-PTM memory B cells able to cross-recognize other PTMs. Furthermore, immunizing with CaOVA and boosting with AcOVA (or vice versa) skewed the overall AMPA-response profile towards a relatively higher reactivity against the “booster” PTM (Figure 1B). Human data also illustrated dynamic changes in AMPA reactivity profiles in both individuals at risk of RA and in early RA patients (not shown).

Conclusion:

The relationship between different reactivities within the AMPA response is dynamic. The initial exposure to a PTM antigen induces cross-reactive response that can be boosted by the same or other PTMs. The overall reactivity pattern can be skewed by subsequent exposure to other PTMs. These data might explain temporal changes in the reactivity profile of the AMPA response and point to the possibility that the PTM responsible for the initiation of the AMPA response may differ from the PTM predominantly recognized later in time.

Disclosure of Interests:

None declared

POS0470 GLUCOCORTICOID DISCONTINUATION IN EARLY RHEUMATOID AND UNDIFFERENTIATED ARTHRITIS PATIENTS. A SUB-ANALYSIS OF THE BeSt AND IMPROVED STUDIES

Background:

Discontinuation of glucocorticoids (GC) as bridging therapy in rheumatoid arthritis (RA) treatment is recommended as rapidly as clinically feasible. Little is known about the rate of, and possible characteristics associated with successful GC discontinuation.

Objectives:

To evaluate the success rate of GC discontinuation, and to study which factors are associated with successful GC discontinuation.

Methods:

Data from two treat-to-target studies; BeSt (target DAS ≤2.4, LDA), and IMPROVED (target DAS <1.6, remission) were evaluated for all patients initially treated with a tapered high-dose of oral GC with conventional DMARD(s). GCs were discontinued when DAS ≤2.4 was maintained for 28 weeks in BeSt, and as soon as DAS was <1.6 in IMPROVED. GC discontinuation could be attempted twice: first attempt called ‘primary’, second attempt after GC restart called ‘secondary’. Discontinuation was considered successful if the treatment target was maintained at the next visit. Univariable, and exploratory forward and backward multivariable logistic regression analyses were performed to identify potential characteristics associated with successful discontinuation (p-value <0.2 included in final model).

Results:

From the 131 patients initiating combination therapy with prednisone in the BeSt study, 93 attempted discontinuation. Primary discontinuation was successful in 60% (56/93) and secondary discontinuation in 54% (19/35). A lower DAS at the visit prior to GC discontinuation and ACPA negativity were associated with successful discontinuation (table 1). Of the 610 patients in the IMPROVED, 400 attempted discontinuation. Primary discontinuation was successful in 61% (242/400), and secondary in 51% (71/139). A lower DAS both at baseline and at the visit prior to GC discontinuation were associated with successful discontinuation (table 1).

Conclusion:

Primary GCs discontinuation was successful in approximately 60% and secondary in 50% of patients, independent of the treatment target and associated threshold for GC discontinuation. Most baseline characteristics were not predictive of successful GC discontinuation, but ACPA negativity (only in BeSt), baseline DAS (only in IMPROVED) and in both studies DAS prior to GC discontinuation were predictive for successful discontinuation. Based on this data it seems that ‘standard’ baseline characteristics are insufficient to ‘personalize’ the duration of temporary GC bridging but the DAS at the moment of GC discontinuation might give guidance.

Table 1.

Results logistic regression analyses

UnivariableMultivariableaR2= 0.173BeStOR (95% CI)p-valueOR (95% CI)p-valueAge, year1.00 (0.98; 1.03)0.98Gender, female0.51 (0.24; 1.09)0.08Symptom duration BL, weeks1.00 (0.99; 1.01)0.61DAS at BL0.92 (0.61; 1.40)0.70DAS prior to discontinuation0.13 (0.05; 0.33)<0.010.11 (0.04; 0.30)<0.01RF, positive1.28 (0.62; 2.69)0.502.24 (0.81; 6,17)0.12ACPA, positive0.70 (0.34; 1.43)0.320.32 (0.12; 0.86)0.02Erosions, present at BL0.65 (0.28; 1.49)0.31UnivariableMultivariableaR2= 0.065IMPROVEDOR (95% CI)p-valueOR (95% CI)p-valueAge, year1.00 (0.99; 1.02)0.64Gender, female0.62 (0.43; 0.89)0.010.75 (0.51; 1.11)0.15Symptom duration BL, weeks1.00 (0.99; 1.00)0.430.99 (0.99; 1.00)0.08DAS at BL0.80 (0.65; 0.98)0.030.78 (0.62; 0.98)0.03DAS prior to discontinuation0.24 (0.15; 0.38)<0.010.24 (0.14; 0.40)<0.01RF, positive0.82 (0.57; 1.17)0.27ACPA, positive0.95 (0.66; 1.35)0.76Erosions, present at BL0.80 (0.49; 1.29)0.35

ACPA: anti-citrullinated protein antibodies; BL: baseline; DAS: disease activity score; RF: rheumatoid factor. α The final multivariable logistic regression model was based on stepwise forward and backward selection of predictors, both resulting in the same final model.

Acknowledgements:

We would like to thank all patients for their contribution as well as the rheumatologists who participated in the BeSt study group and in the IMPROVED-study group. We would also like to thank all other rheumatologists and trainee rheumatologists who enrolled patients in these studies, and all research nurses for their contributions.

Disclosure of Interests:

Johanna M. Maassen: None declared, Raquel Dos-Santos: None declared, Sytske Anne Bergstra: None declared, Robbert Goekoop: None declared, Thomas Huizinga: None declared, Cornelia Allaart Grant/research support from: The original BeSt study was realized with a government grant from the Dutch College of Health Insurance Companies, with additional funding from Schering-Plough and Janssen. the IMPROVED study was financially supported by AbbVie in the first year.

AB0667 A PROSPECTIVE STUDY INTO COVID-19 LIKE SYMPTOMS IN PATIENTS WITH AND WITHOUT IMMUNE MEDIATED INFLAMMATORY DISEASES OR IMMUNOMODULATING DRUGS

Background:

Patients with an immune mediated inflammatory disorder or post solid organ transplantation (IMIDT), are at risk for infectious complications especially if they are treated with immunosuppressive drugs (imeds). There is still great uncertainty whether these IMIDT patients are more susceptible to COVID-19 than controls, and/or should be advised to avoid taking their immunosuppressive treatment.

Objectives:

To evaluate whether patients with IMIDT are more at risk for CLS than controls.

Methods:

The IENIMINI study is a prospective cohort study in patients with IMIDT and controls (healthy or no IMIDT) who were identified based on the registration database of the Leiden University Medical Center. Over time, participants registered COVID-like symptoms (CLS) as they occurred, and filled in additional questionnaires. Univariate and multivariate regression analyses were done to identify variables associated with having CLS.

Results:

Of the 8670 individuals approached, 2110 with IMIDT and 1067 controls agreed to participate. In March and April, 454 (22%) of IMIDT patients and 242 (23%) of controls recorded to have CLS, mostly mild with a median (IQR) duration of seven (3-14) days in the IMIDT group and six days (4-11) in the control group. Eleven (5%) of the IMIDT patients with immunosuppressive medication (imed), 6 (3%) of IMIDTs without imed and 2 (1%) of controls were hospitalized with CLS (p=0.04). In May and June, fewer episodes overall were recorded. Being female (OR 1.45 95%CI 1.15;1.82), having a lung disease (OR 1.50 95%CI 1.20;1.88) and wearing a face mask (OR 1.42 95%CI 1.13-1.77) were independently associated with a higher risk, while higher age (OR 0.96 95%CI 0.96;0.97) and having an IMIDT with immunosuppressive medication use (OR 0.68 95%CI 0.51;0.91) were independently associated with a lower risk (see Table 1). Similar results were found after data imputation.

Table 1.

Univariate & multivariate analysis of variables associated with having CLS or not (OR with 95% CI)

n0UnivariateMultivariate*Sex, female25461.89 (1.58;2.25)1.45 (1.15;1.82)BMI23910.99 (0.97;1.01)1.00 (0.98;1.03)Age25460.97 (0.96;0.97)0.96 (0.96;0.97)IMIDT without imed†25461.00 (0.82;1.23)0.94 (0.72;1.24)IMIDT with imed †25460.79 (0.65;0.97)0.68 (0.51;0.91)Smoking (current)24631.35 (1.02;1.78)1.05 (0.74;1.50)Physical contact with family**22201.47 (1.22;1.78)1.22 (0.98;1.53)Visiting other people (not family)22051.26 (1.05;1.51)0.96 (0.77;1.20)Wearing a face mask21961.46 (1.20;1.76)1.42 (1.13;1.77)Close contact (at work)21801.65 (1.34;2.03)1.27 (0.97;1.66)Self-reported Diabetes Mellitus23810.69 (0.50;0.96)0.89 (0.58;1.36)Self-reported lung disease23961.30 (1.09;1.54)1.50 (1.20;1.88)Self-reported heart disease23990.85 (0.69;1.04)1.09 (0.83;1.43)Daily alcohol use24160.84 (0.71;1.00)1.20 (0.96;1.50)Influenza vaccination***24150.71 (0.60;0.84)0.96 (0.76;1.21)Solid organ transplantation25460.74 (0.54;1.03)0.79 (0.47;1.35)Good adherence to lockdown rules22451.17 (0.41;3.29)2.46 (0.65;9.38)Use of oral corticosteroids25460.84 (0.66;1.06)1.44 (0.95;2.20)Working outside the house24351.39 (1.16;1.68)0.92 (0.71;1.20)

Abbreviations: BMI=body mass index; CI= confidence intervals; CLS=Covid like symptoms; IMIDT= with immune mediated inflammatory disorders or transplant organ; n0=number of observations; OR=odds ratio.

* number of observations: 1835

** physical contact specified as ‘holding/shaking hands, hugging etcetera’

*** in autumn 2019

† control group = reference group

Conclusion:

Between March and July 2020, IMIDT patients, whether or not taking imeds, did not show an increased risk of reported COVID-like symptoms compared to controls. Continuing immunosuppressant drugs as long as not ill, while following the Dutch COVID rules, appears to be safe.

Disclosure of Interests:

Lotte van Ouwerkerk: None declared., Andrea van der Meulen Speakers bureau: Dr. van der Meulen reports personal fees from Janssen, grants and personal fees from Takeda, personal fees from Galapogos, grants from Nestle, grants from Norgine, outside the submitted work., Grant/research support from: Dr. van der Meulen reports personal fees from Janssen, grants and personal fees from Takeda, personal fees from Galapogos, grants from Nestle, grants from Norgine, outside the submitted work., Maarten Ninaber: None declared., Y.K. Onno Teng: None declared., Thomas Huizinga: None declared., Cornelia Allaart: None declared.

POS0395 ANTI-ACETYLATED PROTEIN ANTIBODIES IN RHEUMATOID ARTHRITIS (RA): CLUES FOR THE STARTING POINT OF AUTOANTIBODY RESPONSES IN RA

Background:

Rheumatoid arthritis (RA) is characterized by autoantibodies such as rheumatoid factor (RF) and anti-modified protein autoantibodies (AMPAs) like anti-citrullinated protein antibodies (ACPA) and anti-carbamylated protein antibodies (anti-CarP). Recently, another AMPA: anti-acetylated protein antibodies (AAPA) have been found in RA patients [1]. The prevalence of AAPA antibodies and their isotypes have yet to be determined. Since isotype profiles reflect the breadth of an immune response, the prevalence of AAPA isotypes in arthritis patients with and without RA can help to understand the relevance of this autoantibody response in RA.

Objectives:

To describe the prevalence of AAPA isotypes in arthritis patients with and without RA.

Methods:

In 650 RA patients fulfilling the 1987 RA criteria and 555 non-RA arthritis patients from the Leiden Early Arthritis Cohort, baseline serum samples were screened by ELISA for IgG, IgM and IgA to an acetylated- and control peptide that was based upon the CCP-2 backbone. The cutoff for positivity was based on 80 controls (mean + 2SD). A sample was considered positive if it was above the cutoff and was 0.1 optical density higher on the acetylated peptide than on the control peptide.

Results:

AAPA IgG was found in 36% of RA patients versus 6.7% of non-RA arthritis patients (figure 1a). Within RA patients, AAPA IgG antibodies were mostly present in the ACPA-(CCP-2) positive group (64% in ACPA-positive, compared to 5% in ACPA-negative). Levels of AAPA IgG and IgA were higher in RA patients than in healthy controls and non-RA arthritis patients (figure 1b), however, surprisingly, no difference in levels was found for IgM.

When isotype profiles in AAPA- positive arthritis patients were compared, patients with RA were more often positive for two or more isotypes then patients without RA, and thus displayed considerably more overlap in AAPA isotypes compared to non-RA patients (table 1). Intriguingly, IgM AAPA was the most prevalent isotype in non-RA patients, versus IgG in RA patients.

Table 1.

Anti-acetylated protein antibody (AAPA) isotype overlap in AAPA positive patients.

AAPA isotypeRA patients (=310) n (%)Non-RA arthritis patients (n=106) n (%)IgG+IgM-IgA-115 (37.1)28 (5.1)IgG-IgM+IgA-52 (16.8)48 (8.7)IgG-IgM-IgA+14 (4.5)13 (2.3)IgG+IgM+IgA-24 (7.7)3 (0.5)IgG+IgM-IgA+37 (11.9)4 (0.7)IgG-IgM+IgA+9 (2.9)8 (1.4)IgG+IgM+IgA+59 (19.0)2 (0.4)

AAPA: anti-acetylated protein antibodies, RA: rheumatoid arthritis

Conclusion:

AAPA are detected in one third of RA patients, and mainly in the ACPA-positive subgroup. The predominance of IgM AAPA in non-RA arthritis patients and healthy controls suggests that healthy persons can develop AAPA IgM without the development of RA. These results also suggest that in healthy individuals, AAPA responses can occur, but do not mature past the IgM-stage, while in RA patients, the AAPA-response does mature and might form a “starting point” for development of other AMPA leading to the concurrent present of several AMPA in disease.

References:

[1]Juarez, M., et al., Identification of novel antiacetylated vimentin antibodies in patients with early inflammatory arthritis. Ann Rheum Dis, 2016. 75(6): p. 1099-107.

Disclosure of Interests:

None declared

POS0356 THE RELATIONSHIP OF GENETICS AND CLINICALLY SUSPECT ARTHRALGIA IN RA DEVELOPMENT ASSESSED USING HC, CSA AND RA PATIENTS

Background:

The identification of a pre-RA stage of patients with clinically suspect arthralgia (CSA) has proven to be beneficial in the early detection of Rheumatoid disease. Similarly, genetic susceptibility studies have identified important genetic risk factors for the development of (CCP positive) RA.1 The question that arises is whether these findings represent independent etiological pathways and could therefore be complimentary in the early diagnosis of RA.

Objectives:

To corroborate the knowledge of genetic differences between HC and RA patients and extend it to include the CSA stage of disease.

Methods:

We used three datasets sampled from the same region in the Netherlands: 1,085 healthy controls (HC), 530 CSA and 1,277 RA patients. CSA patients were monitored for a median of 2 years for conversion into clinically apparent inflammatory arthritis (CSAc) or not (CSAnc).2 We assessed the association between HLA SE and disease stage using logistic regression. The analysis was repeated in the CCP positive and CCP negative strata of both the CSA and the RA populations.

Results:

Consistent with previous studies, HLA SE was significantly enriched in RA patients compared to HC (OR 2.28) (Figure 1). HLA SE also differentiated HC vs CSAc (OR 1.69), CSAnc vs CSAc (OR 1.74), and CSAnc vs RA (0R 2.35). No difference was found in HC vs CSAnc and CSAc vs RA.

Conclusion:

HLA SE is more prevalent in patients who developed (rheumatoid) arthritis than in both healthy controls and CSA patients who do not progress to arthritis. The results presented here seem to indicate a clear distinction between CSA patients who develop arthritis and those who do not. We therefore believe that known RA genetics play a role in the development of arthritis rather than the CSA symptoms. While this relationship varies by CCP status, an independent effect remains. Studies into the broader role of genetics beyond HLA SE are currently underway.

Figure 1.

Distinguishing ability of HLA SE across HC, CSAc, CSAnc and RA in the full populations as well as in the CCP positive and negative stratifications. The arrowhead indicates the “case” status in each logistic regression. OR’s (95% CI) derived from regression coefficients indicate the change in odds ratio attributable to HLA SE positivity.

References:

[1]van der Helm-van Mil, A. H., et al. Arthritis and rheumatism, 2006. 54(4): p. 1117–1121.

[2]van Steenbergen, H.W., et al. Ann Rheum Dis, 2017. 76(3): p. 491-496.

Disclosure of Interests:

None declared

POS0001 PHENOTYPE AND FUNCTIONAL CHARACTERISTICS OF ANTIGEN-SPECIFIC, AUTO-REACTIVE B CELL RESPONSES REVEAL DIFFERENTIAL IMMUNOLOGICAL ACTIVITY IN PATIENTS WITH SYSTEMIC SCLEROSIS

Background:

Systemic Sclerosis (SSc) is a systemic autoimmune disease that carries the highest mortality burden among the rheumatic diseases. Disease risk and course are difficult to predict in individual patients, and anti-inflammatory and B-cell depleting therapies show varying results. >95% of SSc patients harbor autoantibodies. Among those, anti-topoisomerase antibodies (ATA) and anti-centromere antibodies (ACA) are most prevalent, mutually exclusive in individual patients and associate with distinct disease phenotypes. Despite these associations, the clinical value of both ATA and ACA for patient stratification within these phenotypes is limited. Here, we hypothesized that phenotypic and functional characteristics of the underlying autoreactive B cell responses could allow insights in differential ‘immunological disease activity’ in individual patients, thereby providing indications as to potential drivers of these responses as well as granularity as to which patients may benefit from targeted interventions.

Objectives:

To assess phenotypic and functional characteristics of anti-topoisomerase and anticentromere specific B cell responses in individual patients with SSc.

Methods:

Peripheral blood mononuclear cells (PBMC) from ATA- and ACA-positive SSc patients were cultured without stimulation or in the presence of CD40L-expressing fibroblasts, IL-21 and BAFF. Following culture, ATA- and ACA-IgG and -IgA were measured in culture supernatants by ELISA. In addition, PBMC were depleted of circulating plasmablasts by fluorescence activated cell sorting (FACS), and isolated plasmablasts were cultured separately. Furthermore, the presence of antigen-specific plasmablasts was confirmed by ELISPOT. Finally, the degree of spontaneous ATA secretion was correlated to the presence or absence of interstitial lung disease (ILD; based on high-resolution computed tomography). Healthy donors and patients with rheumatoid arthritis served as controls.

Results:

We observed that individual ATA- and ACA-positive SSc patients harbored circulating B cells that secrete either ATA-IgG or ACA-IgG upon stimulation, depending on their serotype. In addition, we noted spontaneous secretion of ATA-IgG and, more remarkably, extensive secretion of ATA-IgA in ATA-positive patients. This degree of spontaneous, antigen-specific IgA secretion was specific for the ATA response, while spontaneous ACA-IgA secretion was undetectable in patients harboring ACA. FACS experiments and ELISPOT showed that the spontaneous ATA-IgA and -IgG secretion was attributable to circulating plasmablasts. Of note, the degree of spontaneous ATA-IgG secretion was remarkably higher in patients with ILD than in those without.

Conclusion:

Our findings demonstrate that individual ATA-positive SSc patients harbor activated ATA-IgG and ATA-IgA B cell responses, as indicated by the spontaneous secretion of both ATA isotypes by circulating plasmablasts. Importantly, by taking the presence of plasmablasts as a proxy for recent B cell activation, our data suggest a link between the activity of the antigen-specific B cell response and the presence of ILD. In contrast, the ACA B cell response was far less active and lacked the active IgA component, which suggests a difference in the triggers driving these autoreactive B cell responses in patients. In fact, the remarkable ATA-IgA secretion points towards a potential mucosal trigger of the ATA response, which may be continuously active in individual patients.

Disclosure of Interests:

None declared.

POS0097 JOINT INFLAMMATION TENDS TO RECUR IN THE SAME JOINTS DURING THE RHEUMATOID ARTHRITIS DISEASE COURSE

Background:

It is unknown whether in the disease course of rheumatoid arthritis (RA), inflammation recurs in the same joints over time or is more variable in joint locations. Joint involvement patterns over time might provide clues about the underlying mechanisms causing local joint inflammation.

Objectives:

The aim of this study is to assess if local joint inflammation at presentation of RA tends to recur or persist in the same joints.

Methods:

Data from the BeSt study were used, a treat-to-target (DAS≤2.4) trial in newly diagnosed RA (ACR 1987 criteria) patients. During 10 years, for each patient 68 joints were assessed three-monthly (41 visits) by trained nurses for swelling (yes/no) and tenderness.

We analyzed the association between local joint swelling at baseline and later swelling of the same joint using a multilevel mixed-effects logistic regression model. Models were adjusted for joint location and for timepoint, with joints clustered within patients. A sensitivity analysis was done for the 25% most affected joints (MCP 1-3, PIP 2-3, wrists and MTP 2-4).

To investigate whether later swelling of a joint is predicted by baseline swelling of that same joint specifically, rather than by baseline swelling in general, a permutation test with 1000 permutations was performed. A p-value <0.05 indicates that joint swelling is better predicted by its baseline swelling than by baseline swelling of randomly selected other joints.

In a separate model, with an interaction term between baseline swelling and previous visit swelling (yes/no), we evaluated if the association between baseline swelling and later local swelling was influenced by whether later swelling was persistent (swelling at both the current and previous visit) or recurrent (swelling at current visit but not at the previous visit).

Results:

The 508 patients had a median (IQR) follow-up duration of 10 (6-10) years. At baseline, 8,137/34,423 (24%) assessed joints were scored as swollen. Baseline swelling was subsequently persistent in 21% of the joints with a median (IQR) duration of 1 (1-2) visit (± 3 months after baseline). In addition, after resolution of initial swelling, swelling recurred at least once in 46% of the joints with baseline swelling.

Baseline swelling was significantly associated with swelling in the same joint during follow-up (OR 2.37, 95% CI 2.30-2.43). A sensitivity analysis of the most affected joints showed similar results (OR 2.10 [95% CI 2.03-2.19]).

The permutation test showed a significant result with p<0.001, indicating that joint swelling is better predicted by baseline swelling of that same joint than by baseline swelling of other joints.

The association between baseline swelling and later local swelling was weaker in case of persistent swelling than in case of recurrent swelling (interaction term baseline swelling * swelling at previous timepoint ‘yes’: OR 0.80 [95% CI 0.75-0.85]).

Conclusion:

In newly diagnosed RA, over median 10 years of treatment to target DAS≤2.4, baseline swelling persisted in 21% of the joints, for median 3 months after baseline. Local recurrence after initial resolution occurred in 46% of the joints. Baseline joint swelling was significantly associated with local joint swelling during follow-up, even when taking into account the higher a priori chance of swelling in the joints that are most often affected, and joint swelling during follow-up was better predicted by baseline swelling of that particular joint than by baseline swelling of other joints. Local persistence and recurrence of joint swelling despite DAS≤2.4 steered treatment adjustments suggest that local joint conditions or even joint memory play a role in mechanisms of joint inflammation.

Acknowledgements:

We would like to thank all patients for their contribution as well as the rheumatologists who participated in the BeSt study group. We would also like to thank all other rheumatologists and trainee rheumatologists who enrolled patients in these studies, and all research nurses for their contributions.

Disclosure of Interests:

Sascha Heckert: None declared, Sytske Anne Bergstra: None declared, Xanthe Matthijssen: None declared, Yvonne Goekoop-Ruiterman: None declared, F. Fodili: None declared, Cornelia Allaart Grant/research support from: The original BeSt study was supported by a government grant from the Dutch insurance companies, with additional funding from Schering-Plough B.V. and Janssen B.V., Thomas Huizinga: None declared

POS0384 A NOVEL MECHANISM LINKING MUCOSAL BACTERIA WITH AUTOANTIBODY RESPONSES IN RA: ACETYLATED BACTERIAL LYSATE AS A MODEL ANTIGEN

Background:

Rheumatoid arthritis (RA) is characterized by autoantibodies against post-translationally modified proteins (AMPA) such as citrullinated, carbamylated and acetylated proteins. Importantly, these antibodies are highly multireactive, as they often recognize more than one of these post-translational modifications. Despite extensive research, the antigens inducing the breach of tolerance remain unknown, although microbial antigens are often suspected. Various bacteria are known to be capable of acetylation, therefore, it is intriguing to know what mechanisms can underlie the breach of tolerance towards acetylated proteins and development of anti-acetylated protein antibodies (AAPA).

Objectives:

To investigate whether acetylated proteins of bacterial origin (1) are recognized by human derived AMPA and AMPA expressing B cells; and (2) can induce AMPA development when used to immunize mice.

Methods:

Acetylated E. coli proteins were acquired with two separate methods (Figure 1A): by culturing E. coli in a condition promoting auto-acetylation (intrinsically acetylated bacterial proteins, IABP), or by directly acetylating lysate-derived proteins via a chemical reaction (extrinsically acetylated BP, EABP). Acetylated ovalbumin (AcOVA) served as positive control for AAPA induction in mice, non-acetylated BP (NABP) and phosphate buffer saline (PBS) served as negative control. Mice were immunized with these proteins and the resulting antibody response was studied by ELISA. Furthermore, EABP/IABP/NABP were investigated for recognition by human-derived AAPA with ELISA and AAPA-expressing B cells with spleen tyrosine kinase (Syk) phosphorylation assay; acetylated human fibrinogen and native fibrinogen served as positive and negative control.

Results:

Repetitive immunization of mice with EABP resulted in an AMPA response recognizing acetylated, carbamylated and citrullinated proteins. AMPA titers in these mice exceeded the titers in the positive control mice immunized with AcOVA and were substantially higher than in the NABP-immunized mice (Figure 1B). Human-derived monoclonal AAPA recognized EABP and IABP (not shown). B cell activation (measured by Syk phosphorylation) assay indicated that AAPA expressing B cells recognized EABP and (to a lesser extent) IABP, but not NABP (Figure 1C).

Conclusion:

Acetylated bacterial proteins are potent antigens that can induce cross-reactive AMPA responses in mice and they are recognized by human AAPA. This suggests that acetylated bacterial proteins could possibly be involved in the breach of tolerance in RA.

Acknowledgements:

We thank Dr. Can Araman and Prof. Chunaram Choudhary for their advice regarding optimization of bacterial auto-acetylation.

Disclosure of Interests:

None declared

POS0714 WHITE MATTER HYPERINTENSITIES LEAD TO REDUCED PSYCHOMOTOR SPEED IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS AND NEUROPSYCHIATRIC SYMPTOMS

Background:

Cognitive impairment is common in patients with systemic lupus erythematosus (SLE) and neuropsychiatric (NP) symptoms, but the exact underlying structural brain correlates are unknown.

Objectives:

We aimed to compare cognitive function between groups of patients with different phenotypes of (NP)SLE and assessed the association between brain volumes, white matter hyperintensity (WMH) volume and cognitive function.

Methods:

Patients who visited the NPSLE clinic of the Leiden University Medical Center between 2007-2015 were included in this study (n=151; 42 ± 13 years, 91% female). In a multidisciplinary consensus meeting, phenotypes were established and neuropsychiatric symptoms were attributed to SLE (NPSLE, inflammatory (n=24) or ischemic (n=12)) or to minor involvement of SLE or other causes (minor/non-NPSLE (n=115)). All patients underwent standardized cognitive assessment of the four cognitive domains: global cognitive functioning (GCF), learning and memory (LM), executive functioning and complex attention (EFCA) and psychomotor speed (PS)). Cognitive dysfunction was defined as a T-score <40, with age, sex, gender and education matched individuals of the Dutch population as reference. In addition, automated volume measurements on brain MRI (white matter, grey matter, white matter hyperintensities (WMH) and total brain volume (TBV)) were performed. Patients with brain infarcts >1.5 cm were excluded. Cognitive function (Z-score) was compared between different NPSLE phenotypes using multiple regression analyses corrected for age, sex and education. Associations between brain volumes, WMH and cognitive function were assessed per phenotype using multiple regression analyses corrected for age, sex and intracranial volume.

Results:

Global cognitive functioning was impaired in 5%, learning & memory in 46%, and executive functioning & complex attention in 39% and psychomotor speed in 46% of all patients. Patients with inflammatory NPSLE showed the most cognitive impairment and reduced cognitive function compared to ischemic NPSLE (all domains) and minor/non-NPSLE (EFCA) (p <0.05).

Lower total brain volume and grey matter volume were associated with lower cognitive functioning in all domains (β: 0.00/0.01 (0.00; 0.01)) and lower white matter volume associated with lower LM, EFCA and PS (β: 0.00/0.01 (0.00; 0.01)) in all patients. Higher WMH volume associated with lower psychomotor speed (β: -0.14 (-0.32; -0.02)), especially in patients with inflammatory NPSLE (β: -0.36 (-0.60; -0.12).

Conclusion:

Reduced brain volume leads to reduced cognitive function in multiple cognitive domains in all patients with SLE and neuropsychiatric symptoms. Increased WMH volume leads to reduced psychomotor speed, especially in patients with inflammatory NPSLE.

Table 1.

Prevalence of cognitive impairment in patients with minor/non-NPSLE, inflammatory NPSLE and ischemic NPSLE

Global cognitive functioningLearning &memoryExecutive functioning & complex attentionPsychomotor speedAll patients(n = 151)8 (5)70 (46)57 (39)69 (46)Inflammatory NPSLE(n = 24) 3 (13) 14 (58) 12 (50) 12 (50)Ischemic NPSLE(n = 12) 0 (0) 6 (50) 2 (17) 2 (17)Minor/non-NPSLE(n = 115) 5 (4) 50 (44) 43 (38) 55 (49)

NPSLE = neuropsychiatric systemic lupus erythematosus.

Data represent n (%) of patients with cognitive impairment in the mentioned cognitive domain. Cognitive impairment was defined as cognitive function at least 1SD lower than the mean of an age, sex and education matched general Dutch population. The percentages were calculated from total number of patients with available scores: Global functioning: 23/24 inflammatory NPSLE and 113/115 minor/non-NPSLE; psychomotor speed 113/115 minor/non-NPSLE, executive function & complex attention: also 113/115. All tests were available for ischemic NPSLE.

Disclosure of Interests:

None declared

POS0843 A NEW RISK MODEL IS ABLE TO IDENTIFY SYSTEMIC SCLEROSIS PATIENTS WITH A LOW RISK OF DISEASE PROGRESSION

Background:

Disease course in Systemic Sclerosis (SSc) ranges from mild, to severe with progressive organ involvement within months. Guidelines for follow-up are mainly based on expert consensus, and advocate annual assessment. So far, no data driven guidelines exist that describe tailormade systematic assessments for individual patients in line with individual disease course.

Objectives:

To develop a prediction model to guide annual assessment of SSc patients tailored in accordance to disease activity.

Methods:

A machine learning approach was used to develop a model that can identify patients without disease progression. SSc patients included in the prospective Leiden SSc cohort and fulfilling the ACR/EULAR 2013 criteria were included. The primary endpoint in the prediction model was disease progression which was defined as progression in ≥1 organ system, and/or start of immunosuppression or death between the two most recent visits. Using elastic-net-regularization, and including 90 independent clinical variables (100% complete), we trained the model on 75% and validated it on 25% of the patients in order to perform internal validation of the final model. We optimized the model on negative predictive value (NPV) to minimize the likelihood of missing progression. By expert assessment of the test characteristics, including swarm plots of the probability scores, cut-offs were identified for low, intermediate and high risk for disease progression.

Results:

Of the 492 SSc patients (range of follow-up: 2-10yrs), disease progression during follow-up was observed in 52% (median time 4.9yrs), including myocardial progression in 29%, lung progression in 23%, skin progression in 16%, and death in 12%. Performance of the model in the test set showed an AUC-ROC of 0.66. Probability score cutoffs were defined: low risk for disease progression (<0.197, NPV:1.0; 29% of patients), intermediate risk (0.197-0.223, NPV:0.82; 27%) and high risk (>0.223, NPV:0.78; 44%). The predictive variables included in the model were: previous use of cyclophosphamide or corticosteroids, start with immunosuppressive drugs, previous gastrointestinal progression, previous cardiovascular event, pulmonary arterial hypertension, modified Rodnan Skin Score, creatinine kinase, and diffusing capacity for carbon monoxide.

Conclusion:

Our machine-learning-assisted model for disease progression enabled us to classify 29% of SSc patients as ‘low risk’. In this group annual assessment programs could be less extensive than indicated by international guidelines.

Baseline characteristicsTotaln=492Non-ProgressorsN=235ProgressorsN=257DemographicsFemale, n (%)389 (79)193 (82)196 (76)Age, mean (SD)55 (14)55 (15)55 (13)Disease duration nonRP, median (IQR)3.2 (0.9-10.3)3.5 (0.8-10.5)3.6 (1.1-9.3)Organ involvementDcSSc, n (%)118 (24)34 (15)84 (33)DLCO% of pred, mean (SD)66 (18)69 (18)64 (17)FVC% of pred, mean (SD)98 (23)96 (24)97 (21)ILD on HRCT, n (%)183 (37)66 (28)117 (46)PAH, n (%)26 (5)10 (4)16 (6)GAVE, n (%)9 (2)4 (2)5 (2)Cardiac involvement, n (%)28 (6)14 (6)14 (5)Myositis, n (%)8 (2)6 (3)2 (1)Renal crisis, n (%)14 (3)6 (3)8 (3)AutoantibodiesAnti-centromere, n (%)194 (39)118 (50)76 (30)Anti-topoisomerase, n (%)116 (24)42 (18)74 (29)

RP=raynaud phenomenon, dcSSc= diffuse cutaneous systemic sclerosis, mRSS=modified rodnan skin score, DU=digital ulcera, DLCO= single-breath diffusing capacity for carbon monoxide, FVC= forced vital capacity, ILD=interstitial lung disease, HRCT= high resolution computed tomography, PAH= pulmonary arterial hypertension, GAVE= gastric antral vascular extasia.

Disclosure of Interests:

None declared

AB0668 THE ONSET OF RHEUMATOID ARTHRITIS AFTER COVID-19 – COINCIDENCE OR CONNECTED?

Background:

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been suggested to induce autoimmune phenomena. Multiple studies have reported the presence of autoantibodies in patients with COVID-19. Also the presence of anti-citrullinated protein antibodies (ACPA) and flaring of rheumatoid arthritis (RA) after COVID-19 has been described.[1, 2] Furthermore, in rheumatology clinics patients may present with polyarthritis compatible with RA shortly after SARS-CoV-2 infection. However, it is unclear how often ACPA occur after COVID-19 and whether preceding COVID-19 impacts on disease presentation of RA and phenotype of the ACPA response.

Objectives:

This study aims to determine the seroprevalence of ACPA after COVID-19 and to investigate the association between preceding COVID-19 infection and disease presentation of new-onset RA, including clinical phenotype and autoantibody response.

Methods:

To estimate the prevalence of ACPA after COVID-19 we measured ACPA IgG in samples from 61 patients visiting the specialized post-COVID outpatient clinic of the LUMC 5 weeks after hospitalization, using routine tests or in-house ELISA. Furthermore, we identified 5 patients presenting with polyarthritis compatible with RA after SARS-CoV-2 infection. To study the impact of COVID-19 on disease presentation, we examined clinical phenotype, autoantibody isotype positivity and ACPA IgG variable domain (V-domain) glycosylation of these patients and compared these features to regular RA patients. Autoantibody isotypes, including rheumatoid factor (RF) IgM/IgA, anti-CCP2 IgG/ IgM/IgA and anti-carbamylated protein antibodies (anti-CarP) IgG were measured using in-house ELISA’s. The percentage of V-domain glycosylation of purified ACPA IgG was measured with UHPLC.

Results:

None of the 61 post-COVID patients tested positive for ACPA 5 weeks after hospitalization, except two patients previously diagnosed with ACPA-positive RA. Thus, we could not observe an increase in ACPA-positivity shortly after COVID-19. Of the 5 patients who developed polyarthritis compatible with RA after SARS-CoV-2 infection, the average age was 63.6 years and 2/5 were female. 4/5 patients had been hospitalized due to severe COVID-19. On average, joint complaints started 6.6 weeks after infection, although two patients reported symptoms before infection. 4/5 patients fulfilled the ACR 2010 criteria for RA. Three patients (patient 1, 4, 5) were phenotypically very similar to regular new-onset RA patients. Patient 3 had a history of seronegative RA and had been in DMARD-free remission for 5 years. She flared 6 weeks after SARS-CoV-2 infection. Patient 2 had a remarkably different presentation. He was admitted with a suspected septic polyarthritis or pneumonia with reactive polyarthritis 6 weeks after COVID-19. ACPA level was low positive. The patient died unexpectedly after two days and autopsy revealed dilating myocarditis of unclear underlying cause. No causative pathogen could be identified.

Previous studies have shown that RA-patients are most often either seronegative or triple-positive for RF, ACPA and anti-CarP antibodies. Autoantibody measurements on sera of the post-COVID polyarthritis patients revealed a similar pattern (Figure 1A) with two patients being completely seronegative, and three patients positive for a range of autoantibodies. In all post-COVID samples, the percentage of ACPA IgG V-domain glycosylation was significantly increased compared to total IgG (Figure 1B), similar as in regular RA.

Conclusion:

In conclusion, we found that the seroprevalence of ACPA is not increased post-COVID and that most patients presenting with polyarthritis after COVID-19 resemble regular RA patients, both regarding clinical phenotype and autoantibody characteristics. Although sample size and follow-up was limited, it appears that RA post-COVID may be coincidence rather than connected.

References:

[1]Vlachoyiannopoulos et al. Ann Rheum Dis, 2020.

[2]Perrot et al. The Lancet Rheumatology, 2020.

Disclosure of Interests:

None declared.

SAT0585 GEO-EPIDEMIOLOGY OF AUTOANTIBODIES IN RA: DIFFERENT PREVALENCES IN FOUR ETHNICALLY DIVERSE RA POPULATIONS

Background:

Rheumatoid arthritis (RA) has been described in virtually every ethnic population. Most RA patients harbor anti-modified protein antibodies (AMPAs), including anti-citrullinated protein (ACPA), anti-carbamylated protein (anti-CarP), anti-malondialdehyde acetaldehyde (anti-MAA), and anti-acetylated protein antibodies (AAPA). However, it is unclear whether differences exist in the AMPA response between different ethnic groups. Such differences could provide new clues to genetic and environmental factors contributing to autoantibody development.

Objectives:

To investigate the prevalence of different AMPA in four ethnically diverse RA populations, and their association with smoking.

Methods:

Enzyme-linked immunosorbent assays were used to measure anti-CarP IgG, anti-MAA IgG (both in-house), and anti-acetylated vimentin IgG (Orgentec) in ACPA-positive sera of Dutch (NL, n=103), Japanese (JP, n=174), Canadian First Nations People (FN, n=100), and black South Africans (SA, n=67) fulfilling the 1987 ACR classification criteria for RA. Ethnicity-matched local healthy controls were used to calculate cohort-specific cut-offs. Logistic regression was used to identify whether ever-smoking was associated with AMPA seropositivity in each cohort, corrected for age, gender, and disease duration. Random-effects meta-analysis was used to pool the resulting odds ratios (OR).

Results:

For all three AMPAs, median levels were higher in FN and especially SA than NL and JP patients (Figure 1). The median autoantibody levels in arbitrary units (in % of patients positive) for NL, JP, FN and SA RA patients were: anti-CarP IgG: 1157 (47%), 994 (43%), 1642 (58%) and 2336 (76%) (p<0.001); anti-MAA IgG: 131 (29%), 179 (22%), 251 (29%) and 257 (53%) (p<0.001); AAPA: 133 (20%), 136 (17%), 153 (38%) and 316 (28%) (p<0.001). Prevalence, meaning positivity, also differed significantly between cohorts for all AMPAs (p<0.001).There were also marked differences in total IgG levels in mean (SD) g/L: 13 (4) for NL, 17 (6) for JP, 18 (6) for FN, and 25 (8) for SA (p<0.001). When the autoantibody levels were normalized to total IgG, the differences in became less pronounced between cohorts (Figure 2). The median arbitrary units per g/L Total IgG for NL, JP, FN and SA RA patients were: anti-CarP IgG: 54, 25, 53, and 79; anti-MAA IgG: 6, 5, 8, and 9; and AAPA: 2, 2, 2, and 3, suggesting that autoantibody level differences may partly correspond to cohort-specific differences in total IgG, although the overall trend of higher levels in SA persisted. There was no association between smoking and anti-CarP or anti-MAA positivity, with pooled OR (95% CI) of 1.31 (0.79-2.18) and 0.85 (0.46-1.56), respectively. However, smoking was positively and consistently associated with AAPA positivity in each cohort: pooled OR (95% CI) of 2.01 (1.06-3.81).

Conclusion:

In these ACPA-positive ethnically diverse RA populations, levels and prevalence of various AMPAs differ, suggesting that ethnic background and environment may influence the development of the autoantibody response in RA. Despite these differences, our results imply smoking as a consistent risk factor for AAPA across different ethnic backgrounds.

Disclosure of Interests:

Emma C. de Moel: None declared, Veerle Derksen: None declared, Leendert A Trouw: None declared, Chikashi Terao: None declared, Mohammed Tikly: None declared, Hani El-Gabalawy: None declared, Holger Bang Grant/research support from: Employee of Orgentec Diagnostika, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Rene Toes: None declared, Diane van der Woude: None declared

SAT0104 MAINTENANCE OF SDAI REMISSION AND PATIENT-REPORTED OUTCOMES (PROS) FOLLOWING DOSE DE-ESCALATION OF ABATACEPT IN MTX-NAÏVE, ANTI-CITRULLINATED PROTEIN ANTIBODY (ACPA)+ PATIENTS WITH EARLY RA: RESULTS FROM AVERT-2, A RANDOMISED PHASE IIIB STUDY

Background:

The Phase IIIbAssessingVeryEarlyRATreatment (AVERT)-2 trial (NCT02504268) evaluated SC abatacept (ABA) + MTX vs ABA placebo (PBO) + MTX in ACPA+ patients (pts) with early, active RA.1Results from the 56-wk induction period (IP) showed a significantly greater proportion of pts treated with ABA + MTX (vs MTX alone) reported clinically meaningful improvements in HAQ-DI, global disease activity and pain, which were sustained at 52 wks.2

Objectives:

To report maintenance of SDAI remission and PROs from the AVERT-2 de-escalation (D-E) period.

Methods:

Pts received blinded SC ABA (125 mg once wkly [QW]) + MTX or ABA PBO + MTX induction treatment for 56 wks. In this analysis, pts who completed induction with ABA + MTX and had sustained SDAI remission (≤3.3 at Wks 40 and 52) were re-randomised 1:1:1 to ABA QW + MTX, stepwise D-E (ABA every other wk + MTX for 24 wks then ABA PBO + MTX for 24 wks), or ABA QW + MTX PBO for 48 wks in the D-E period. PROs included physical function (HAQ-DI [0–3; decrease=improvement] and Short-Form 36 [SF-36] v2.0 Physical Functioning Scale [PFS]; 0–100; increase=improvement), and fatigue (Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-F] score; 0–52; decrease=improvement). Endpoints included: proportion of pts in SDAI remission and pts with HAQ-DI response (decrease from IP Day [D]1 in HAQ-DI ≥0.30); adjusted mean change (adMC) from D-E D1 in HAQ-DI, SF-36 PFS or FACIT-F to D-E Wk 48. adMCs were estimated using a mixed effect model with repeated measures.

Results:

147 ABA + MTX-treated pts were re-randomised in the D-E period. Across re-randomised arms, the range of mean scores was 1.87–2.52 for SDAI and 0.18–0.30 for HAQ-DI at entry into D-E period (D-E D1). 74% of pts receiving ABA QW + MTX maintained SDAI remission at D-E Wk 48 (Fig 1); this proportion was higher than in the ABA withdrawal and ABA QW + MTX PBO arms. Pts continuing ABA QW + MTX maintained HAQ-DI response during D-E (Fig 1), but by D-E Wk 48 the proportion of pts with HAQ-DI response in the ABA withdrawal arm declined by 30%. At D-E Wk 48, a small numerical decrease (adMC –0.04) in HAQ-DI was observed in the ABA QW + MTX arm; increases were seen in the withdrawal (adMC 0.26) and ABA QW + MTX PBO arms (adMC 0.16). By D-E Wk 48, SF-36 PFS increased (adMC 1.68) in the ABA QW + MTX arm but decreased in the withdrawal (adMC –3.34) and ABA QW + MTX PBO (adMC –1.45) arms. FACIT-F score increased during D-E in all arms, but the increase at D-E Wk 48 was lower in the ABA QW + MTX arm (adMC 0.79) vs the withdrawal (adMC 4.12) and ABA QW + MTX PBO (adMC 2.41) arms. Similar trends were seen for other PROs including Work Productivity and Activity Impairment-RA; while activity impairment remained stable in the ABA QW + MTX arm, there was a trend for worsening in the withdrawal arm.

Conclusion:

In the AVERT-2 D-E period, continued combination therapy (abatacept + MTX) resulted in maintenance of benefits on PROs, particularly physical functioning, in seropositive pts with early RA. D-E of abatacept followed by complete withdrawal was associated with the greatest loss of remission as well as worsening of PROs. The PRO results corresponded well to the maintenance of clinical (SDAI) remission.

References:

[1]Emery P, et al. ACR 2018; San Diego, USA: Poster 563.

[2]Emery P, et al. ACR 2019; Atlanta, USA: Poster 1423.

Acknowledgments:

Joanna Wright (medical writing, Caudex; funding: Bristol-Myers Squibb)

Disclosure of Interests:

Paul Emery Grant/research support from: AbbVie, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer, Roche (all paid to employer), Consultant of: AbbVie (consultant, clinical trials, advisor), Bristol-Myers Squibb (consultant, clinical trials, advisor), Lilly (clinical trials, advisor), Merck Sharp & Dohme (consultant, clinical trials, advisor), Novartis (consultant, clinical trials, advisor), Pfizer (consultant, clinical trials, advisor), Roche (consultant, clinical trials, advisor), Samsung (clinical trials, advisor), Sandoz (clinical trials, advisor), UCB (consultant, clinical trials, advisor), Yoshiya Tanaka Grant/research support from: Asahi-kasei, Astellas, Mitsubishi-Tanabe, Chugai, Takeda, Sanofi, Bristol-Myers, UCB, Daiichi-Sankyo, Eisai, Pfizer, and Ono, Consultant of: Abbvie, Astellas, Bristol-Myers Squibb, Eli Lilly, Pfizer, Speakers bureau: Daiichi-Sankyo, Astellas, Chugai, Eli Lilly, Pfizer, AbbVie, YL Biologics, Bristol-Myers, Takeda, Mitsubishi-Tanabe, Novartis, Eisai, Janssen, Sanofi, UCB, and Teijin, Vivian Bykerk: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Gustavo Citera Grant/research support from: AbbVie, Amgen, Eli Lilly, Gema, Genzyme, Novartis and Pfizer Inc, Consultant of: AbbVie, Amgen, Eli Lilly, Gema, Genzyme, Novartis and Pfizer Inc, Clifton Bingham Grant/research support from: Bristol-Myers Squibb, Consultant of: Bristol-Myers Squibb, Subhashis Banerjee Shareholder of: AbbVie, Bristol-Myers Squibb, Lily, Pfizer, Employee of: Bristol-Myers Squibb (current); AbbVie, Lily, Pfizer (past), Sean Connolly Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Joe Zhuo Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Robert Wong Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Kuan-Hsiang Gary Huang Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Karissa Lozenski Employee of: Bristol-Myers Squibb, Yedid Elbez Consultant of: Bristol-Myers Squibb, Roy Fleischmann Grant/research support from: AbbVie, Akros, Amgen, AstraZeneca, Bristol-Myers Squibb, Boehringer, IngelhCentrexion, Eli Lilly, EMD Serono, Genentech, Gilead, Janssen, Merck, Nektar, Novartis, Pfizer, Regeneron Pharmaceuticals, Inc., Roche, Samsung, Sandoz, Sanofi Genzyme, Selecta, Taiho, UCB, Consultant of: AbbVie, ACEA, Amgen, Bristol-Myers Squibb, Eli Lilly, Gilead, GlaxoSmithKline, Novartis, Pfizer, Sanofi Genzyme, UCB

SAT0099 BMI AND TREATMENT SURVIVAL IN RA PATIENTS STARTING TREATMENT WITH TNFΑ-INHIBITORS: LONG TERM FOLLOW-UP IN THE REAL LIFE METEOR REGISTRY

Background:

BMI appears to be associated with treatment response on TNFi(nhibitors) in rheumatoid arthritis (RA), but large heterogeneity between studies exists. More extreme BMI categories are rarely studied and it is unclear if differences exist between various TNFi.1

Table 1

Characteristics of RA patients

Female, n (%)935 (79.8)Age, years*51.0 ±13.7Current smokers, n (%)256 (23.2)RF Positivity, n (%)404 (55.6)Anti-CCP Positivity, n (%)430 (58.2)X-ray Erosion, n (%)317 (61.9)ESR, mm/h*31.2±21.9CRP, mg/L*17.2±3.9DAS 28-CRP*3.8±1.6VAS global*46.6±28.6HAQ*0.9±0.7First TNFi Etanercept, n (%)525 (38.7) Adalimumab, n (%)379 (27.9) Infliximab, n (%)118 (8.7) Certolizumab, n (%)188 (13.8) Golimumab, n (%)147 (10.9)

* mean ±S.D

RF, Rheumatoid factor; Anti-CCP, Anti- cyclic citrullinated peptid; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; DAS28–CRP, Disease Activity Score using 28 joints–CRP; VAS, Visual analog scale; HAQ, Health Assessment Questionnaire

Objectives:

To study whether there is an association between BMI category and drug survival in RA patients starting treatment with various TNFi in a real life longitudinal international registry.

Methods:

Data from 5230 RA patients starting a TNFi were included from the METEOR registry. Timing of follow-up visits was daily practice based. Follow-up was censored at 5000 days (±13.5 years). Patients were divided into 6 BMI categories (WHO definition): underweight BMI <18.5, normal weight BMI 18.5-25, pre-obesity BMI 25-30, obesity class I BMI 30-35, class II BMI 35-40, and class III BMI >40. Missing data were imputed using chained equations. The association between BMI category and time on treatment was investigated using Kaplan-Meier (KM) curves and Cox regression analyses, for time on first TNFi and for the first prescribed course of adalimumab (ADA), etanercept (ETA) and infliximab (IFX) separately. All analyses were adjusted for the potential confounders age, gender, smoking, baseline DAS28, concomitant glucocorticoid use and country. Potential effect modification by reported pain was tested by adding an interaction term between BMI category and baseline pain category (VAS pain 0-25, 25-50, 50-75 and 75-100).

Results:

Most patients had a normal weight (46%) or pre-obesity (32%). 4% of patients were underweight, 10% had obesity class I, 3% obesity class II and 1% obesity class III. N=2936 patients ever started ETA, n=2069 ADA, n=1390 IFX, n=263 certolizumab and n=84 golimumab. The KM curve in fig 1A shows TNFi survival in patient starting their first TNFi per BMI category. Patients with normal weight and pre-obesity had longest drug survival and patients with obesity class II and especially patients with obesity class III had shortest drug survival. The adjusted Cox regression support these findings, with statistically significantly shorter drug survival for patients with obesity class III [HR (95% CI) 1.67 (1.29; 2.18)] and class II [1.28 (1.06; 1.54)], but also for underweight patients [1.3 (1.07; 1.58)], compared to normal weight patients. KM curves for individual TNFi showed shorter drug survival on ADA for patients with obesity class II and III (fig 1B), on ETA for patients with obesity, especially in class III (fig 1C) and on IFX, for patients with obesity class II and III and underweight patients (fig 1D). After adjustment in Cox regression, statistical significant BMI-drug survival associations remained for patients with pre-obesity starting ADA [HR (95% CI) 0.86 (0.75; 0.99)], for patients starting ETA with obesity class II [HR (95% CI) 1.27 (0.98; 1.65) or class III [1.79 (1.25; 2.55)] and for patients on IFX who were underweight [HR (95% CI) 1.82 (1.20; 2.76)] or in obesity class II [1.49 (0.98; 2.26)]. No effect modification was found for reported pain.

Conclusion:

Both underweight (as identified in IFX treated patients) and overweight patients (in ADA, ETA and IFX treated patients) discontinued a first TNFi treatment earlier than normal weight patients. Reported pain was not the main determinant. It remains uncertain what determines TNFi survival in individual patients.

References:

[1] Singh, et al.PloS One2018; 13:e0195123

Disclosure of Interests:

Sytske Anne Bergstra: None declared, David Vega-Morales: None declared, Elizabeth Murphy: None declared, Marieke de Buck: None declared, Karen Solomon-Escoto: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Cornelia Allaart: None declared

THU0327 EFFECT OF IMMUNOSUPPRESSIVE MEDICATION ON GASTRO-INTESTINAL INVOLVEMENT IN SYSTEMIC SCLEROSIS PATIENTS STRATIFIED FOR DISEASE DURATION

Background:

Gastrointestinal tract (GIT) involvement is associated with high morbidity in systemic sclerosis (SSc) but the data on its impact from unselected and well characterized SSc cohorts are scarce. Currently, the effect of immunosuppressive (IS) treatment on GIT involvement is largely unknown.

Objectives:

To evaluate the severity and worsening of GIT involvement in two prospective SSc cohorts. To assess factors associated with severity of GIT involvement, stratified for disease duration. To evaluate effect of IS treatment on worsening of GIT involvement.

Methods:

All SSc patients fulfilling the 2013 SSc classification criteria from two SSc cohorts were evaluated. Incident SSc was defined as disease duration since first symptom non-Raynaud < 24 months at first presentation. GIT involvement was assessed by the UCLA GIT 2.0 score at baseline and after one year to assess worsening of GIT involvement. Worsening was defined as change > minimal clinical important difference for total score and for each of the seven subdomains. GIT involvement was defined as present if the patients reported symptoms resulting in a score of ≥0.01 and was segregated into mild ≥0.01 (<0.5 or for fecal incontinence and distention/bloating <1.01), moderate (≥0.5 or for fecal incontinence and distention/bloating ≥1.01) or severe GI symptoms (> 1.01 or for distension/bloating > 1.61 or for fecal soiling > 2.01). Logistic regression was applied to identify risk factors associated with GIT involvement at baseline. The effect of IS treatment on worsening on each of the subdomains after one year was evaluated with logistic regression, with adjustment for baseline disease duration and severity.

Results:

In total, 834 SSc patients were included; 236 (28%) had incident disease (table 1). Incident cases (IC) showed comparable severity of GIT involvement compared to non-incident cases (NIC) except for significantly less severe reflux and distension/bloating (figure 1). Logistic regression showed female sex (OR 8.5(1.1-36.01)) and smoking (OR 2.9(1.2-7.3)) to be associated with GIT severity at baseline in IC; in NIC anti-centromere antibody (OR 1.7(1.3-2.2)) was additionally associated with GIT severity. The use of IS at baseline did not associate with GI severity at baseline. In total n = 685 (82% never had IS treatment (83% NIC, 81% IC); of these 258 (38%) started with IS after baseline assessment (52% IC, 32% NIC, p =0.02). When comparing change of GIT involvement after one year between those who started IS and those who did not, worsening of GI symptoms occurred more frequently in patients who started IS treatment (figure 2), but notably, patients in this group were also more frequently anti-topoisomerase positive, had ILD, and diffuse disease subset compared to the patients without IS treatment; age and sex were comparable. In the logistic regression with adjustment for disease duration and severity, there were no significant associations between IS treatment and worsening on GIT involvement.

Conclusion:

Regardless disease duration, about 1/3 of all SSc patients had moderate-severe GIT involvement. Disease duration and treatment initiation with IS did not have a significant influence on worsening of GIT involvement.

Table:

Baseline characteristicsNon-inception cohort(n=598)Inception cohort(n=236)Female, n(%)504 (85)180 (76)Age, mean(SD)55 (13)56 (14)Disease duration non Raynaud-Phenomenon, median (IQR)8.8 (4.8-14.4)0.7 (0.3-1.2)Diffuse cutaneous subset, n(%)119 (20)67 (28)Interstitial lung disease, n(%)233 (39)71 (30)Anti-centromere, n(%)296 (50)96 (41)Immunosuppresive treatment at baseline, n(%)102 (17)44 (19))Duration of treatment at baseline in years, mean (SD)4.1 (4.8)1.2 (2.9)Methotrexate, n(%)54 (9)24 (10)Mycophenolate mofetil, n(%)25 (4)13 (6)Hydroxycholoquine, n(%)20 (3)7 (3)Cyclofosfamide, n(%)1 (1)10 (4)Azathioprine, n(%)11 (2)2 (1)Corticosteroids, n(%)58 (10)27 (11)

Acknowledgments:

NA

Disclosure of Interests:

Nina van Leeuwen: None declared, Håvard Fretheim: None declared, Øyvind Molberg: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Jeska de Vries-Bouwstra: None declared, Anna-Maria Hoffmann-Vold Grant/research support from: Boehringer Ingelheim, Consultant of: Boehringer Ingelheim, Actelion, Bayer, GlaxoSmithKline, Speakers bureau: Boehringer Ingelheim, Actelion, Roche

AB1243 TRAINING AND VALIDATION OF A MULTIVARIATE PREDICTOR OF RISK OF RADIOGRAPHIC PROGRESSION FOR PATIENTS WITH RHEUMATOID ARTHRITIS

Background:

The multi-biomarker disease activity (MBDA) score, adjusted for age, sex and adiposity (MBDAadj), has been shown to be better than several conventional disease activity measures for predicting risk for radiographic progression (RP) in patients with rheumatoid arthritis (RA).1Serologic status and other non-disease activity measures are also predictive of RP risk. Combining them with the MBDAadjshould result in a stronger prognostic test for RP than any one measure alone.

Objectives:

Develop a multivariate model for predicting risk for RP that includes the adjusted MBDA score and other known predictors of RP.

Methods:

Four RA cohorts were used, two for training (OPERA and BRASS, n=555) and two for validation (SWEFOT and Leiden, n=397). Each pair of cohorts was heterogeneous in disease duration and treatment history. BMI data were not available for one validation cohort, so a BMI surrogate was modeled using forward selection with the two training cohorts and 3 others (CERTAIN, InFoRM, RACER) (N=1411). An RP risk score was then trained using forward selection in a linear mixed-effects regression, considering disease-related and demographic variables as predictors of change in modified total Sharp score over one year (ΔmTSS), with a random effect on cohort. The RP risk score was validated as a predictor of RP with two cutoffs (ΔmTSS >3 and >5) using logistic mixed-effects regression. Odds ratios (OR) and 95% profile likelihood-based confidence intervals (CI) were calculated from the models and significance was assessed by likelihood ratio tests. Risk curves were generated to show probability of RP as a function of the RP risk score.

Results:

The BMI surrogate included leptin, sex, age and age2and correlated well with BMI (ρ = 0.76). In training, the most significant independent predictors of RP were MBDAadj(p = 0.00020), seropositivity (p = 9.3 x 10-5), BMI surrogate score (p = 0.013) and use of targeted therapy (p = 0.0026). The final model was: RP risk score = 0.024 x MBDAadj+ 0.093 if seropositive – 0.063 x BMI surrogate score – 0.61 if using a targeted therapy. In validation, the OR (95% CI) of the RP risk score for predicting ΔTSS >3 or >5 were 2.2 (1.6, 3.2) (p = 2.6 × 10-6) and 3.1 (2.0, 5.0) (p = 5.7 × 10-8), respectively (Figure 1). The odds of a patient having RP increases by 50% for each 21-unit or 15-unit increase in MBDAadj, for RP defined as ΔTSS >3 or >5, respectively.

Figure 1.

Conclusion:

A multivariate model containing adjusted MBDA score, seropositivity, a BMI surrogate and use of targeted therapy has been trained and validated as a prognostic test for radiographic progression in RA.

References:

[1]Curtis, et al.Rheumatology [Oxford].2018;58:874

Disclosure of Interests:

Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Michael E. Weinblatt Grant/research support from: BMS, Amgen, Lilly, Crescendo and Sonofi-Regeneron, Consultant of: Horizon Therapeutics, Bristol-Myers Squibb, Amgen, Abbvie, Crescendo, Lilly, Pfizer, Roche, Gilead, Nancy Shadick Grant/research support from: Mallinckrodt, BMS, Lilly, Amgen, Crescendo Biosciences, and Sanofi-Regeneron, Consultant of: BMS, Cecilie Heegaard Brahe: 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, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Saedis Saevarsdottir Employee of: Part-time at deCODE Genetics/Amgen Inc, working on genetic research unrelated to this project, Megan Horton Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Brent Mabey Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Darl Flake Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Rotem Ben-Shachar Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Eric Sasso Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Alexander Gutin Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Elena Hitraya Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Jerry Lanchbury Shareholder of: Myriad Genetics, Inc., Employee of: Myriad Genetics, Inc., Jeffrey Curtis Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB

SAT0297 DIFFERENTIAL PHENOTYPES OF DISEASE-SPECIFIC AUTO-REACTIVE B CELL RESPONSES IN PATIENTS WITH SYSTEMIC SCLEROSIS

Background:

Systemic Sclerosis (SSc) carries the highest mortality burden among the rheumatic diseases. >95% of SSc patients harbor autoantibodies. Anti-topoisomerase antibodies (ATA) and anti-centromere antibodies (ACA) are most prevalent, mutually exclusive in individual patients, associate with distinct disease phenotypes and predict disease. Whether and how these auto-reactive B cell responses contribute to disease, however, is currently unclear.

Objectives:

To delineate phenotypic and functional characteristics of anti-topoisomerase and anti-centromere specific B cell responses in individual patients with SSc.

Methods:

Peripheral blood mononuclear cells (PBMC) obtained from ATA- and ACA-positive SSc patients were cultured without stimulation or in the presence of CD40L-expressing fibroblasts, IL-21 and BAFF. In addition, PBMC were depleted of circulating plasmablasts (CD19+CD20-CD27++) by fluorescence activated cell sorting (FACS), and isolated plasmablasts were cultured separately. ATA- and ACA-IgG and -IgA were measured in culture supernatants by ELISA. B cell subsets were defined by flow cytometry. Healthy donors and patients with rheumatoid arthritis served as controls.

Results:

We observed that ATA- and ACA-positive SSc patients harbour circulating B cells that secrete either ATA-IgG or ACA-IgG upon stimulation, depending on their serotype. In addition, we noted spontaneous secretion of ATA-IgG and, more remarkably, extensive secretion of ATA-IgA in ATA-positive patients. This degree of spontaneous, antigen-specific IgA secretion was specific for the ATA response in ATA-positive patients, while spontaneous ACA-IgA secretion was undetectable in the ACA-positive patient group. FACS experiments showed that spontaneously ATA-IgA secreting B cells were primarily present in the plasmablast compartment.

Conclusion:

Our findings demonstrate that ATA-positive SSc patients harbour an activated ATA-IgG and ATA-IgA B cell response, as indicated by the spontaneous secretion of both ATA isotypes by circulating plasmablasts. Remarkably, the ACA B cell response was far less active and lacked the active IgA component which suggests a difference in the triggers driving these autoreactive B cell responses in patients. Moreover, the remarkable ATA-IgA secretion points towards a potential mucosal origin of the ATA response.

Disclosure of Interests:

Corrie Wortel: None declared, Nina van Leeuwen: None declared, Maaike Boonstra: None declared, Rene Toes: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Jeska de Vries-Bouwstra: None declared, Hans Ulrich Scherer Grant/research support from: Bristol Myers Squibb, Sanofi, Pfizer, Speakers bureau: Pfizer, Lilly, Roche, Abbvie

OP0219 MORTALITY OF RHEUMATOID ARTHRITIS PATIENTS, TREATED TO TARGET AT LOW DISEASE ACTIVITY: 17-YEARS FOLLOW-UP OF THE BEST COHORT

Background:

Rheumatoid arthritis is known to be associated with increased mortality over the years when compared to the general population. In the BeSt study, 508 patients were treated to target (Disease Activity Score ≤2.4) for 10 years between April 2000 and August 2012. At the end of the initial study follow-up, the observed mortality in the BeSt cohort was similar to mortality in the general population. In the current study we evaluated the mortality in the BeSt cohort after 17 years follow-up and compared it to the general Dutch population.

Objectives:

Evaluate long-term mortality in the BeSt study cohort.

Methods:

In the BeSt study 508 patients diagnosed with early RA were randomized to four initial treatment strategies: 1. Sequential monotherapy; 2. Step-up combination therapy; 3. Initial combination therapy with prednisone; or 4. Initial combination therapy with infliximab. During the 10-year follow-up period treatment was steered at low disease activity (DAS ≤2.4) and adjusted every three months when necessary. After 10-years patients were treated and followed-up according to regular care. We explored mortality through the Dutch state registry for mortality (Centrum voor Familiegeschiedenis) and treating rheumatologist. Mortality in the BeSt cohort was compared to the general Dutch population (Statistics Netherlands) matched by gender, age and calendar year using the standardized mortality ratio (SMR). Kaplan-Meier curves and the log-rank test were used to compare survival among the initial treatment strategies.

Results:

The mean duration of follow-up in non-deceased patients was 17 years (range 16-18). In total, 143 patients died (28%) compared to a total of 105 (21%) expected deaths in the reference population. The overall SMR after 17 years was 1.37 (95% CI: 1.16-1.61). Within the study population, no statistically significant difference in survival-curves was observed between the four initial treatment strategies (log-rank p=0.76) (table 1, and figure 1).

Table 1.

BeSt study cohort mortality - stratified for initial treatment strategy

Sequential monotherapyn=126Step-up combination therapyn=121Initial combination therapy with prednisonen=133Initial combination therapy with infliximabn=128N (%) †38 (30)31 (26)41 (31)33 (26)SMR (95% CI)1.41 (1.03–1.94)1.20 (0.84-1.70)1.53 (1.13-2.09)1.31 (0.93-1.85)

SMR: standardized mortality ratio (number observed deaths/number expected deaths); CI: confidence interval.Conclusion:

Figure 1.

Survival curves – stratified for initial treatment strategy

After a mean of 17 years follow-up the mortality was increased in the BeSt study cohort when compared to the general Dutch population. We observed no difference in survival curves among the four treatment strategies.

Disclosure of Interests:

Johanna M. Maassen: None declared, Yvonne Goekoop-Ruiterman: None declared, Hans van Groenendael: None declared, WIllem Lems Grant/research support from: Pfizer, Consultant of: Lilly, Pfizer, Pit Kerstens: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Cornelia Allaart: None declared

FRI0090 MAINTENANCE OF CLINICAL RESPONSE WITH ABATACEPT IN COMBINATION WITH MTX IN INDIVIDUAL PATIENTS WITH EARLY RA WHO ARE MTX-NAÏVE AND ANTI-CITRULLINATED PROTEIN ANTIBODY (ACPA)+: RESULTS FROM THE INDUCTION PERIOD OF AVERT-2, A RANDOMISED PHASE IIIB STUDY

Background:

In the 56-wk induction period (IP) of the Phase IIIbAssessingVeryEarlyRATreatment (AVERT)-2 trial (NCT02504268), more patients (pts) achieved SDAI remission (≤3.3) with abatacept (ABA) + MTX vs ABA placebo (PBO) + MTX at IP Wk 52.1It is unknown whether each individual pt within a treatment (Tx) group achieves and sustains the same efficacy endpoints at all time points during the IP.

Objectives:

To investigate whether ABA effectiveness is sustained by individual pts who achieved SDAI remission (≤3.3), SDAI low disease activity (LDA; >3.3–11), DAS28 (CRP) <2.6, ACR50/70 response or Boolean remission at IP Wk 24 (AVERT-2 primary endpoint) and both Wks 40 and 52 (Wks 40/52).

Methods:

Pts were randomised 3:2 to blinded SC ABA (125 mg/wk) + MTX or ABA PBO + MTX induction Tx for 56 wks. Key inclusion criteria: age ≥18 yrs; RA diagnosis (ACR/EULAR 2010 criteria); RA duration ≤6 mos; SDAI >11; ACPA+; CRP >3 mg/L or ESR ≥28 mm/h; TJC ≥3 and SJC ≥3; DMARD naïve. Response rates were investigated by Tx arm in the cohort 1 analysis population (all randomised pts treated in the IP [intent-to-treat analysis]).

Results:

Of randomised cohort 1, 752 pts were treated during the IP: 451 with ABA + MTX and 301 with ABA PBO + MTX. Baseline characteristics were similar across Tx arms.1Stringent SDAI remission endpoint at IP Wk 24 was achieved by 22% of ABA + MTX-treated pts; of these, 56% sustained SDAI remission at IP Wks 40/52 (Table). A similar proportion of ABA + MTX-treated pts achieved (17%) and sustained (58%) Boolean remission at IP Wks 24 and 40/52. At IP Wk 24, 42% of ABA + MTX-treated pts achieved DAS28 (CRP) <2.6 and 74% sustained DAS28 (CRP) <2.6 to IP Wks 40/52; a high proportion of patients sustained ACR50/70 responses at IP Wks 40/52 (83% and 79%, respectively). A lower proportion of pts sustained SDAI LDA to IP Wks 40/52 vs other endpoints (Table). Most efficacy endpoints were achieved by fewer pts who received ABA PBO + MTX than ABA + MTX (Table); among responders in this Tx group, fewer sustained remission at Wks 40/52, which correlates with a higher proportion of pts sustaining SDAI LDA at Wks 40/52 with ABA PBO + MTX than ABA + MTX.

Conclusion:

The majority of individual pts with RA who achieved clinically stringent endpoints such as SDAI remission, DAS28 (CRP) <2.6 or Boolean remission, as well as clinically meaningful endpoints such as ACR50/70 at IP Wk 24 with weekly SC abatacept, sustained their responses to Wks 40/52. The high proportion of patients achieving early stringent remission and response to SC abatacept by individual pts may be indicative of sustained efficacy over time.

References:

[1]Emery P, et al. ACR 2018; San Diego, USA: Poster 563.

Table .

Proportion of Pts With Response at IP Wk 24 Who Also Achieved Remission at Wks 40/52

EndpointResponders at IP Wk 24, n (%)Responders at IP Wk 24 and Wks 40/52, n/N (%)ABA + MTX(n=451)ABA PBO + MTX(n=301)ABA + MTX*ABA PBO + MTX*SDAI remission (≤3.3)100 (22)40 (13)56/100 (56)17/40 (43)SDAI low disease activity (>3.3–11)167 (37)82 (27)46/167 (28)32/82 (39)DAS28 (CRP) <2.6188 (42)78 (26)139/188 (74)43/78 (55)ACR50 response†260 (58)125 (42)215/260 (83)92/125 (74)ACR70 response†156 (35)66 (22)123/156 (79)42/66 (64)Boolean remission76 (17)29 (10)44/76 (58)8/29 (28)

*% based on number of pts within each Tx group who achieved response at IP Wk 24 (denominator);†Response at IP Wks 24 and 52

Acknowledgments:

Lola Parfitt (medical writing, Caudex; funding: Bristol-Myers Squibb)

Disclosure of Interests:

Paul Emery Grant/research support from: AbbVie, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer, Roche (all paid to employer), Consultant of: AbbVie (consultant, clinical trials, advisor), Bristol-Myers Squibb (consultant, clinical trials, advisor), Lilly (clinical trials, advisor), Merck Sharp & Dohme (consultant, clinical trials, advisor), Novartis (consultant, clinical trials, advisor), Pfizer (consultant, clinical trials, advisor), Roche (consultant, clinical trials, advisor), Samsung (clinical trials, advisor), Sandoz (clinical trials, advisor), UCB (consultant, clinical trials, advisor), Yoshiya Tanaka Grant/research support from: Asahi-kasei, Astellas, Mitsubishi-Tanabe, Chugai, Takeda, Sanofi, Bristol-Myers, UCB, Daiichi-Sankyo, Eisai, Pfizer, and Ono, Consultant of: Abbvie, Astellas, Bristol-Myers Squibb, Eli Lilly, Pfizer, Speakers bureau: Daiichi-Sankyo, Astellas, Chugai, Eli Lilly, Pfizer, AbbVie, YL Biologics, Bristol-Myers, Takeda, Mitsubishi-Tanabe, Novartis, Eisai, Janssen, Sanofi, UCB, and Teijin, Vivian Bykerk: None declared, Clifton Bingham Grant/research support from: Bristol-Myers Squibb, Consultant of: Bristol-Myers Squibb, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Gustavo Citera Grant/research support from: AbbVie, Amgen, Eli Lilly, Gema, Genzyme, Novartis and Pfizer Inc, Consultant of: AbbVie, Amgen, Eli Lilly, Gema, Genzyme, Novartis and Pfizer Inc, Kuan-Hsiang Gary Huang Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Sean Connolly Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Yedid Elbez Consultant of: Bristol-Myers Squibb, Robert Wong Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Karissa Lozenski Employee of: Bristol-Myers Squibb, Roy Fleischmann Grant/research support from: AbbVie, Akros, Amgen, AstraZeneca, Bristol-Myers Squibb, Boehringer, IngelhCentrexion, Eli Lilly, EMD Serono, Genentech, Gilead, Janssen, Merck, Nektar, Novartis, Pfizer, Regeneron Pharmaceuticals, Inc., Roche, Samsung, Sandoz, Sanofi Genzyme, Selecta, Taiho, UCB, Consultant of: AbbVie, ACEA, Amgen, Bristol-Myers Squibb, Eli Lilly, Gilead, GlaxoSmithKline, Novartis, Pfizer, Sanofi Genzyme, UCB

AB0430 MORTALITY IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS AND NEUROPSYCHIATRIC SYMPTOMS

Background:

Little is known about mortality in patients with systemic lupus erythematosus (SLE) presenting with neuropsychiatric (NP) symptoms.

Objectives:

We aimed to evaluate all-cause and cause-specific mortality in patients with SLE and NP symptoms.

Methods:

All patients with the clinical diagnosis of SLE of 18 years and older that visited the tertiary referral NPSLE clinic of the Leiden University Medical Center between 2007-2018 and signed informed consent were included in this study. Patients were classified as NPSLE if NP symptoms were attributed to SLE and immunosuppressive or anticoagulant therapy was initiated, otherwise patients were classified as non-NPSLE. Municipal registries were checked for current status (alive/deceased). Electronical medical files were studied for clinical characteristics and cause of death. Standardized mortality ratios (SMRs) and 95% confidence intervals were calculated using data from the general Dutch population. In addition, a rate ratio (RR) was calculated using direct standardization to compare mortality in NPSLE with non-NPSLE patients.

Results:

351 patients with the clinical diagnosis of SLE were included, of which 149 patients were classified as NPSLE (42.5%). Compared with the general population, mortality was increased five times in NPSLE (SMR 5.0, 95% CI: 2.6-8.5) and nearly four times in non-NPSLE patients (SMR 3.7, 95% CI: 2.2-6.0), as shown in Table 1. Risk of death due to cardiovascular disease (CVD) was increased in non-NPSLE patients (SMR 6.2, 95% CI: 2.0-14.6) and an increased risk of death to infections was present in both NPSLE and non-NPSLE patients ((SMR 29.9, 95% CI: 3.5 – 105) and SMR 91.3 (95% CI: 18.8 – 266) respectively). However, mortality did not differ between NPSLE and non-NPSLE patients (RR 1.0, 95% CI: 0.5 – 2.0).

Table 1.

All-cause mortality in SLE patients presenting with neuropsychiatric symptoms attributed to SLE (NPSLE) or to other causes (non-NPSLE)

NPSLE(N = 149)Non-NPSLE(N = 202)Deaths (N, %)13 (8.7)17 (8.4)Age at death (median, range)49 (32 – 79)59 (20 – 89)Follow-up time (years)9061047Crude mortality rate (per 1000 PY)14.316.2All-cause mortality*Female5.5 (2.8 – 9.6)3.4 (1.9 – 5.7)Male2.3 (0.1 - 12.8)6.2 (1.3 – 18.2)Combined5.0 (2.6 – 8.5)3.7 (2.2 – 6.0)

*Standardized mortality ratio, ratio of the observed and expected number of deaths

Conclusion:

Mortality was increased in both NPSLE and non-NPSLE patients in comparison with the general population, but there was no difference in mortality between NPSLE and non-NPSLE patients. Risk of death due to infections was increased in both groups.

Disclosure of Interests:

Rory Monahan: None declared, Rolf Fronczek: None declared, Jeroen Eikenboom: None declared, Huub Middelkoop: None declared, L.J.J. Beaart- van de Voorde: None declared, Gisela Terwindt: None declared, Nic van der Wee: None declared, Frits Rosendaal: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Margreet Kloppenburg: None declared, G.M. Steup-Beekman: None declared

FRI0098 ASSOCIATION BETWEEN THE SEROLOGIC STATUS OF ISOTYPE-SPECIFIC AUTOANTIBODIES AND THERAPEUTIC EFFICACY IN RHEUMATOID ARTHRITIS PATIENTS TREATED WITH ABATACEPT: A PROSPECTIVE ULTRASOUND COHORT STUDY IN JAPAN

Background:

The presence of anti-cyclic citrullinated protein antibodies (ACPA) and anti-carbamylated protein (anti-CarP) antibody is specific for rheumatoid arthritis (RA). Recently, it was reported that the serological status of ACPA is associated with the therapeutic response of the T-cell co-stimulation blocker abatacept (1, 2). However, it is currently unclear whether the serological status of each isotype levels of these autoantibodies before treatment introduction or the changes during treatment are associated with the therapeutic response of abatacept.

Objectives:

To evaluate longitudinal changes in the isotypes of ACPA and anti-CarP in RA patients treated with abatacept, and associations between the baseline serological status/ these changes and clinical response/ ultrasonographic response.

Methods:

This study is part of an ongoing non-randomized multicenter prospective cohort study of patients with active RA who received biological or targeted DMARD therapy at 13 participating rheumatology centers from the Kyushu region of Japan since June 2013 (3). As of the present report, we enrolled 43 consecutive Japanese patients with active RA who have introduced treatment with abatacept and had finished the first 12-month observation period. We evaluated disease activity by clinical composite measure and ultrasound score at baseline, 3, 6, 9 and 12 months. In ultrasound of bilateral hands from 22 sites, the findings obtained by gray-scale (GS) and power Doppler (PD) assessments were graded on a semi-quantitative scale from 0 to 3 and the sum of GS or PD scores was used as the total GS or PD score. The serum levels of IgG/IgM/IgA-type of ACPA and anti-CarP were measured by the ELISA method in Leiden University Medical Center. We evaluated the association between serologic status of autoantibodies and clinical /ultrasonographic therapeutic efficacy.

Results:

The median age was 72 years, and the disease duration was 54 months. Methotrexate was concomitant in 22 (51%). Sixteen (37%) patients had a history of previous use of biological DMARDs. Nineteen (44%) and 23 (54%) patients achieved SDAI remission and PD remission (total PD score =0) at 12 months, respectively. The serum levels of all isotypes of ACPA/anti-CarP significantly decreased at 12 months from baseline. The reduction of IgM-ACPA level significantly correlated with the reduction of SDAI (rs=0.33, p=0.031) and total PD score (rs=0.49, p=0.0007). Both clinical and ultrasonographic therapeutic responses were better in patients with the detectable IgM-ACPA at baseline than in patients without that (Figure): the reduction of SDAI (p=0.0078) and that of total PD score (p=0.0079) were significantly larger in the former than in the latter. All isotype of anti-CarP did not associate with therapeutic response.

Conclusion:

Treatment of abatacept induced to the reduction of the autoantibody levels. The IgM-ACPA level at baseline and the change in IgM-ACPA associated with both clinical and ultrasonographic therapeutic response in patients treated with abatacept. IgM-ACPA, compared with usual IgG-ACPA, better reflects the treatment response of abatcept in patients with RA

References:

[1]Ann Rheum Dis. 2016;75:709, 2) RMD Open. 2018;4:e000564, 3)Arthritis Care Res (Hoboken). 2018;70:1719.

Acknowledgments:

We have acknowledged for all the members of Kyushu multicenter rheumatoid arthritis ultrasound prospective observational cohort study group.

Disclosure of Interests:

Shin-ya Kawashiri Grant/research support from: This work was supported by Bristol-Myers Squibb and Ono Pharmaceutical. co., Yushiro Endo: None declared, Ayako Nishino: None declared, Toshimasa Shimizu: None declared, Yukitaka Ueki: None declared, Nobutaka Eiraku: None declared, Akitomo Okada: None declared, Naoki Matsuoka: None declared, Tamami Yoshitama: None declared, Hideki Nakamura: None declared, Mami Tamai: None declared, Tomoki Origuchi: None declared, Rene Toes: None declared, Thomas Huizinga Grant/research support from: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Consultant of: Ablynx, Bristol-Myers Squibb, Roche, Sanofi, Atsushi Kawakami: None declared