Treatment overview of axial spondyloarthritis in 2023

The treatment of patients with axial spondyloarthritis (axSpA) is characterized by non-pharmacological and pharmacological treatment options. It may depend on the type and extent of musculoskeletal and extramusculoskeletal manifestations. Recent data on non-pharmacological treatment options, such as physical activity, physiotherapy, and modification of lifestyle factors, are summarized in this review. Moreover, we have provided an overview on non-steroidal anti-inflammatory drugs and the ever-expanding number of biological and targeted synthetic disease-modifying antirheumatic drugs (bDMARDs and tsDMARDs, respectively). In addition to data on efficacy and safety, the review also encompasses data on switching/cycling, tapering, and treatment selection for specific patient subgroups to optimize treatment outcomes.

OP0102 THE SYNOVIUM IN CHRONIC INFLAMMATORY JOINT DISEASES: COMPARISON OF CLINICAL, HISTOLOGICAL AND scRNA-SEQ Data BETWEEN RA, PsA, SpA AND UA

Background

The synovium is the primary location of inflammation in various rheumatic diseases. However, specific differences of joint inflammation have not been explored on a single-cell level so far.

Objectives

To characterize the synovium of rheumatoid arthritis (RA), psoriatic arthritis (PsA), spondyloarthritis (SpA) and undifferentiated arthritis (UA) based on clinical and histological characteristics and single-cell RNA sequencing (scRNA-seq).

Methods

We performed ultrasound (US) guided synovial biopsy in patients fulfilling classification criteria: 10 RA, 4 PsA, 4 SpA and 3 UA. 3 osteoarthritis (OA) samples were obtained from surgery. Clinical data were collected at time of biopsy. Histological analysis of the synovium included Krenn score [1], synovial pathotype [2], vascularization [3] and presence of lymphoid follicles. OA histology was not available. We prepared scRNA-seq libraries with 10X Genomics and sequenced on NovaSeq 6000. ScRNA-seq data was analysed with Cell Ranger, Seurat and Harmony R packages. We selected overexpressed genes using log2 ratio (>0.25) and FDR adjusted p value < 0.05.

Results

Patients showed typical disease characteristics. In RA, 6/10 were seropositive, 8/10 were female and median age was 59 years (IQR 12). Patients with PsA, SpA and UA were seronegative. 2/4 SpA and 1/4 PsA patients were HLA-B27 positive. Median age was 53 years in PsA (IQR 14.2), 52.5 in SpA (IQR 14.8) and 53 in UA (IQR 3.5). In PsA 3/4, SpA 2/4 and UA 1/3 patients were male.

RA joints had significantly higher B-Mode US scores compared to PsA and SpA joints (mean B-Mode Score: RA 2.7; PsA 2; SpA 2). Correspondingly, RA patients reported a significantly higher amount of swelling in the biopsied joint compared to PsA and SpA (mean “Swelling-Score”: RA 6.85; PsA 4.25; SpA 4).

Histology showed no clear differences in the cell composition; most joints showed a lympho-myeloid pathotype. Mean Krenn Score was highest in RA (4.78) and lowest in SpA (3.33). PD-Mode US score showed a significant positive association with histological vascularization. Lymphoid follicles were significantly more seen in RA compared to all other diseases.

Integration of scRNA-seq data revealed 16 cell clusters with respective marker gene: PRG4 synovial fibroblasts (SF), THY1 SF, ACTA2 smooth muscle cells, VWF endothelial cells, TPSB2 mastcells, IGHG plasma cells, CD79 B-cells, CD69 T-Cells, CCL5 natural killer cells, DMTN Treg-cells, CXC2 neutrophil granulocytes, TREM2 macrophages, CD48 macrophages, CLEC10A macrophages, CD4 dendritic cells, MKI67 proliferating cells. OA had the lowest and RA the highest number of inflammatory cells within the synovium. SpA synovium had the highest number of neutrophils. Re-Clustering of only SF revealed 4 subtypes: PRG4 SF (3578 cells), CXCL12 SF (4539 cells), POSTN SF (2387 cells) and MFAP5 SF (1734 cells). Top 5 marker genes are shown in the Table 1. Most differentially expressed genes in OA were found in PRG4 SF; the previously described OA specific gene CSN1S1 [3] was not only underexpressed in RA but also in other inflammatory joint diseases (Figure 1). PGF, a gene associated with pathological angiogenesis, was one of the top discriminator genes, highly expressed in PsA SF (mostly PRG4 SF). RA SF (mostly CXCL12 SF) showed a high expression of CHI3L1, which is a RA specific autoantigen. High expression of hemoglobin genes was found in SpA PRG4 SF; an unexplored but previously described finding [5, 6].

Table 1.

Top 5 synovial fibroblast (SF) marker genes.

ClusterGenePRG4 SFPRG4CSN1S1MMP3CRTAC1HTRA1CXCL12 SFAPOECXCL12CCL2PTGDSCD74POSTN SFCOMPCOL1A1POSTNCILPPTNMFAP5 SFMFAP5SFRP2APODCXCL14CFD

Conclusion

We were able to compare the synovium of the most common chronic inflammatory joint diseases on various levels for the first time. The findings set the path for future diagnostic, prognostic, and therapeutic approaches in inflammatory joint diseases.

References

[1]Krenn et al, Histopath. 2006

[2]Humby et al, ARD 2019

[3]Kennedy et al, AR 2010

[4]Galligan et al, GI 2007

[5]Yeremenko et al, A&R 2012

[6]Park et al, JRD 2016

Disclosure of Interests

None declared

OP0175 TYPE OF mRNA COVID-19 VACCINE AND TREATMENT INFLUENCE ANTIBODY KINETICS IN PATIENTS WITH INFLAMMATORY RHEUMATIC DISEASES

Background

Patients on immunomodulatory treatments mount an attenuated immune response following mRNA COVID-19 vaccination, yet long-term studies of vaccine-induced anti-SARS-CoV-2 antibody (Ab) kinetics are missing.

Objectives

In this prospective observational study, we mapped the humoral antibody response to mRNA COVID-19 vaccines up to 24 weeks post full vaccination in patients with inflammatory rheumatic diseases (IRDs). We aimed to assess differences due to treatment, age, past SARS-CoV-2 infection, and vaccine (BNT162b2 vs. mRNA-1273).

Methods

Adult patients from the SCQM cohort who assented to an mRNA COVID-19 vaccine were recruited between 3/21 – 9/21. Participants answered questionnaires via an app and received kits for the self-collection of capillary blood samples at baseline, 4, 12, and 24 weeks post full vaccination. Samples were tested for IgG Ab against the S1 domain of the SARS-CoV-2 spike protein (anti-S1-IgG) using the EUROIMMUN ELISA. To examine differences in Ab titres arising from the defined parameters, while accounting for inter-assay variability, mixed effects continuous outcome logistic regression models were applied at each timepoint.

Results

Samples were obtained from 570 patients: 67% female, mean age 53 y (SD 12 y) with 37% RA, 36% axSpA, 21% PsA, and 6% UA (undifferentiated arthritis), on no medication (no DMARDs & no glucocorticoids; 15%), csDMARDs (10%), TNFi (48%), IL-1/6/17/23i (14%), JAKi (6%), rituximab (RTX; 4%), or abatacept (ABA; 2%) in mono/combination therapy at the first vaccination. 10% of patients had a past SARS-CoV-2 infection, 54% received BNT162b2, 46% mRNA-1273.

For any Ab threshold, the odds of having a higher Ab titre at 4, 12, and 24 weeks post full vaccination were 3.3 – 4 times higher with mRNA-1273 compared to BNT162b2 (Table 1, Figure 1). TNFi, JAKi, RTX, and ABA as monotherapy resulted in significantly lower Ab levels compared to no medication at almost all timepoints. In combination therapy, TNFi, IL-1/6/17/23i, RTX, and csDMARDs led to consistently lower Ab titres at all timepoints compared to respective monotherapy.

Table 1.

The OR of being above a given Ab threshold, regardless of the threshold. Ref. levels: mean age, no medication, no past SARS-CoV-2 inf., BNT162b2. Included in model but not shown: diagnosis, infrequently used medication (all non-signif.)

Weeks post full vacc.41224OR (95% CI); pAge0.96 (0.94 – 0.97)****0.98 (0.96 – 0.996)*0.98 (0.97 – 1.00)mRNA-1273 (vs BNT162b2)3.28 (2.34 – 4.61)****3.96 (2.83 – 5.54)****3.94 (2.93 – 5.50)****Past COVID inf. (vs none)7.56 (4.32 – 13.2)****8.14 (4.78 – 13.86)****11.65 (6.62 – 20.50)****csDMARD†1.27 (0.67 – 2.41)1.78 (0.94 – 3.35)1.70 (0.86 – 3.36)TNFi†0.46 (0.28 – 0.71)****0.30 (0.19 – 0.48)****0.13 (0.081 – 0.22)****IL-1/6/17/23i†0.97 (0.54 – 1.75)1.04 (0.57 – 1.89)0.89 (0.49 – 1.64)JAKi†0.38 (0.16 – 0.91)*0.38 (0.16 – 0.91)*0.53 (0.22 – 1.28)RTX†0.078 (0.013 – 0.46)**0.078 (0.015 – 0.42)**0.16 (0.037 – 0.71)*ABA†0.14 (0.039 – 0.51)**0.087 (0.022 – 0.35)***0.068 (0.017 – 0.27)***Interactions§Age:vaccine‡1.04 (1.02 – 1.07)**1.02 (0.99 – 1.05)1.03 (1.0008 – 1.058)*csDMARD:combi0.12 (0.02 – 0.70)*0.17 (0.029 – 0.95)*0.11 (0.023 – 0.56)**TNFi:combi0.34 (0.20 – 0.59)***0.37 (0.22 – 0.61)***0.36 (0.21 – 0.62)***IL-1/6/17/23i:combi0.26 (0.09 – 0.78)*0.25 (0.085 – 0.70)**0.20 (0.071 – 0.58)**JAKi:combi1.76 (0.33 – 9.44)1.23 (0.32 – 4.70)0.95 (0.25 – 3.65)RTX:combi0.11 (0.01 – 0.87)*0.095 (0.012 – 0.73)*0.085 (0.0091 – 0.79)*ABA:combi1.75 (0.25 – 12.2)0.74 (0.096 – 5.75)0.51 (0.073 – 3.62)

* p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001;

†Medication as monoth. vs no medication

‡Interaction terms showing how OR of mRNA-1273 (vs BNT162b2) increases with age

§Interaction terms with medications: medication in combination th. vs medication as monoth.

Conclusion

Compared to no medication, some immunomodulatory therapies resulted in markedly lower Ab levels at all timepoints. In IRD patients, a past SARS-CoV-2 infection resulted in strikingly increased immunogenicity, as did mRNA-1273 compared to BNT162b2.

Acknowledgements

This study is investigator-initiated and received independent financial support from Moderna Switzerland GmbH. The SCQM thanks the patients for their participation in this study. A list of rheumatology offices and hospitals that contribute to the SCQM registries can be found on www.scqm.ch/institutions. The SCQM is financially supported by pharmaceutical industries and donors. A list of financial supporters can be found on www.scqm.ch/sponsors.

Disclosure of Interests

Catherine Elizabeth Raptis Grant/research support from: The study presented in the abstract is investigator-initiated and received independent financial support from Moderna Switzerland GmbH. The SCQM is financially supported by pharmaceutical industries and donors. A list of financial supporters can be found on www.scqm.ch/sponsors, Diego Olivier Andrey: None declared, Christos Polysopoulos Grant/research support from: The study presented in the abstract is investigator-initiated and received independent financial support from Moderna Switzerland GmbH. The SCQM is financially supported by pharmaceutical industries and donors. A list of financial supporters can be found on www.scqm.ch/sponsors, Christoph Berger: None declared, Adrian Ciurea: None declared, Pierre Lescuyer: None declared, Tanja Maletic Grant/research support from: The study presented in the abstract is investigator-initiated and received independent financial support from Moderna Switzerland GmbH. The SCQM is financially supported by pharmaceutical industries and donors. A list of financial supporters can be found on www.scqm.ch/sponsors, Myriam Riek Grant/research support from: The study presented in the abstract is investigator-initiated and received independent financial support from Moderna Switzerland GmbH. The SCQM is financially supported by pharmaceutical industries and donors. A list of financial supporters can be found on www.scqm.ch/sponsors, Almut Scherer Grant/research support from: The study presented in the abstract is investigator-initiated and received independent financial support from Moderna Switzerland GmbH. The SCQM is financially supported by pharmaceutical industries and donors. A list of financial supporters can be found on www.scqm.ch/sponsors, Isabell von Loga Grant/research support from: The study presented in the abstract is investigator-initiated and received independent financial support from Moderna Switzerland GmbH. The SCQM is financially supported by pharmaceutical industries and donors. A list of financial supporters can be found on www.scqm.ch/sponsors, Judith Safford: None declared, Kim Lauper Speakers bureau: Kim Lauper reports consulting fees for Pfizer and speakers fees for Pfizer, Viatris and Celltrion outside of the submitted work., Consultant of: Kim Lauper reports consulting fees for Pfizer and speakers fees for Pfizer, Viatris and Celltrion outside of the submitted work., Burkhard Moeller: None declared, Nicolas Vuilleumier: None declared, Axel Finckh Speakers bureau: Axel Finckh has received consultancies or speaker honoraria for AbbVie, BMS, Eli-Lilly, Gilead, Pfizer, Sanofi, and UCB outside of the submitted work, Consultant of: Axel Finckh has received consultancies or speaker honoraria for AbbVie, BMS, Eli-Lilly, Gilead, Pfizer, Sanofi, and UCB outside of the submitted work, Grant/research support from: Axel Finckh has received research support from AbbVie, Eli-Lilly, Galapagos, and Pfizer outside of the submitted work, Andrea Rubbert-Roth: None declared

OP0020 SEX DIFFERENCES IN EFFECTIVENESS OF FIRST-LINE TUMOR NECROSIS FACTOR INHIBITORS IN AXIAL SPONDYLOARTHRITIS; RESULTS FROM FIFTEEN COUNTRIES IN THE EuroSpA RESEARCH COLLABORATION NETWORK

Background

Evidence reveals sex differences in physiology, disease presentation and response to treatment in axial spondyloarthritis (axSpA). Pooled data from four randomized controlled trials demonstrated reduced treatment efficacy of a tumor necrosis factor inhibitor (TNFi) in females compared to males with ankylosing spondylitis1. However, real-life evidence confirming these data in large cohorts is scarce. We sought to validate prior studies using data from a large multinational cohort based on real-life clinical practice.

Objectives

To investigate sex differences in treatment response and drug retention rates in clinical practice among patients with axSpA, treated with their first TNFi.

Methods

Data from biologic-naïve axSpA patients initiating a TNFi in the EuroSpA registries were pooled. In the primary analysis, propensity-score weighting was applied to assess the causal effect of sex on clinically important improvement (CII) according to ASDAS-CRP at 6 months. A generalized linear regression model was used to estimate the causal risk difference (RD) and relative risk (RR) of sex on CII. Possible covariates influencing the outcome were determined a priori and selected based on availability in the database (<20% missing). The final covariates included in the model were country, age and TNFi start year. In the secondary analysis, drug retention was assessed over 24 months of follow-up by Kaplan-Meier curves and log-rank test.

Results

In total, 6,451 axSpA patients with available data on ASDAS-CRP at baseline and 6 months were assessed for treatment response. Baseline characteristics are shown in the Table 1. In the adjusted analysis, the probability for females to have CII was 15% (RR, 0.85; 95% confidence interval [CI], 0.82 to 0.89) lower compared to males and the difference in probability for having CII was 9.4 percentage points (RD, 0.094; 95% CI, 0.069 to 0.12). The survival analysis included 28,608 axSpA patients with available data on retention rates. The TNFi 6/12/24-month retention rates were significantly lower in females (81%/69%/58%) compared to males (89%/81%/72%), see Figure 1.

Table 1.FemaleMaleMean (SD), Median [IQR] or percentagesMean (SD), Median [IQR] or percentagesAge (years)42.0 (12.1)41.4 (12.3)Fulfilment of mNYC66%80%Disease duration (years)2.0 [1.0, 7.0]3.0 [1.0, 9.0]TNFi start year Start 1999-20097.2%9.8% Start 2010-201326%27% Start 2014-201637%36% Start 2017-202030%27%BASDAI, mm59 (20)54 (21)BASFI, mm48 (25)46 (24)ASDAS, units3.5 (0.9)3.5 (1.0)CRP (mg/L)6.7 [2.5, 16.0]11.9 [4.0, 25.0]SJC (0-28)0 [0, 0]0 [0, 0]TJC (0-28)0 [0, 2]0 [0, 1]VAS pain, mm63 (22)59 (24)VAS fatigue, mm65 (25)59 (26)

mNYC, modified New York criteria; TNFi, tumor necrosis factor inhibitor; BASDAI, Bath Ankylosing Spondylitis Disease Activity Indexf; BASFI, Bath Ankylosing Spondylitis Functional Index; ASDAS, Ankylosing Spondylitis Disease Activity Score; CRP, C-reactive protein; SJC, swollen joint count; TJC, tender joint count; VAS, visual analogue scale.

Conclusion

Treatment efficacy and retention rates are lower among female patients with axSpA initiating their first TNFi. Females presented with lower C-reactive protein levels and higher scores on patient reported outcomes at baseline, reflecting differences in disease expression. Recognizing these sex differences is of relevance for customized patient care and may improve patient education.

References

[1]van der Horst-Bruinsma et al. Ann Rheum Dis. 2013 Jul;72(7):1221-4.

Acknowledgements

Novartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.

Disclosure of Interests

Pasoon Hellamand Grant/research support from: Novartis, Marleen G.H. van de Sande Speakers bureau: UCB, Consultant of: Abbvie, Eli Lily, Novartis and UCB, Grant/research support from: Novartis, Janssen, UCB and Eli Lilly, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Thomas Klausch: None declared, Michael Nurmohamed Speakers bureau: Abbvie, Janssen and Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS, Ronald van Vollenhoven Consultant of: AbbVie, AstraZeneca, Biogen, BMS, Galapagos, Janssen, Miltenyi, Pfizer, UCB and speaker fees from Abbvie, Galapagos, GSK, Janssen, Pfizer, R-Pharma and UCB, Grant/research support from: BMS, GSK and UCB, Dan Nordström Consultant of: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Anna-Mari Hokkanen Grant/research support from: MSD, Maria Jose Santos Speakers bureau: Abbvie, AstraZeneca, Lilly, Novartis and Pfizer, Elsa Vieira-Sousa Speakers bureau: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Consultant of: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Grant/research support from: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Anne Gitte Loft Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Grant/research support from: Novartis, Bente Glintborg Grant/research support from: Pfizer, Abbvie and BMS, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Grant/research support from: Abbvie, BMS, Merck, Celgene and Novartis, Ulf Lindström: None declared, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly and Novartis, Brigitte Michelsen Grant/research support from: Novartis, Adrian Ciurea Speakers bureau: AbbVie and Novartis, Michael J. Nissen Speakers bureau: AbbVie, Eli Lilly, Janssens, Novartis and Pfizer, Consultant of: AbbVie, Eli Lilly, Janssens, Novartis and Pfizer, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis and Pfizer, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis and Pfizer, Corina Mogosan Speakers bureau: AbbVie, Ewopharma, Lilly, Novartis and Pfizer, Consultant of: AbbVie, Ewopharma, Lilly, Novartis and Pfizer, Gary Macfarlane Grant/research support from: GSK, Gareth T. Jones Grant/research support from: AbbVie, Pfizer, UCB, Amgen and GSK, Karin Laas Speakers bureau: Amgen, Janssen, Novartis and Abbvie, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek and Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek and Janssen, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi and Sandoz-Lek, Consultant of: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi and Sandoz-Lek, Isabel Castrejon Speakers bureau: Eli Lilly, BMS, Janssen, MSD and Abbvie, Consultant of: Eli Lilly, BMS, Janssen, MSD and Abbvie, Manuel Pombo-Suarez Consultant of: Abbvie, MSD and Roche, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Consultant of: Amgen and Novartis, Arni Jon Geirsson: None declared, Eirik kristianslund: None declared, Jiří Vencovský Speakers bureau: Abbvie, Argenx, Boehringer-Ingelheim, Eli-Lilly, Gilead, MSD, Novartis, Octapharma, Pfizer, Roche, Sanofi and UCB, Consultant of: Abbvie, Argenx, Boehringer-Ingelheim, Eli-Lilly, Gilead, MSD, Novartis, Octapharma, Pfizer, Roche, Sanofi and UCB, Lucie Nekvindova: None declared, Semih Gulle: None declared, Berrin Zengin: None declared, Merete Lund Hetland Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz and Novartis, Irene van der Horst-Bruinsma Speakers bureau: BMS, AbbVie, Pfizer and MSD, Consultant of: Abbvie, UCB, MSD, Novartis and Lilly, Grant/research support from: MSD, Pfizer, AbbVie and UCB.

POS1020 BIOLOGICAL DMARD TREATMENT IN PSORIATIC ARTHRITIS IS LIKEWISE EFFECTIVE IN PATIENTS WITH HIGH AND WITH LOW JOINT COUNTS – RESULTS FROM THE SWISS CLINICAL QUALITY MANAGEMENT (SCQM) FOR RHEUMATIC DISEASES COHORT STUDY

Background

Biological and targeted synthetic (b/tsDMARDs) may be used in absent remission in psoriatic arthritis (PsA) independent of a defined number of affected joints. However, minimum three swollen and three tender joints are a common inclusion criterion in trials of b/tsDMARDs, and less is currently known about their effectiveness in PsA patients with low joint counts.

Objectives

To characterize PsA patients with low or high joint counts (LJC/HJC), analyze their drug treatment in routine care, and estimate the effectiveness of a first bDMARD in LJC and HJC patients.

Methods

We defined patients with less than three tender or swollen joints as LJC, and those with at least three tender and swollen joints as HJC patients. Patients were twice categorized according to their joint counts at registration in the registry, and at start of a first bDMARD (Table 1). We compared HJC and LJC at registration for current and future DMARD therapies, and at start of a first bDMARD for treatment effectiveness, using drug retention in univariate and in multivariable Cox regression models.

Table 1.

Selected characteristics of bDMARD naïve PsA patients with a low and with a high number of affected joints at start of their first bDMARD.

VariableLevelsHJC% highLJC% lowN allpbDMARD typeTNFi17692.617588.8351=0.22OMA147.42211.236csDMARD cotherapyyes11761.69045.7207<0.01csDMARD historynaive2312.15527.978<0.01tsDMARD_historynaive17592.117789.8352=0.47Dactylitis historyyes11560.56030.5175<0.01HLA B27yes1211.52823.340=0.02MDAYes00.0178.617<0.01DAPSA remission00.0126.112<0.01DactylitisYes9349.03316.8126<0.01EnthesitisYes6361.85547.0118=0.03BMImean (SD)27.65(5.05)26.58(4.72)333=0.046MASESmean (SD)2.86(3.93)1.61(2.47)219=0.005HAQ-DImean (SD)0.77(0.58)0.60(0.50)292=0.010EQ-5dmean (SD)62.22(20.63)67.22(16.27)294=0.022Patient globalmean (SD)5.93(2.41)4.83(2.58)288<0.001Tender joint countmean (SD)10.15(8.93)4.92(8.17)387<0.001Swollen joint countmean (SD)7.16(4.91)1.37(2.15)387<0.001Patient painmean (SD)5.96(2.47)4.85(2.51)290<0.001

Abbreviations: DAPSA: Disease activity of PsA. BMI: Body mass index, EQ-5d: European Quality of Life Measurement in five dimensions. HAQ-DI. Health assessment questionnaire disability index. HJC: High joint count, LJC: Low joint count, MASES: Maastricht ankylosing spondylitis enthesitis score, MDA: minimal disease activity, OMA: other mode of action than TNFi.

Results

We followed DMARD therapies for median (IQR) 3.2 (1.6, 5.0) in 675 LJC patients and for 3.4 (1.8, 5.2) years in 334 HJC patients. LJC patients at registration as well as at start of a first bDMARD were less often female, with less severe skin, enthesitis, dactylitis and nail involvement. Furthermore, LJC patients had lower disability indices and a more favorable health related quality of life. When defined at registration, LJC were as frequent as HJC patients on csDMARDs, but less often on bDMARDs. During their follow-up, a csDMARD, a first and a second bDMARD were less often and on average later commenced in LJC than in HJC patients. However, when defined at start of a first bDMARD, drug retention did not significantly differ between LJC and HJC patients (Figure 1).

Figure 1.

Multivariable adjusted Cox regression model for discontinuation of a first bDMARD. Abbreviation: JC_group_base: Low and high joint count groups at baseline.

Conclusion

The majority of Swiss PsA patients is in LJC status, which also means a better status in most PsA domains than in HJC patients. LJC status was associated with established bDMARD therapy and with slower treatment escalation. However, bDMARDs were likewise effective in bDMARD-naïve LJC and HJC patients, and should not withhold only for reasons of a low joint count.

References

[1]Gossec et al. 2020, Annals of the Rheumatic Diseases 79 (6): S700–712.

[2]Gladman et al. 2021, The Journal of Rheumatology 48 (12): 1824–29.

Acknowledgements

I acknowledge all patients, physicians and researchers of the Swiss Clinical Quality Management (SCQM) for rheumatic diseases Program, and Celgene for funding of this research.

Disclosure of Interests

Burkhard Moeller Speakers bureau: Novartis, MSD, Synergy, Eli Lilly, Bristol-Myers-Squibb, Janssen-Cilag, AbbVie and Pfizer, Grant/research support from: Celgene, Amgen, Vifor, Adrian Ciurea Speakers bureau: Abbvie and Novartis, Raphael Micheroli: None declared, Michael J. Nissen Speakers bureau: Abbvie, Celgene, Eli-Lilly, Janssen, Novartis and Pfizer, Eleftherios Papagiannoulis: None declared, Almut Scherer: None declared, Godehard Scholz: None declared, Nikhil Yawalkar Speakers bureau: Abbvie, Amgen, Celgene, Janssen, Lilly, Novartis, Pfizer

POS0001 CAN SINGLE IMPUTATION TECHNIQUES FOR BASDAI COMPONENTS RELIABLY CALCULATE THE COMPOSITE SCORE IN AXIAL SPONDYLOARTHRITIS PATIENTS?

Background

In axial spondyloarthritis (axSpA), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is a key patient-reported outcome. However, one or more of its components may be missing when recorded in clinical practice.

Objectives

To determine whether an individual patient’s BASDAI at a given timepoint can be reliably calculated with different single imputation techniques and to explore the impact of the number of missing components and/or differences between missingness of individual components.

Methods

Real-life data from axSpA patients receiving tumour necrosis factor inhibitors (TNFi) from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were utilized [1]. We studied missingness in BASDAI components based on simulations in a complete dataset, where we applied and expanded the approach of Ramiro et al. [2]. After introducing one or more missing components completely at random, BASDAI was calculated from the available components and with three different single imputation techniques: possible middle value (i.e. 50) of the component and mean and median of the available components. Differences between the observed (original) and calculated scores were assessed and correct classification of patients as having BASDAI<40 mm was additionally evaluated. For the setting with one missing component, differences arising between missing one of components 1-4 versus 5-6 were explored. Finally, the performance of imputations in relation to the values of the original score was investigated.

Results

A total of 19,894 axSpA patients with at least one complete BASDAI registration at any timepoint were included. 59,126 complete BASDAI registrations were utilized for the analyses with a mean BASDAI of 38.5 (standard deviation 25.9). Calculating BASDAI from the available components and imputing with mean or median showed similar levels of agreement (Table 1). When allowing one missing component, >90% had a difference of ≤6.9 mm between the original and calculated scores and >95% were correctly classified as BASDAI<40 (Table 1). However, separate analyses of components 1-4 and 5-6 as a function of the BASDAI score suggested that imputing any one of the first four BASDAI components resulted in a level of agreement <90% for specific BASDAI values while imputing one of the stiffness components 5-6 always reached a level of agreement >90% (Figure 1, upper panels). As expected, it was observed that regardless of the BASDAI component set to missing and the imputation technique used, correct classification of patients as BASDAI<40 was less than 95% for values around the cutoff (Figure 1, lower panels).

Table 1.

Level of agreement between the original and calculated BASDAI and correct classification for BASDAI<40 mm

Level of agreement with Dif≤6.9 mm* (%)Correct classification for BASDAI<40 mm** (%)1 missing componentAvailable93.996.9Value 5073.996.3Mean94.296.8Median93.196.82 missing componentsAvailable83.794.8Value 5040.792.8Mean83.594.8Median82.894.73 missing componentsAvailable71.992.6Value 5028.187.3Mean72.292.6Median69.792.2

* The levels of agreement with a difference (Dif) of ≤6.9 mm between the original and calculated scores were based on the half of the smallest detectable change. Agreement of >90% was considered as acceptable. ** Correct classification of >95% was considered as acceptable.

Figure 1.

Level of agreement between the original and calculated BASDAI and correct classification for BASDAI<40 mm as a function of the original score

Conclusion

BASDAI calculation with available components gave similar results to single imputation of missing components with mean or median. Only when missing one of BASDAI components 5 or 6, single imputation techniques can reliably calculate individual BASDAI scores. However, missing any single component value results in misclassification of patients with original BASDAI scores close to 40.

References

[1]Ørnbjerg et al. (2019). Ann Rheum Dis, 78(11), 1536-1544.

[2]Ramiro et al. (2014). Rheumatology, 53(2), 374-376.

Acknowledgements

Novartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.

Disclosure of Interests

Stylianos Georgiadis Grant/research support from: Novartis, Myriam Riek Grant/research support from: Novartis, Christos Polysopoulos Grant/research support from: Novartis, Almut Scherer Grant/research support from: Novartis, Daniela Di Giuseppe: None declared, Gareth T. Jones Speakers bureau: Janssen, Grant/research support from: AbbVie, Pfizer, UCB, Amgen, GSK, Merete Lund Hetland Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Grant/research support from: Abbvie, BMS, Merck, Celgene, Novartis, Simon Horskjær Rasmussen Grant/research support from: Novartis, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Novartis, Bente Glintborg Grant/research support from: Pfizer, Abbvie, BMS, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Karel Pavelka Speakers bureau: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Consultant of: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Jakub Zavada Speakers bureau: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Consultant of: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Merih Birlik: None declared, Ayten Yazici Grant/research support from: Roche, Brigitte Michelsen Grant/research support from: Novartis, Eirik kristianslund: None declared, Adrian Ciurea Speakers bureau: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Michael J. Nissen Speakers bureau: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Ana Maria Rodrigues Speakers bureau: Abbvie, Amgen, Consultant of: Abbvie, Amgen, Grant/research support from: Novartis, Pfizer, Amgen, Maria Jose Santos Speakers bureau: Abbvie, AstraZeneca, Lilly, Novartis, Pfizer, Gary Macfarlane Grant/research support from: GSK, Anna-Mari Hokkanen Grant/research support from: MSD, Heikki Relas Speakers bureau: Abbvie, Celgene, Pfizer, UCB, Viatris, Consultant of: Abbvie, Celgene, Pfizer, UCB, Viatris, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Corina Mogosan: None declared, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Consultant of: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Björn Gudbjornsson Speakers bureau: Amgen, Novartis, Consultant of: Amgen, Novartis, Arni Jon Geirsson: None declared, Pasoon Hellamand Grant/research support from: Novartis, Marleen G.H. van de Sande Speakers bureau: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Consultant of: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Grant/research support from: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Isabel Castrejon: None declared, Manuel Pombo-Suarez Consultant of: Abbvie, MSD, Roche, Bruno Frediani: None declared, Florenzo Iannone Speakers bureau: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis

POS0995 VALIDATION OF THE SPARCC MRI-RETIC E-TOOL FOR INCREASING SCORING PROFICIENCY OF MRI LESIONS IN AXIAL SPONDYLOARTHRITIS

Background

The web-based Spondyloarthritis Research Consortium of Canada (SPARCC) real-time iterative calibration (RETIC) modules for scoring MRI lesions in axial spondyloarthritis (axSpA) have been created by SPARCC developers to enable remote training of readers to appropriately use the SPARCC MRI inflammation and structural damage instruments and to attain adequate scoring proficiency.

Objectives

We aimed to test the performance of these modules in enhancing scoring proficiency in comparison to SPARCC developers.

Methods

The SPARCCRETIC SIJ inflammation and structural damage modules are each comprised of 50 DICOM axSpA cases with baseline and follow up scans and an online scoring interface based on SIJ quadrants. Continuous visual real-time feedback regarding concordance/discordance of scoring per SIJ quadrant with expert readers is provided by a color-coding scheme. Reliability is assessed in real-time by intra-class correlation coefficient (ICC), ICC data being provided every 10 cases, which are scored until proficiency targets for ICC are attained. In the present exercise, participants (n=15) from the EuroSpA Imaging project were randomized, stratified by reader expertise in scoring with SPARCC, to one of two reader training strategies (groups A and B) that each comprised 3 stages (25 patients per stage, 2 timepoints, blinded to chronology; independent assessment of Inflammatory and structural lesions): Group A. 1. Review of original SPARCC manuscript describing scoring method. 2. Review of PowerPoint summary of SPARCC method plus completion of SPARCCRETIC module. 3. Re-review of PowerPoint summary. Group B. Same 3-step strategy as A except SPARCCRETIC module completed at stage 3. The reliability of scoring was compared to an expert radiologist (SPARCC developer).

Results

Very good scoring proficiency for status and change scores was evident for SPARCC BME even by non-experienced readers with similar levels of reliability irrespective of prior expertise. The beneficial impact of the SPARCCRETIC module on scoring proficiency was most consistently evident for the scoring of structural lesions and for Strategy B, where the impact was evident for all structural lesions, level of reader expertise, and status as well as change scores (Table 1). Scoring proficiency improved the most for the least experienced readers (Figure 1).

Table 1.

Inter-rater reliability (Status/Change ICC) compared to radiologist SPARCC developer

MRI LesionReader expertiseStrategy AStrategy BStage 1 cases (n=25)Stage 2 cases (n=25)Stage 3 cases (n=25)Stage 1 cases (n=25)Stage 2 cases (n=25)Stage 3 cases (n=25)BMENone (n=4)0.91 / 0.940.83/0.820.77/0.780.82/0.880.65/0.820.88/0.90Intermediate (n=6)0.88/0.880.90/0.900.85/0.900.93/0.940.78/0.800.83/0.80Experienced (n=5)0.92/0.940.90/0.880.92/0.930.83/0.880.84/0.900.89/0.89ANKYLOSISNone (n=4)0.86/0.660.83/0.280.86/0.780.66/0.410.69/0.340.88/0.80Intermediate (n=6)0.89/0.570.83/0.370.92/0.810.82/0.680.74/0.470.93/0.84Experienced (n=5)0.96/0.760.93/0.640.94/0.860.97/0.240.83/0.410.91/0.79BACKFILLNone (n=4)-0.08/-0.050.38/0.220.59/0.380.64/0.130.05/-0.090.47/0.27Intermediate (n=6)0.41/0.130.44/0.420.69/0.390.50/0.220.30/0.300.70/0.42Experienced (n=5)0.82/0.380.55/0.400.91/0.640.65/0.240.21/0.260.71/0.30EROSIONNone (n=4)0.13/-0.080.67/0.420.51/0.330.34/0.330.23/0.080.38/0.37Intermediate (n=6)0.42/0.180.56/0.120.51/0.440.33/0.270.45/0.180.53/0.39Experienced (n=5)0.61/0.330.64/0.340.64/0.420.51/0.270.58/0.110.62/0.31FAT METAPLASIANone (n=4)0.62/0.540.30/0.170.57/0.290.43/0.530.38/0.070.83/0.63Intermediate (n=6)0.49/0.380.59/0.300.79/0.510.57/0.780.50/0.420.81/0.47Experienced (n=5)0.75/0.620.81/0.340.91/0.700.84/0.900.56/0.130.78/0.37

Conclusion

Attaining scoring proficiency for MRI structural lesions in axSpA is difficult but can be consistently improved by using the SPARCCRETIC module, even for experienced readers.

Figure 1.

Disclosure of Interests

Walter P Maksymowych Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, UCB, Consultant of: Abbvie, Boehringer Ingelheim, Celgene, Eli-Lilly, Galapagos, Novartis, Pfizer, UCB, Grant/research support from: Abbvie, Novartis, Pfizer, UCB, Anna Enevold Fløistrup Hadsbjerg Grant/research support from: Novartis, Mikkel Østergaard Consultant of: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli Lilly and Company, Galapagos, Gilead, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Grant/research support from: AbbVie, BMS, Merck, Celgene, Novartis, Raphael Micheroli: None declared, Susanne Juhl Pedersen Grant/research support from: Novartis, Adrian Ciurea: None declared, Nora Vladimirova Grant/research support from: Novartis, Michael J Nissen Speakers bureau: Eli-Lilly, Janssen, Novartis, Consultant of: Abbvie, Celgene, Eli-Lilly, Janssen, Novartis, Pfizer, Kristyna Bubova: None declared, Stephanie Wichuk: None declared, Manouk de Hooge: None declared, Ashish Jacob Mathew Grant/research support from: Novartis, Karlo Pintaric: None declared, Monika Gregová: None declared, Ziga Snoj: None declared, Marie Wetterslev: None declared, Karel Gorican: None declared, Joel Paschke: None declared, Iris Eshed: None declared, Robert G Lambert Paid instructor for: Novartis

POS1168 SELF-REPORTED SARS-CoV2 TESTING AND COVID-19 DISEASE IN PATIENTS WITH RHEUMATOID ARTHRITIS, AXIAL SPONDYLOARTHRITIS AND PSORIATIC ARTHRITIS IN A SWISS OBSERVATIONAL COHORT

Background:

Since the beginning of the pandemic in Switzerland, immunosuppressed people were strongly advised to be tested for SARS-CoV2 when symptomatic as it was conjectured that they might be more at risk for infection and/or severe disease. While patients with autoimmune diseases might be indeed more at risk of death from COVID-191, it remains unknown, whether there are differences in infection or complication rates between patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and axial spondyloarthritis (AxSpA), and whether this relates to their disease or their treatment. Additionally, the prevalence of SARS-CoV2 testing in this population is not known.

Objectives:

This study aimed to assess and compare the rate of COVID-19 and SARS-CoV2 testing in patients with RA, AxSpA and PsA, the potential association with their treatment and, for testing, the number of symptoms.

Methods:

We included patients with RA, AxSpA and PsA from the Swiss Clinical Quality Management register (SCQM) using a smartphone app (mySCQM) to record information between March and December 2020. The outcomes of interest were self-reported SARS-CoV2 testing, symptoms compatible with COVID-19 during the previous month and confirmed COVID-19 through PCR nasopharyngeal swab. Outcomes were evaluated over the complete length of the aforementioned period (i.e. the outcome has been reported at least once during the period). Outcomes were compared between diseases groups, using logistic regression. We also evaluated the association of baseline treatment (TNF-inhibitors, b/tsDMARDs with other modes of action (OMA), no b/tsDMARDs) on the odds of symptoms and testing and the association of the number of symptoms (0-9) on the odds of testing. The analyses of SARS-CoV2 testing and COVID-19 symptoms were additionally adjusted for age, gender, glucocorticoids and csDMARDs. Confirmed cases were not adjusted for treatment and other covariates considering the low number of events.

Results:

We included 927 patients with RA, 805 with AxSpa and 453 with PsA (Table 1). 1010 patients reported COVID-19-like symptoms (mostly fever, runny nose and cough), but only 455 of them (45%) reported being tested. 151 patients were tested without symptoms. In between March and December 2020, 7.6% of RA, 8.5% of AxSpA and 10.5% of PsA patients were tested positive for COVID-19 (p=0.678). The odds of testing, symptoms and confirmed COVID-19 were similar between diseases and not associated with treatment for testing and symptoms (Figure 1). The number of symptoms was associated with the odds of testing (OR 1.43, 95%CI 1.37-1.50 by symptom).

Table 1.RAaxSpAPsApn 927 805 453Age (mean, SD)56.4 (13)47.1 (12)52.7 (11)<0.001Genderfemale 705 (76) 403 (50) 230 (51)<0.001TreatmentTNFi 272 (29) 498 (62) 174 (38)<0.001OMA 355 (38) 71 (9) 137 (30)No b/tsDMARDs 300 (32) 236 (29) 142 (31)csDMARDs use 476 (51) 111 (14) 147 (33)<0.001Steroids use 93 (10) 11 (1) 19 (4)<0.001Disease duration14.2 (10)17.4 (11)14.8 (12)<0.001Testing for COVID-19All patients258 (28)231 (29)117 (26) 0.550Patients with symptoms189/427 (44)179/392 (46)87/191 (46) 0.911Presence of COVID-19 symptoms427 (46)392 (49)191 (42) 0.082Positive COVID-19 test* 18/237 (8) 19/223 (9) 11/105 (11) 0.678

N, % when not specified otherwise. *Missing data on test results in 41 patients χ2 test for categorical and t-test for continuous variables.

Figure 1.

Conclusion:

Prevalence of COVID-19 symptoms and confirmed cases was similar between diseases, and for symptoms, was not associated with treatment. Despite strong advice from health authorities, less than 50% of patients with inflammatory rheumatic diseases and COVID-19 symptoms were tested. This proportion was not significantly different between diseases and not influenced by type of treatment. Efforts should be made to improve rates of SARS-CoV2 testing in patients with rheumatic diseases.

References:

[1]Williamson, E. J. et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature 584, 430–436 (2020).

Acknowledgements:

This study was supported by Pfizer, Sanofi, Novartis, Gilead, Biogen and Bristol-Myers Squibb.

We thank all the patients and health professionals contributing to SCQM.

Disclosure of Interests:

Eleftherios Papagiannoulis: None declared, Adrian Ciurea Speakers bureau: Abbvie, Eli Lilly, MSD, Novartis, Pfizer, Diana Dan: None declared, Axel Finckh: None declared, Benoit GILBERT: None declared, Isabell von Loga Consultant of: Deloitte Consulting AG., Cathy Melong Pianta Taleng: None declared, Almut Scherer Consultant of: Pfizer, Employee of: BMS (2007-2008), Kim Lauper Consultant of: Gilead Galapagos, Grant/research support from: AbbVie. The SCQM foundation is supported by different companies https://www.scqm.ch/en/sponsoren/.

POS0027 SECULAR TRENDS IN BASELINE CHARACTERISTICS, TREATMENT RETENTION AND RESPONSE RATES IN 27189 BIO-NAÏVE AXIAL SPONDYLOARTHRITIS PATIENTS INITIATING TNFI – RESULTS FROM THE EUROSPA COLLABORATION

Background:

Knowledge of changes over time in baseline characteristics and tumor necrosis factor inhibitor (TNFi) response in bio-naïve axial spondyloarthritis (axSpA) patients treated in routine care is limited.

Objectives:

To investigate secular trends in baseline characteristics and retention, remission and response rates in axSpA patients initiating a first TNFi.

Methods:

Prospectively collected data on bio-naïve axSpA patients starting TNFi in routine care from 15 European countries were pooled. According to year of TNFi initiation, three groups were defined a priori based on bDMARD availability: Group A (1999–2008), Group B (2009–2014) and Group C (2015–2018). Retention rates (Kaplan-Meier), crude and LUNDEX adjusted1 remission (Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) <20) and response (ASDAS Major and Clinically Important Improvement (MI/CII), BASDAI 50) rates were assessed at 6, 12 and 24 months. No statistical comparisons were made.

Results:

In total, 27189 axSpA patients were included (5945, 11255 and 9989 in groups A, B and C).

At baseline, patients in group A were older, had longer disease duration and a larger proportion of male and HLA-B27 positive patients compared to B and C, whereas disease activity was similar across groups.

Retention rates at 6, 12 and 24 months were highest in group A (88%/81%/71%) but differed little between B (84%/74%/64%) and C (85%/76%/67%).

In all groups, median ASDAS and BASDAI had decreased markedly at 6 months (Table 1). The ASDAS values at 12 and 24 months and BASDAI at 24 months were higher in group A compared with groups B and C. Similarly, crude remission and response rates were lowest in group A. After adjustments for drug retention (LUNDEX), remission and response rates showed less pronounced between-group differences regarding ASDAS measures and no relevant differences regarding BASDAI measures.

Conclusion:

Nowadays, axSpA patients initiating TNFi are younger with shorter disease duration and more frequently female and HLA-B27 negative than previously, while baseline disease activity is unchanged. Drug retention rates have decreased, whereas crude remission and response rates have increased. This may indicate expanded indication but also a stable disease activity threshold for TNFi initiation over time, an increased focus on targeting disease remission and more available treatment options.

References:

[1]Arthritis Rheum 2006; 54: 600-6.

Table 1.

Secular trends in baseline characteristics, treatment retention, remission and response rates in European axSpA patients initiating a 1st TNFi

Baseline characteristicsGroup A(1999–2008)Group B(2009–2014)Group C(2015–2018)Age, years, median (IQR)57 (49–66)51 (42–60)46 (37–56)Male, %666057HLA-B27, %877772Years since diagnosis, median (IQR)5 (1–12)2 (0–8)2 (0–7)Smokers, %232425ASDAS, median (IQR)3.5 (2.8–4.1)3.4 (2.8–4.1)3.5 (2.8–4.1)BASDAI, median, (IQR)57 (42–71)59 (43–72)57 (41–71)TNFi drug, % (Adalimumab /Etanercept / Infliximab /Certolizumab / Golimumab)22 / 35 / 43 / 0 / 037 / 21 / 20 / 4 / 1827 / 28 / 24 / 8 / 13Follow up6 months12 months24 monthsGr AGr BGr CGr AGr BGr CGr AGr BGr CRetention rates, %, (95% CI)88 (88–89)84 (83–85)85 (84–86)81 (80–82)74 (74–75)76 (75–76)71 (70–72)64 (63–65)67 (66–68)ASDAS, median, (IQR)1.8 (1.2–2.8)1.9 (1.2–2.8)1.8 (1.2–2.6)1.9 (1.3–2.6)1.7 (1.2–2.5)1.6 (1.1–2.4)1.9 (1.4–2.6)1.7 (1.1–2.4)1.5 (1.1–2.2)ASDAS inactive disease, %, c/L28 / 2528 / 2430 / 2624 / 1932 / 2434 / 2623 / 1634 / 2039 / 23ASDAS CII, %, c/L57 / 5159 / 5063 / 5461 / 5063 / 4767 / 5159 / 4168 / 4074 / 45ASDAS MI, %, c/L31 / 2732 / 2737 / 3232 / 2637 / 2741 / 3130 / 2042 / 2546 / 28BASDAI, median, (IQR)23 (10–40)26 (11–48)24 (10–44)21 (10–38)23 (10–42)20 (8–39)22 (9–40)20 (8–39)16 (6–35)BASDAI remission, %, c/L44 / 4040 / 3443 / 3645 / 3645 / 3450 / 3844 / 3048 / 2956 / 34BASDAI 50 response, %, c/L53 / 4750 / 4253 / 4557 / 4656 / 4258 / 4457 / 3960 / 3563 / 38

Gr, Group; c/L, crude/LUNDEX adjusted.

Acknowledgements:

Novartis Pharma AG and IQVIA for supporting the EuroSpA Research Collaboration Network.

Disclosure of Interests:

Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Sara Nysom Christiansen Speakers bureau: BMS and GE, Grant/research support from: Novartis, Simon Horskjær Rasmussen: None declared, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Grant/research support from: Novartis, Ulf Lindström: None declared, Jakub Zavada: None declared, Florenzo Iannone: None declared, Fatos Onen: None declared, Michael J. Nissen Speakers bureau: Novartis, Eli Lilly, Celgene, and Pfizer, Consultant of: Novartis, Eli Lilly, Celgene, and Pfizer, Brigitte Michelsen Consultant of: Novartis, Grant/research support from: Novartis, Maria Jose Santos Speakers bureau: AbbVie, Novartis, Pfizer, Gary Macfarlane Grant/research support from: GlaxoSmithKline, Dan Nordström Consultant of: Abbvie, BMS, MSD, Novartis, Pfizer, Roche, UCB, Manuel Pombo-Suarez: None declared, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Irene van der Horst-Bruinsma Speakers bureau: Abbvie, BMS, MSD, Novartis, Pfizer, Lilly, UCB, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Johan Askling: None declared, Bente Glintborg Grant/research support from: Pfizer, Biogen, AbbVie, Karel Pavelka Speakers bureau: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Consultant of: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Elisa Gremese: None declared, Nurullah Akkoc: None declared, Adrian Ciurea Speakers bureau: Abbvie, Eli-Lilly, MSD, Novartis, Pfizer, Eirik kristianslund: None declared, Anabela Barcelos: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene, Amgen, GSK, Anna-Mari Hokkanen Grant/research support from: MSD, Carlos Sánchez-Piedra: None declared, Ruxandra Ionescu Speakers bureau: Abbvie, Amgen, Boehringer-Ingelheim Eli-Lilly,Novartis, Pfizer, Sandoz, UCB, Ziga Rotar Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Marleen G.H. van de Sande: None declared, Arni Jon Geirsson: None declared, Mikkel Østergaard Speakers bureau: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth, Consultant of: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth, Merete L. Hetland Speakers bureau: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis.

Comparative effectiveness of antitumour necrosis factor agents, biologics with an alternative mode of action and tofacitinib in an observational cohort of patients with rheumatoid arthritis in Switzerland

Background

Multiple biologic and targeted synthetic disease-modifying rheumatic drugs (b/tsDMARDs) are approved for the management of rheumatoid arthritis (RA), including TNF inhibitors (TNFi), bDMARDs with other modes of action (bDMARD-OMA) and Janus kinase inhibitors (JAKi). Combination of b/tsDMARDs with conventional synthetic DMARDs (csDMARDs) is recommended, yet monotherapy is common in practice.

Objective

To compare drug maintenance and clinical effectiveness of three alternative treatment options for RA management.

Methods

This observational cohort study was nested within the Swiss RA Registry. TNFi, bDMARD-OMA (abatacept or anti-IL6 agents) or the JAKi tofacitinib (Tofa) initiated in adult RA patients were included. The primary outcome was overall drug retention. We further analysed secondary effectiveness outcomes and whether concomitant csDMARDs modified effectiveness, adjusting for potential confounding factors.

Results

4023 treatment courses of 2600 patients were included, 1862 on TNFi, 1355 on bDMARD-OMA and 806 on Tofa. TNFi was more frequently used as a first b/tsDMARDs, at a younger age and with shorter disease duration. Overall drug maintenance was significantly lower with TNFi compared with Tofa [HR 1.29 (95% CI 1.14 to 1.47)], but similar between bDMARD-OMA and Tofa [HR 1.09 (95% CI 0.96 to 1.24)]. TNFi maintenance was decreased when prescribed without concomitant csDMARDs [HR: 1.27 (95% CI 1.08 to 1.49)], while no difference was observed for bDMARD-OMA or Tofa maintenance with respect to concomitant csDMARDs.

Conclusion

Tofa drug maintenance was comparable with bDMARDs-OMA and somewhat higher than TNFi. Concomitant csDMARDs appear to be required for optimal effectiveness of TNFi, but not for bDMARD-OMA or Tofa.

OP0242 META-ANALYSIS OF SINGLE-CELL RNA SEQUENCING DATA OF THE SYNOVIUM TO DEFINE SYNOVIAL FIBROBLAST PHENOTYPES ACROSS JOINT LOCATION AND DISEASE

Background:

Up to now, three groups used single cell RNA sequencing (scRNA-seq) to analyse the synovium in arthritis using different methods and material to measure RNA expression on a single cell level: Ref. 1 used unsorted dissociated synovial cells and a droplet based method; Refs 2 and 3 performed scRNA-seq on sorted cell populations.

Objectives:

The aim of this study was to perform a meta-analysis of scRNA-seq data of the synovium in arthritis: 1) to define synovial fibroblast (SF) phenotypes, 2) to confirm differences across SF clusters between rheumatoid arthritis (RA) and osteoarthritis (OA) and 3) to analyse joint specific differences between SF phenotypes.

Methods:

In addition to the available count matrices [1-3], we used unsorted dissociated synovial cells from three patients with undifferentiated arthritis (UA) with a droplet-based method (10x Genomics). We followed a standard protocol [4] to integrate the datasets into a shared space, even in the presence of extensive technical and/or biological differences (“batch-corrected”). SF were selected as previously described (PDPN+,ISLR+,COL1A2+,PTPRC-) [1-3]. We used a minimum log2 FC of 0.25 for average expression of genes in a cluster relative to the average expression in all other clusters combined to define marker genes. R with Seurat, Monocle and clusterProfiler packages were used for scRNA-seq analysis, pseudotime trajectory analysis and pathway enrichement analysis, respectively. Quantitative PCR (qPCR) (n=6-14 per location and disease), immunohistochemistry (IHC) and Krenn synovitis score (n=5-15 per location and disease) were performed according to standard protocols.

Results:

Data from 29 RA, 3 UA and 6 OA patients were analysed. From a total of 29’448 cells, we identified 14’787 (50%) with a fibroblast phenotype. Of those, we determined 5 subpopulations (Fig. 1): 1)THY1-CD55hifibroblasts with high expression ofMMP1andMMP3(SF1), 2)THY1loCD34+fibroblasts expressing high levels ofPI16(SF2) 3)THY1hifibroblasts expressing high levels of periostin (POSTN) and collagens (e.g.COL1A1, COL3A1) (SF3), 4)THY1hifibroblasts expressingCXCL12(SF4) and 5)THY1lofibroblasts expressingCXCL12,NR4A1andCCL2(SF5). Fig. 2 shows pathway enrichment map of all marker genes; it organizes enriched terms into a network with edges connecting overlapping gene sets. Pseudotime trajectory axis derived from Monocle indicated that SF4 represent a state between SF3 and SF5. Pseudotemporal expression dynamics ofTHY1marked the progression of these three subtypes (Graph 1). SF1 and SF2 were proportionally underrepresented and SF3-5 overrepresented in RA (chi-squared = 37.18, p = 1.65e-07). The expression of POSTN, a signature gene of SF3, was not different between RA and OA tissues, but significantly correlated with the synovitis score (Spearman ρ = 0.55, p=0.02), in particular with pathological changes in the sublining. POSTN expression was higher in hand than in knee synovial tissues (mean ± SD IHC score: hand 8 ±2, knee 5 ±2) and in cultured SF (qPCR: 10-fold difference). Accordingly, SF3 was enriched in hand versus knee synovial tissues in the scRNA-seq dataset (chi-squared = 944.87, p < 2.2e-16).

Fig. 1Fig. 2

Graph 1

Conclusion:

In our meta-analysis, we found comparable subtypes of fibroblasts as in the individual analyses [1-3], showing the robustness of cell phenotype identification using scRNA-seq. The different SF phenotypes appear to be plastic cell states rather than fixed cell subtypes, whose development is controlled by an interrelation between pathological changes in the synovium and joint location.

References:

[1]Stephenson et al. Nat. Commun. 2018

[2]Mizoguchi et al. Nat. Commun. 2018

[3]Zhang et al. Nat Immunol. 2019

[4]Stuart, Butler, et al. Cell 2019

Disclosure of Interests:

Raphael Micheroli: None declared, Mojca Frank-Bertoncelj: None declared, Sam G. Edalat: None declared, Kerstin Klein: None declared, Tadeja Kuret: None declared, Kristina Buerki: None declared, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Oliver Distler Grant/research support from: Grants/Research support from Actelion, Bayer, Boehringer Ingelheim, Competitive Drug Development International Ltd. and Mitsubishi Tanabe; he also holds the issued Patent on mir-29 for the treatment of systemic sclerosis (US8247389, EP2331143)., Consultant of: Consultancy fees from Actelion, Acceleron Pharma, AnaMar, Bayer, Baecon Discovery, Blade Therapeutics, Boehringer, CSL Behring, Catenion, ChemomAb, Curzion Pharmaceuticals, Ergonex, Galapagos NV, GSK, Glenmark Pharmaceuticals, Inventiva, Italfarmaco, iQvia, medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Roche, Sanofi and UCB, Speakers bureau: Speaker fees from Actelion, Bayer, Boehringer Ingelheim, Medscape, Pfizer and Roche, Caroline Ospelt Consultant of: Consultancy fees from Gilead Sciences.

FRI0040 MULTI-VARIATE APPROACH INCLUDING SEROLOGY AND GENETICS FOR AN IMPROVED IDENTIFICATION OF PATIENTS AT RISK OF DEVELOPING RA

Background:

First-degree relatives of rheumatoid arthritis (RA) patients (FDR-RA) have a 3 - 5-fold increased prevalence of the disease [1]. RA development is triggered by an interaction between genetic and environmental factors.

As the field is moving towards prevention in pre-clinical stages of RA, it is key to identify individuals with imminent RA, prior to onset of symptoms, which will presumably rely on both the measurement of autoantibodies and genetic risk markers.

Objectives:

Assemble a pattern of serologic biomarkers in combination with genetics to improve the identification of individuals at high risk to develop RA.

Methods:

The cohort included 827 serum samples from 601 individuals, followed within the Swiss multicenter cohort study SCREEN-RA of FDR [2]. FDR-RA were categorized into four groups according to the presence of symptoms and systemic autoimmunity associated with RA; 1: asymptomatic FDR-RA without anti-CCP or symptoms, 416 (69%); 2: FDR-RA with clinically suspect arthralgia (CSA) [3] or with signs of arthritis, without anti-CCP, 72 (12%); 3: FDR-RAs with no signs of arthritis, positive anti-CCP test, 55 (9%); 4: FDR with signs of arthritis or CSA, positive anti-CCP-test, 58 (10%).

Serum samples were analyzed for the presence of anti-CCP (IgG, IgA), RF (IgM, IgA) and anti-RA33 (IgM, IgA, IgG) using the EliATMinstrument platform (Phadia AB, Uppsala, Sweden).

Genetic measurements were performed using the AmpliSeqTMtechnology on the Ion GeneStudioTMinstruments (Thermo Fisher Scientific, Carlsbad, USA), covered variants were analyzed using an algorithm focusing on the identification of RA patients.

Results:

The overall prevalence of biomarkers, considering results above cutoff values, was 1% for anti-CCP IgG and IgA, 10% and 2% for RF IgM and RF IgA, respectively, and 6-15% for all three anti-RA33 isotypes. Several individuals had multiple positive serology tests (Fig 1): 3.6% (22) were positive for 2 tests and 1% (6) were positive for 3 or more tests. Among the 28 individuals positive for ≥2 tests, 17 (61%) were symptomatic.

Figure 1.

Distribution of positive serology within the different groups. No positivity (none), positive for one (1), equal or more than 2 (2-5) of the serologic tests.

Nine of 604 FDR-RA subsequently developed classifiable RA and were positive for serologic biomarkers before date of RA diagnosis (Table 1). The RA converters had a mean age of 39 years (24-75 yrs) and an average follow-up time within the study of 3.6 years (1-7 yrs).

Table 1.

Biomarker status of subsequent RA converters before date of diagnosis.

RA convertersCCP IgGCCP IgARF IgMRF IgARA33 total1+++++2+−++−3−−+−+4−−+−−5−−+−−6−−−−+7−−−−+8−−−−−9−−−−−

Using an algorithm to analyze the RA-associated genetic SNPs, we could highlight 48 FDR-RA (8%) with an increased genetic risk to develop RA. 15 out of 48 individuals (31%) at high genetic risk reported CSA, and 12 out of 48 individuals (25%) displayed signs of systemic autoimmunity associated with RA.

Conclusion:

When looking at FDR it could help to not only include anti-CCP autoantibody testing but also additional biomarkers like RF and anti-RA33. Furthermore, looking at the genetic risk factors could give additional information. The combination with the multi-variate profile could even improve the early diagnosis of these patients.

References:

[1]Kuo et al. Rheumatology 2017; 56:928933

[2]Finckh et al. Ann Rheum Dis 2011; 70: S3–282

[3]van Steenbergen HW, et al. Ann Rheum Dis 2017; 76:491–496

Disclosure of Interests:

Maresa Grundhuber Grant/research support from: Thermo Fisher Scientific, Employee of: Thermo Fisher Scientific, Isabel Gehring Grant/research support from: Thermo Fisher Scientific, Employee of: Thermo Fisher Scientific, Céline Lamacchia Grant/research support from: Thermo Fisher Scientific partially supported this study, Pascale Roux-Lombard: None declared, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Ulrich Walker Grant/research support from: Ulrich Walker has received an unrestricted research grant from Abbvie, Consultant of: Ulrich Walker has act as a consultant for Abbvie, Actelion, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, MSD, Novartis, Pfizer, Phadia, Roche, Sandoz, Sanofi, and ThermoFisher, Paid instructor for: Abbvie, Novartis, and Roche, Speakers bureau: Abbvie, Actelion, Bristol-Myers Squibb, Celgene, MSD, Novartis, Pfizer, Phadia, Roche, Sandoz, and ThermoFisher, Burkhard Moeller: None declared, Diego Kyburz Grant/research support from: Abbvie, Roche, Consultant of: Abbvie, BMS, Novartis, Pfizer, Roche, UCB, Gilead, Sanofi, Speakers bureau: Pfizer, BMS, Novartis, Abbvie, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Maryam Poorafshar Grant/research support from: Thermo Fisher Scientific, Employee of: Thermo Fisher Scientific, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific

OP0075 SPINAL RADIOGRAPHIC PROGRESSION IN AXIAL SPONDYLOARTHRITIS AND THE IMPACT OF CLASSIFICATION AS NONRADIOGRAPHIC VERSUS RADIOGRAPHIC DISEASE

Background:

Data on spinal radiographic progression is more limited in nonradiographic axial spondyloarthritis (nr-axSpA) than in the radiographic disease state (r-axSpA). It remains unclear, whether radiographic sacroiliitis is by itself associated with progression of spinal structural damage.

Objectives:

To investigate whether spinal radiographic progression relates to structural damage at the sacroiliac level in axSpA by means of statistical mediation analyses in a large prospective real-life cohort of patients with axSpA.

Methods:

Patients from the Swiss Clinical Quality Management cohort were included if they fulfilled the ASAS classification criteria and could be classified as nr-axSpA or r-axSpA after central scoring of pelvis radiographs. Spinal radiographs performed every 2 years were scored according to the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). The relationship between classification status and spinal progression over 2 years was investigated using binomial generalized estimating equations models with adjustment for sex, ankylosing spondylitis disease activity score (ASDAS) and tumor necrosis factor inhibitor treatment. Baseline spinal damage was considered an intermediate variable and included in sensitivity analyses, as were additional variables potentially influencing radiographic progression.

Results:

In total, 88 nr-axSpA and 418 r-axSpA patients contributed to data for 725 radiographic intervals (Table 1). Mean (SD) mSASSS change over 2 years was 0.16 (0.62) units in nr-axSpA and 0.92 (2.78) units in r-axSpA, p=0.01. Nr-axSpA was associated with a significantly lower progression over 2 years (defined as an increase in ≥2 mSASSS units) in adjusted analyses (OR 0.33, 95%CI 0.13; 0.83), confirmed with progression defined as the formation of ≥1 syndesmophyte. Mediation analyses revealed that sacroiliitis exerted its effect on spinal progression indirectly by being associated with the appearance of a first syndesmophyte (OR 0.09, 95%CI 0.02; 0.36 for nr-axSpA vs r-axSpA) (Fig. 1 and 2). Baseline syndesmophytes were predictors of further progression.

Table 1.

Baseline characteristics at first radiograph.

ParameterN506nr-axSpAN = 88r-axSpAN = 418PFemale sex, %50654.533.7<0.001Age, y50639.5±11.140.4±11.00.52Symptom duration, y49810.0±9.914.0±9.8<0.001HLA-B27 positive, %45271.680.70.09BASDAI4274.6±2.04.2±2.30.26ASDAS4082.8±0.92.8±1.10.74Elevated CRP, %42230.640.60.14BASFI4332.8±2.23.1±2.50.71BASMI4351.1±1.42.2±2.0<0.001mSASSS5060.9±1.56.8±12.7<0.001Syndesmophytes, %5069.135.2<0.001On TNFi, %50619.336.40.002Fig. 1.

Modified Stoke Ankylosing Spondylitis Spine Score (mSASSS) for individual patients plotted as a function of duration since symptom onset.

Fig. 2.

Two-year mSASSS progression depicted in a cumulative probability plot. Progression was defined as an increase in mSASSS of at least 2 units (dotted line) in 2 years.

Conclusion:

Spinal structural damage is mainly restricted to patients with r-axSpA, leading to relevant prognostic and therapeutic implications.

Disclosure of Interests:

Monika Hebeisen: None declared, Raphael Micheroli: None declared, Almut Scherer: None declared, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Manouk de Hooge: None declared, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Kristina Buerki: None declared, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Burkhard Moeller: None declared, Pascal Zufferey: None declared, Pascale Exer: None declared, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer.

THU0013 INTEGRATED ANALYSIS OF SYNOVIAL SINGLE CELL RNA SEQUENCING DATA DEEPENS THE CURRENT KNOWLEDGE OF SYNOVIAL PATHOLOGY IN ARTHRITIS

Background:

The heterogeneity of synovial tissues from patients with arthritis could contribute to the interpatient variability in disease course, prognosis and treatment response. Single-cell RNA sequencing (scRNA-seq) permits in-depth analysis of tissue heterogeneity, which could facilitate drug discovery and patient stratification for precision medicine.

Objectives:

To construct a comprehensive landscape of synovial cell types and molecular pathways in arthritis by integrating our and published scRNA-seq data, generated across different scRNA-seq technologies [Smart-seq2, Drop-seq], cell preparation protocols [dissociated unsorted, sorted cells] and types of arthritis [undifferentiated (UA), rheumatoid arthritis, osteoarthritis].

Methods:

Synovial tissues were obtained by ultrasound-guided biopsy from patients with UA [not fulfilling the classification criteria for a specific arthritis, n=3]. Biopsies were disintegrated [enzymatic and mechanical disruption] and cell viability assessed with trypan blue. ScRNA-seq libraries [2 per patient] were prepared with 10X Genomics Drop-Seq and sequenced on NovaSeq6000. Bioinformatics analysis of our and published [n=35] datasets1-3was performed using Seurat protocol4with correction for batch effects and filtering low-quality cells. Functional enrichment analysis of marker genes in clusters was done with STRING Protein-Protein networks. Synovitis was assessed with ultrasound and histology.

Results:

Our tissue disintegration protocol resulted in good cell yield and viability (92%, 72%, 100%). The synovial cellular heterogeneity detected by scRNA-seq reflected the histological findings [Krenn score, pathotype]. These were supported with the ultrasound and clinically assessed disease activity. The integrated analysis of 41 datasets from 38 donors yielded 41845 scRNA-seq cell profiles, 50% contributed by our dataset. An independent analysis of our data and their integration with published data showed that different scRNA-seq methods and protocols can identify all the major synovial cell types and their activation states (Figure 1) with large heterogeneity between donors. We identified a previously undescribed synovial cell population, which was located near the fibroblast cluster, was negative for canonical cell markers, but highly enriched in cell division genes (80% of marker genes). These cells comprised a mixed population of CD34-, podoplanin (PDPN)highor PDPNlowcells that were mostly negative for the sub-lining fibroblast marker THY. Furthermore, they appeared to be highly secretory (extracellular matrix components) and their gene expression profile was inclined towards cell migration, vascular development and insulin growth factor-dependent processes.

Figure 1.

Heatmap with top 20 cluster gene markers, gene enrichment analysis and UMAP plot of synovial cell clusters.

Conclusion:

By integrating synovial scRNA-seq data from 41845 cells, we identified a previously undescribed, highly proliferative and secretory synovial cell population in arthritis. We increased the number of known scRNA-seq synovial cell profiles in arthritis by two-fold and demonstrated the robustness of synovial scRNA-seq data outputs across different technologies and protocols. This broadens the current knowledge of synovial tissue heterogeneity and pathology in arthritis.

References:

[1]Stephenson W. et al. Nat Commun 2017.

[2]Mizoguchi F. et al. Nat Commun 2017.

[3]Zhang F. et al. Nat Immunol 2018.

[4]Stuart T et al. Cell 2019

Acknowledgments:

This work is supported by Vontobel Foundation and medAlumni University of Zurich

Disclosure of Interests:

Sam G. Edalat: None declared, Raphael Micheroli: None declared, Tadeja Kuret: None declared, Kristina Buerki: None declared, Chantal Pauli: None declared, Snežna Sodin-Šemrl: None declared, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Oliver Distler Grant/research support from: Grants/Research support from Actelion, Bayer, Boehringer Ingelheim, Competitive Drug Development International Ltd. and Mitsubishi Tanabe; he also holds the issued Patent on mir-29 for the treatment of systemic sclerosis (US8247389, EP2331143)., Consultant of: Consultancy fees from Actelion, Acceleron Pharma, AnaMar, Bayer, Baecon Discovery, Blade Therapeutics, Boehringer, CSL Behring, Catenion, ChemomAb, Curzion Pharmaceuticals, Ergonex, Galapagos NV, GSK, Glenmark Pharmaceuticals, Inventiva, Italfarmaco, iQvia, medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Roche, Sanofi and UCB, Speakers bureau: Speaker fees from Actelion, Bayer, Boehringer Ingelheim, Medscape, Pfizer and Roche, Caroline Ospelt Consultant of: Consultancy fees from Gilead Sciences., Gregor Rot: None declared, Mojca Frank-Bertoncelj: None declared

THU0383 GENDER DIFFERENCES IN NONRADIOGRAPHIC AXIAL SPONDYLOARTHRITIS: FROM CLINICAL CHARACTERISTICS TO EFFECTIVENESS OF TNF INHIBITORS

Background:

While a male predominance is found in radiographic axial spondyloarthritis (r-axSpA), an equal male to female distribution was repeatedly reported for the nonradiographic disease form (nr-axSpA). Some important differences in clinical manifestations and response to treatment with tumor necrosis factor inhibitors (TNFi) between the sexes have been delineated for r-axSpA. It remains unclear, whether comparable sex differences can be assumed for nr-axSpA. Indeed, existing data on gender differences in nr-axSpA is limited to subgroups and is particularly scarce regarding effectiveness of treatment.

Objectives:

To investigate sex differences with regard to demographics, clinical manifestations and response to TNFi in nr-axSpA after exclusion of patients with co-morbid fibromyalgia (FM).

Methods:

Response to a first TNFi was assessed in 85 women and 78 men with nr-axSpA and without concomitant FM in the Swiss Clinical Quality Management Cohort. The primary outcome was the proportion of patients achieving a 40% improvement in the Assessment of Spondyloarthritis international Society criteria (ASAS40) at 1 year. Additional response outcomes were evaluated as secondary outcomes. Patients having discontinued TNFi were considered nonresponders. Logistic regression analyses were adjusted for baseline differences (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Maastricht ankylosing spondylitis enthesitis score (MASES), diagnostic delay, body mass index (BMI)).

Results:

Baseline characteristics of women and men are shown in Table 1. Significant differences were restricted to diagnostic delay, BASDAI, MASES and BMI. An ASAS40 response was achieved by 17% of women and 38% of men (OR 0.34, 95% CI 0.12; 0.93, p=0.02). A lower response rate in women was confirmed in the adjusted analysis (OR 0.19, 95% CI 0.05; 0.62, p=0.009) as well as for the other outcomes assessed (Table 2).

Table 1.

Baseline characteristics of women and men with nr-axSpA starting a first TNFi (after exclusion of patients with co-morbid FM).

ParameterN163MenN = 78WomenN = 85pAge, years16335.6±10.839.1±11.40.10Age at onset, years16227.9±8.628.1±8.50.66Diagnostic delay, years1624.1±7.67.8±9.90.005HLA-B27 positive, %14975.768.00.36Prior MRI sacroiliitis, %15470.868.30.86BASDAI1485.3±2.06.3±1.60.003ASDAS1403.3±1.03.4±0.70.29Elevated CRP, %15442.538.30.62BASFI1483.6±2.43.8±2.50.54BASMI1411.2±1.11.4±1.20.42EQ-5D14154.8±22.855.8±18.30.79Peripheral arthritis,%15941.652.40.20Enthesitis, %15880.585.20.53MASES1572.3±2.53.9±3.30.002csDMARDs ever, %16334.642.40.34Taking NSAIDs, %15092.986.20.29Current smoking, %13928.322.80.55BMI16025.9±4.224.0±4.4<0.001Table 2.

Response rates of women versus men after 1 year of treatment with a first TNFi.

Unadjusted analysesAdjusted analysesOutcomeWomen%Men%OR95% CIPOR95% CIPASAS4017380.340.12; 0.930.020.190.05; 0.620.009BASDAI5023500.300.11; 0.770.0070.190.05; 0.580.005ASDAS improv. ≥1.128580.290.10; 0.780.0080.260.08; 0.750.02ASDAS <2.127490.390.15; 1.000.030.180.04; 0.650.01ASDAS improv. ≥24260.130.01; 0.680.0050.040.00; 0.270.003ASDAS <1.38290.230.05; 0.820.010.070.01; 0.390.005

Conclusion:

Despite only few sex differences in patient characteristics in nr-axSpA, response rates to TNFi are significantly lower in women than in men.

Disclosure of Interests:

Regula Neuenschwander: None declared, Monika Hebeisen: None declared, Raphael Micheroli: None declared, Kristina Buerki: None declared, Pascale Exer: None declared, Karin Niedermann Schneider: None declared, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Almut Scherer: None declared, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer.

THU0398 DRUG RETENTION RATES AND TREATMENT OUTCOMES IN 1860 AXIAL SPONDYLOARTHRITIS PATIENTS TREATED WITH SECUKINUMAB IN ROUTINE CLINICAL PRACTICE IN 13 EUROPEAN COUNTRIES IN THE EUROSPA RESEARCH COLLABORATION NETWORK

Background:

To determine the real-life 6- and 12-month secukinumab effectiveness in Europe overall, as well as stratified by prior biologic disease-modifying anti-rheumatic drug (bDMARD)/targeted synthetic (ts)DMARD use.

Objectives:

Real-life data from axSpA patients treated with secukinumab from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were pooled. We calculated proportions of patients achieving Bath Ankylosing Spondylitis Disease Activity Score (BASDAI) <2/<4 and Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3/<2.1 at 6 and 12 months, including with LUNDEX adjustments (crude value adjusted for drug retention). Retention rates were compared between b/tsDMARD naïve, 1 prior and ≥2 prior b/tsDMARD users with Kaplan-Meier analyses with log rank test and disease states by Chi-square test.

Methods:

A total of 1860 axSpA patients were included (Table 1). Overall 6/12-month secukinumab retention rates were 82%/72% and higher in bionaïve patients (Table 2, Figure). Significant differences in retention rates in-between the registries were found. Inactive disease/low-disease-activity (LDA) were achieved more often in bionaïve patients (Table 2).

Table 1All patients (n=1860)b/tsDMARD naïve (n=414)1 prior b/tsDMARD (n=448)≥2 prior b/tsDMARDs (n=998)Age (years), mean (SD)47 (12)45 (12)47 (12)48 (12)Men, %57%68%58%49%Years since diagnosis, mean (SD)10 (9)8 (9)10 (9)11 (9)Current smokers, %25 %27%25%23%Patient’s global (0-100), median (IQR)70 (50-81)80 (60-90)64 (50-80)70 (50-82)Physician’s global (0-100), median (IQR)45 (25-63)64 (43-78)45 (22-60)40 (20-58)C reactive protein (mg/L), median (IQR)8 (3-25)15 (5-31)7 (3-25)6 (2-22)Erythrocyte sedimentation rate (mm/h), median (IQR)22 (9-44)30 (14-44)24 (8-45)18 (8-42)Pain (0-100), median (IQR)70 (50-81)80 (65-90)65 (49-80)70 (50-80)BASDAI, median (IQR)6.2 (4.6-7.6)6.8 (5.2-8.0)5.9 (4.2-7.2)6.1 (4.4-7.6)BASFI, median (IQR)5.5 (3.2-7.3)6.1 (3.2-7.6)4.8 (2.8-6.8)5.5 (3.3-7.2)ASDAS, median (IQR)3.6 (2.9-4.3)4.2 (3.5-4.8)3.5 (2.7-4.2)3.5 (2.8-4.2)Table 2MonthsAll patients (n=1860)b/tsDMARD naïve (n=414)1 prior b/tsDMARD (n=448)≥2 prior b/tsDMARDs (n=998)p-value*Secukinumab retention rate, % (95%CI)682% (80-84%)90% (87-93%)83% (79-86%)78% (76-81%)0.0011272% (69-74%)84% (81-88%)73% (69-78%)66% (63-69%)<0.001BASDAI <2, % Crude626373518<0.001 LUNDEX adjusted21342813<0.001 Crude1225412918<0.001 LUNDEX adjusted16311811<0.001BASDAI <4, % Crude651716040<0.001 LUNDEX adjusted40654730<0.001 Crude1251765639<0.001 LUNDEX adjusted32573623<0.001ASDAS <1.3, % Crude69131360.001 LUNDEX adjusted712115<0.001 Crude1211181570.002 LUNDEX adjusted713940.002ASDAS <2.1, % Crude6243226200.002 LUNDEX adjusted19292115<0.001 Crude1227442721<0.001 LUNDEX adjusted17331712<0.001

*Comparisons between b/tsDMARD naïve, 1 prior and ≥2 prior b/tsDMARD users were performed with Kaplan-Meier with log-rank test or Chi-Square test, as appropriate

Conclusion:

In this real-life study of 1860 patients with axSpA in 13 European countries secukinumab retention was high and significantly higher for bionaïve patients. Overall, a higher proportion of bionaïve than previous b/tsDMARD users achieved inactive disease/LDA.

Figure

Acknowledgments:

Novartis and IQVIA for supporting the EuroSpA RCN

Disclosure of Interests:

Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, Ulf Lindström: None declared, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Fatos Onen: None declared, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Anna-Mari Hokkanen: None declared, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Carlos Sánchez-Piedra: None declared, Servet Akar: None declared, Joe Sexton: None declared, Matija Tomsic: None declared, Helena Santos Speakers bureau: AbbVie, Eli-Lilly, Janssen, Pfizer, Novartis, Marco Sebastiani: None declared, Jenny Osterlund: None declared, Arni Jon Geirsson: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene and GSK., Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Stylianos Georgiadis Grant/research support from: Novartis, Cecilie Heegaard Brahe Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, 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, 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

OP0109 CO-MEDICATION WITH A CONVENTIONAL SYNTHETIC DMARD IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS IS ASSOCIATED WITH IMPROVED RETENTION OF TNF INHIBITORS: RESULTS FROM THE EUROSPA COLLABORATION

Background:

Axial spondylarthritis (axSpA) patients treated with a tumour necrosis factor inhibitor (TNFi) may receive a concomitant conventional synthetic disease-modifying anti-rheumatic drug (csDMARD), although the value of combination therapy remains unclear.

Objectives:

Describe the proportion and phenotype of patients with axSpA initiating their first TNFi as monotherapy compared to TNFi+csDMARD combination therapy, and to compare the 1-year TNFi retention between the two groups.

Methods:

Data from 13 European registries was collected. Two exposure treatment groups were defined: TNFi monotherapy at baseline (=TNFi start date) and TNFi+csDMARD combination therapy. TNFi retention rates were assessed with Kaplan-Meier curves for each country and combined. Hazard ratios (HR, 95% CI) for discontinuing the TNFi were obtained with Cox models: (i) crude; adjusted for (ii) country, and (iii) country, sex, age, calendar year, disease duration and BASDAI. Participating countries were dichotomized into two strata, depending on their 1-year retention rate being above (stratum A) or below (stratum B) the average retention rate across all countries.

Results:

22,196 axSpA patients were included with 34% on TNFi+csDMARD combination therapy. Baseline characteristics are presented in table 1. Overall, the crude TNFi retention rate was marginally longer in the combination therapy group (80% (79-81%)) compared to the monotherapy group (78% (77-79%)) and was primarily driven by differences in stratum B (fig. 1). TNFi retention rates varied significantly across countries (range:-11.0% to +11.3%), with a clear distinction between the 2 strata. The HRs for discontinuation over 1-year (reference=TNFi monotherapy) in the 3 models were: (i) 0.88 (0.82-0.93), (ii) 0.87 (0.82-0.92), (iii) 0.88 (0.82-0.93).

Table 1Baseline characteristicsAll patients(n=22196)Country stratum ACountry stratum BTNFi mono(n=4940)csDMARD + TNFi(n=2547)TNFi mono(n=9693)csDMARD + TNFi(n=5016)Age (years), mean (SD)42.6 (12.5)43.4 (12.0)42.8 (12.2)41.6 (12.7)43.7 (12.7)Females, %41.137.738.242.044.2Disease duration (yrs), mean (SD)5.7 (8.0)6.2 (7.7)6.7 (7.4)4.9 (8.2)6.1 (8.2)Enthesitis, %50.316.733.957.859.7SJC-28, median (IQR)0 (0-1)0 (0-0)0 (0-2)0 (0-0)0 (0-2)VAS pain (0-100), mean (SD)60.9 (24.5)63.3 (26.5)67.8 (23.3)60.2 (23.4)57.2 (24.3)CRP (mg/L), median (IQR)8 (3-20)7.8 (2-20)18 (6.7-32.6)6.0 (2.7-15)8.0 (3-22)BASDAI (0-10), mean (SD)5.7 (2.1)5.7 (2.2)6.2 (2.1)5.6 (2.0)5.4 (2.2)BASFI (0-10), mean (SD)4.4 (2.5)4.4 (2.6)4.9 (2.5)4.3 (2.4)4.2 (2.9)ASDAS, mean (SD)3.5 (1.1)3.7 (1.0)4.0 (1.0)3.3 (1.0)3.3 (1.1)On Infliximab, %25.721222436Baseline csDMARD use, %-Methotrexate045063-Sulfasalazine068033-Leflunomide0801

Conclusion:

Considerable differences were observed across countries in the use of combination therapy and TNFi retention in axSpA patients. The overall 1-year TNFi retention was higher with csDMARD co-therapy compared to TNFi monotherapy. TNFi monotherapy had a 12-13% higher risk of treatment discontinuation.

Acknowledgments:

Novartis Pharma AG and IQVIA

MN and BD participated equally

Disclosure of Interests:

Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Bénédicte Delcoigne: None declared, Daniela Di Giuseppe: None declared, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Karen Fagerli: None declared, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Heřman Mann: None declared, Nurullah Akkoc: None declared, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Brigitte Michelsen: None declared, Gary Macfarlane: None declared, 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, Matija Tomsic: None declared, Burkhard Moeller: None declared, Pedro Ávila-Ribeiro Grant/research support from: Novartis, Carlos Sánchez-Piedra: None declared, Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Arni Jon Geirsson: None declared, Lucie Nekvindova: None declared, Gozde Yildirim Cetin Speakers bureau: AbbVie, Novartis, Pfizer, Roche, UCB, MSD, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Ulf Lindström: None declared

FRI0283 CO-MEDICATION WITH CSDMARD HAS LITTLE EFFECT ON THE RETENTION OF TNF INHIBITORS IN PSORIATIC ARTHRITIS, RESULTS FROM THE EUROSPA COLLABORATION

Background:

Previous studies have suggested similar effectiveness, but longer treatment retention, for tumor necrosis factor inhibitors (TNFi), when used in combination with a conventional synthetic disease modifying anti-rheumatic drug (csDMARD) in psoriatic arthritis (PsA).

Objectives:

To describe patients with PsA initiating a first TNFi as monotherapy compared to combination therapy, and to explore 1-year treatment retention of TNFi in the two groups.

Methods:

Patients with PsA starting a first TNFi (2006-2017) were identified in biologics registers of 13 European countries, and data were pooled for analysis. Co-medication with csDMARD was determined at TNFi start.

Because of large inter-country variation in TNFi retention, countries were split into two strata, depending on each country’s 1-year retention rate for TNFi being above (stratum A) or below (stratum B) the average 1-year retention rate.

TNFi treatment retention was compared through Kaplan-Meier curves; the proportion remaining on the TNFi at one year; and hazard ratios (HR) during the first year: (i) crude; adjusted for (ii) country-strata, and (iii) country-strata, sex, age, calendar year, DAS28 and disease duration. In model (iii) only registers contributing >1000 patients or <33% missing data for DAS28 were included.

Results:

A total of 14778 patients with PsA starting a first TNFi were included. Baseline disease activity was similar within stratum B, but higher for the combination treatment group in stratum A (table 1).

Table 1.

Baseline characteristics

Country strataStratum AStratum BTNFimonotherapyN=2120TNFi/csDMARDcombinationN=2128TNFimonotherapyN=3369TNFi/csDMARDcombinationN=7161Females52%51%53%51%Age, years49.7 (12.2)48.7 (11.8)48.8 (13.0)48.9 (12.2)Disease duration, yrs6.4 (7.0)6.8 (6.8)5.9 (7.5)5.9 (7.1)Tender joints 285.5 (6.3)8.0 (6.3)5.6 (6.0)5.6 (5.7)Swollen joints 282.8 (4.3)5.6 (5.0)3.0 (3.8)3.3 (3.8)VAS pain54 (29)62 (24)59 (23)56 (24)DAPSA-2824.6 (18.6)36.2 (17.6)27.3 (15.6)27.2 (15.2)DAS28 (CRP)3.5 (1.4)4.7 (1.3)4.0 (1.2)4.0 (1.1)Concomitant csDMARDMethotrexate-76%-79%Sulfasalazine-15%-15%Other csDMARD-49%-25%

Numbers are means (sd) unless otherwise stated.

The Kaplan-Meier curves for the treatment groups were similar within each stratum (fig 1), as were the proportions remaining on TNFi after one year, stratum A: monotherapy 86% (95%CI: 85-88) vs. combination 86% (84-87), stratum B: 71% (69-72) vs. 73% (72-74). The HRs for TNFi discontinuation (ref=TNFi monotherapy) were: (i) 1.06 (0.98-1.13), (ii) 0.94 (0.87-1.01), (iii) 0.89 (0.83-0.96), including 13078 patients (9 countries) for model (iii).

Conclusion:

In this exploratory study no benefit in TNFi retention was observed for csDMARD combination therapy in crude analyses, while in adjusted analyses an 11% lower risk of TNFi discontinuation was found. These preliminary results offer limited support for use of combination therapy in PsA. Further analyses will explore to what extent the results are affected by inter-country heterogeneity and differences between TNFi.

Acknowledgments:

UL and DDG contributed equally.

Novartis Pharma AG and IQVIA support the EuroSpA collaboration.

Disclosure of Interests:

Ulf Lindström: None declared, Daniela Di Giuseppe: None declared, Bénédicte Delcoigne: None declared, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Burkhard Moeller: None declared, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Carlos Sánchez-Piedra: None declared, Kari Eklund Consultant of: Celgene, Lilly, Speakers bureau: Pfizer, Roche, Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Thorvardur Love: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene and GSK., Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Lucie Nekvindova: None declared, Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Nuh Atas: None declared, Servet Yolbaş: None declared, Karen Fagerli: None declared, Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Matija Tomsic: None declared, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Pedro Ávila-Ribeiro Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, 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, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer

Relationship between preterm birth and post-partum periodontal maternal status: a hospital-based Romanian study

PURPOSE

This cross-sectional case-control study of post-partum women aimed to estimate whether maternal periodontitis was a predictive contributor to preterm birth and to identify other risk factors associated with preterm birth in our target population.

METHODS

The case group included women who delivered preterm (74 cases) and the control group included women who had a normal term delivery (120 controls). Medical records, a 16-item questionnaire, and a full-mouth periodontal examination were used to collect information about socio-demographic characteristics, general health problems, birth-related information, behavioral factors and periodontal status. Logistic regression analysis was used to estimate the strength of the relationship between predictors and the categorical outcome variable, preterm birth.

RESULTS

The bivariate analysis revealed the significant associations between preterm birth and socio-demographic factors (educational level, p = 0.003), antepartum smoking habit (p = 0.001) and birth weight lower than 2500 g (p < 0.001). The multivariate analysis highlighted that the presence of post-partum maternal periodontitis and its severity remained independent risk factors of preterm birth in the presence of antepartum smoking habit and route of delivery [adjusted OR 2.26, 95% CI (1.06; 4.82), respectively, OR 3.46, 95% CI (1.08; 11.15)].

CONCLUSION

Post-partum maternal periodontal disease and its severity might, in part, be considered as contributor to preterm deliveries before 37 weeks of gestation.

Long-term immunogenicity after yellow fever vaccination in immunosuppressed and healthy individuals

BACKGROUND

The live-attenuated yellow fever vaccine (YFV) is generally contraindicated in immunosuppressed patients. Our aim was to investigate if immunosuppressive therapy impairs the long-term protection against yellow fever virus in patients who had received YFV prior to the start of their immunosuppressive therapy.

METHODS

Our study examined 35 healthy individuals and 40 immunosuppressed patients with autoimmune diseases or organ transplants. All individuals had received YFV prior to the onset of their immunosuppression. We analysed the long-term influence of the immunosuppressive therapy on the YFV protective immunity by measuring neutralising antibodies (NA) with the Plaque Reduction Neutralisation Test (PRNT). We assessed risk factors for a negative PRNT result (titre below 1: 10) and their influence on the magnitude of the NA.

RESULTS

A median time interval of 21.1 years (interquartile range 14.4-31.3 years) after the YFV in all patients, a total of 35 immunosuppressed patients (88%) were seropositive (PRNT ≥ 1:10) compared to 31 patients (89%) in the control group. The geometric mean titres of NA did not differ between the groups. The duration of an underlying rheumatic disease was the only risk factor found for a lower magnitude of NA. An insufficient level of NA was found in nine subjects (12%) who had received a single dose of YFV (in one subject, the number of YFV doses was unknown).

CONCLUSION

The use of an immunosuppressive drug started after the administration of the YFV did not affect long-term persistence of NA. A second dose of YFV may be necessary to secure long-term immunity.

[The rheumatic hand - diagnostics in practice]

Many rheumatic diseases show changes and are visible in the hands. The pattern of distribution in the relevant joints, soft-tissue changes, skin manifestations, neurological and vascular symptoms and clinical findings provide fundamental information. Imaging and lab results provide diagnostic support. In this review, common diseases are presented in terms of their clinical expressions in the hands: osteoarthritis, rheumatoid arthritis, gout, calcium pyrophosphate dihydrate deposition disease, psoriatic arthritis, reactive arthritis, systemic sclerosis, dermatomyositis/polymyositis and systemic lupus erythematosus. Furthermore, we discuss pathological findings of the hands as a result of diabetic cheiroarthropathia, endocarditis, secondary hypertrophic osteo-arthropathy and chronic regional pain syndrom.

Which subgroup of patients with rheumatoid arthritis benefits from switching to rituximab versus alternative anti-tumour necrosis factor (TNF) agents after previous failure of an anti-TNF agent?

BACKGROUND

Patients with rheumatoid arthritis (RA) with an inadequate response to TNF antagonists (aTNFs) may switch to an alternative aTNF or start treatment from a different class of drugs, such as rituximab (RTX). It remains unclear in which clinical settings these therapeutic strategies offer most benefit.

OBJECTIVE

To analyse the effectiveness of RTX versus alternative aTNFs on RA disease activity in different subgroups of patients.

METHODS

A prospective cohort study of patients with RA who discontinued at least one aTNF and subsequently received either RTX or an alternative aTNF, nested within the Swiss RA registry (SCQM-RA) was carried out. The primary outcome, longitudinal improvement in 28-joint count Disease Activity Score (DAS28), was analysed using multivariate regression models for longitudinal data and adjusted for potential confounders.

RESULTS

Of the 318 patients with RA included; 155 received RTX and 163 received an alternative aTNF. The relative benefit of RTX varied with the type of prior aTNF failure: when the motive for switching was ineffectiveness to previous aTNFs, the longitudinal improvement in DAS28 was significantly better with RTX than with an alternative aTNF (p = 0.03; at 6 months, -1.34 (95% CI -1.54 to -1.15) vs -0.93 (95% CI -1.28 to -0.59), respectively). When the motive for switching was other causes, the longitudinal improvement in DAS28 was similar for RTX and alternative aTNFs (p = 0.40). These results were not significantly modified by the number of previous aTNF failures, the type of aTNF switches, or the presence of co-treatment with a disease-modifying antirheumatic drug.

CONCLUSION

This observational study suggests that in patients with RA who have stopped a previous aTNF treatment because of ineffectiveness changing to RTX is more effective than switching to an alternative aTNF.

Synthesis of 5-alkynylated d4T Analogues as Potential HIV-1 Reverse Transcriptase Inhibitors

A series of 2',3'-didehydro-2',3'-dideoxynucleosides substituted with an alkynylhydroxy- (6, 7, 12 and 13) and alkynylamino- (20) groups at the C-5 position were synthesized. All these five target modified nucleosides were tested for anti-human immunodeficiency virus type 1 activity in CEM-SS and MT-4 cells and unfortunately displayed no improvement in antiviral activity.

[Evidence-based therapy of Raynaud's syndrome]

Raynaud's syndrome has a prevalence of 3-5% in the general population. Despite its high frequency, the majority of available therapies have not been validated in randomized controlled trials. Effective therapies with a high level of evidence include the calcium channel blocker nifedipine. As analyzed by meta-analyses, nifedipine showed improvement of the peripheral circulation, as well as reduction of both the intensity and frequency of attacks in patients with primary and secondary Raynaud's syndrome as compared to placebo. Similar results in a metaanalysis were obtained for intravenous infusions of iloprost in patients with secondary Raynaud's phenomenon associated with systemic sclerosis. In addition, intravenous infusions of iloprost improved healing of fingertip ulcers in patients with systemic sclerosis. Therapies with significant effects in single randomized controlled trials include angiotensin II-receptor type 1 antagonists (losartan), the calcium channel blockers felodipine und amlodipine, serotonin-reuptake-inhibitors (fluoxetine) und phosphodiesterase-V-inhibitors (sildenafil, vardenafil). However, the results for these promising substances have to be confirmed in long-term trials with larger patient numbers.

Synthesis and anti-HIV activity of [d4U]-[trovirdine analogue] and [d4T]-[trovirdine analogue] heterodimers as inhibitors of HIV-1 reverse transcriptase

A series of eleven heterodimers containing both a nucleoside analogue (d4U, d4T) and a non-nucleoside type inhibitor (Trovirdine analogue) were synthesized and evaluated for their ability to inhibit HIV replication. Unfortunately, the (N-3)d4U-Trovirdine conjugates (9a-e) and (N-3)d4T-Trovirdine conjugates (10a-f) were found to be inactive suggesting that the two individual inhibitor compounds do not bind simultaneously in their respective sites.

Synthesis of 5-alkenylated D4T analogues via the Pd-catalyzed cross-coupling reaction

The target compounds 5-[N-(6-amino-hexyl)-acrylamide]-2',3'-didehydro-2',3'-dideoxy-uridine (12) and 5-[N-[5-(methoxycarbonyl)-pentyl]-acrylamide]-2',3'-didehydro-2',3'- dideoxy-uridine (15) were prepared by the palladium acetate-triphenylphosphine-catalyzed reaction of the 5'-O-acetyl-5-iodo-d4T analogue (3). These compounds 12 and 15 can be used to prepare nucleotide probes carrying fluorescent labels and were nevertheless screened for their anti-HIV activity. The biological data demonstrated that none of them were active against HIV-1.

[Lung infiltrations in Hodgkin lymphoma]

We report the case of a young patient presenting with cervical lymphadenopathy and interstitial pulmonary infiltrates due to Hodgkin's Disease. Although lung involvement regressed under chemotherapy, we observed new alveolar infiltrates during treatment. Steroid administration after exclusion of an infectious cause was followed by rapid clinical and radiological improvement, indicating the probable presence of pulmonary bleomycine toxicity.

CD4+ T-cell-epitope escape mutant virus selected in vivo

Mutations in viral genomes that affect T-cell-receptor recognition by CD8+ cytotoxic T lymphocytes have been shown to allow viral evasion from immune surveillance during persistent viral infections. Although CD4+ T-helper cells are crucially involved in the maintenance of effective cytotoxic T-lymphocyte and neutralizing-antibody responses, their role in viral clearance and therefore in imposing similar selective pressures on the virus is unclear. We show here that transgenic virus-specific CD4+ Tcells, transferred into mice persistently infected with lymphocytic choriomeningitis virus, select for T-helper epitope mutant viruses that are not recognized. Together with the observed antigenic variation of the same T-helper epitope during polyclonal CD4+ T-cell responses in infected pore-forming protein-deficient C57BL/6 mice, this finding indicates that viral escape from CD4+ T lymphocytes is a possible mechanism of virus persistence.

Viral escape from the neutralizing antibody response: the lymphocytic choriomeningitis virus model

In addition to CD8+ cytotoxic T lymphocyte (CTL) responses, neutralizing antibodies contribute substantially to the long-term immune control of noncytopathic viruses, as demonstrated during infection with the lymphocytic choriomeningitis virus (LCMV). The high virus load during the initial phase of an infection and the ability of this RNA virus to spontaneously acquire mutations are important prerequisites for escaping an ongoing immune response. In this context, LCMV escape from the humoral response by single point mutations in neutralizing envelope protein determinants may occur, particularly during conditions of CTL deficiency, leading to virus persistence.

Impairment of CD4(+) T cell responses during chronic virus infection prevents neutralizing antibody responses against virus escape mutants

We have shown previously that neutralizing antibodies (nAbs) are important contributors to the long-term immune control of lymphocytic choriomeningitis virus infection, particularly if cytotoxic T cell responses are low or absent. Nevertheless, virus escape from the nAb response due to mutations within the surface glycoprotein gene may subsequently allow the virus to persist. Here we show that most of the antibody-escape viral mutants retain their immunogenicity. We present evidence that the failure of the infected host to mount effective humoral responses against emerging neutralization-escape mutants correlates with the rapid loss of CD4(+) T cell responsiveness during the establishment of viral persistence. Similar mechanisms may contribute to the persistence of some human pathogens such as hepatitis B and C viruses, and human immunodeficiency virus.

Neutralizing antiviral antibody responses

Neutralizing antibodies are evolutionarily important effectors of immunity against viruses. Their evaluation has revealed a number of basic insights into specificity, rules of reactivity (tolerance), and memory—namely, (1) Specificity of neutralizing antibodies is defined by their capacity to distinguish between virus serotypes; (2) B cell reactivity is determined by antigen structure, concentration, and time of availability in secondary lymphoid organs; and (3) B cell memory is provided by elevated protective antibody titers in serum that are depending on antigen stimulation. These perhaps slightly overstated rules are simple, correlate with in vivo evidence as well as clinical observations, and appear to largely demystify many speculations about antibodies and B cell physiology. The chapter also considers successful vaccines and compares them with those infectious diseases where efficient protective vaccines are lacking, it is striking to note that all successful vaccines induce high levels of neutralizing antibodies (nAbs) that are both necessary and sufficient to protect the host from disease. Successful vaccination against infectious diseases such as tuberculosis, leprosy, or HIV would require induction of additional long-lasting T cell responses to control infection.

Synthesis and antiviral activity of C-5 substituted beta-D- and beta-L-D4T analogues

A series of beta-D-2',3'-didehydro-2',3'-dideoxy-nucleosides bearing a tether attached at the C-5 position and their beta-L-counterparts was synthesized. Their inhibitory activities against human immunodeficiency virus (HIV) were investigated and compared to establish relationship(s) between compound structure and their antiviral activity. No significant activity was observed for beta-D- and beta-L-modified nucleosides respectively 7a-c and 14a-c, but 7d and 14d exhibited a weak activity against HIV-1.