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Objective: To investigate the association of the lipidomic profile with osteoarthritis (OA) severity, considering the outcomes radiographic knee and hand OA, pain and function. Design: We used baseline data from the Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) cohort, comprising persons with knee OA fulfilling the clinical American College of Rheumatology classification criteria. Radiographic knee and hand OA severity was quantified with Kellgren-Lawrence sum scores. Knee and hand pain and function were assessed with validated questionnaires. We quantified fasted plasma higher order lipids and oxylipins with liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based platforms. Using penalised linear regression, we assessed the variance in OA severity explained by lipidomics, with adjustment for clinical covariates (age, sex, body mass index (BMI) and lipid lowering medication), measurement batch and clinical centre. Results: In 216 participants (mean age 66 years, mean BMI 27.3 kg/m2, 75% women) we quantified 603 higher order lipids (triacylglycerols, diacylglycerols, cholesteryl esters, ceramides, free fatty acids, sphingomyelins, phospholipids) and 28 oxylipins. Lipidomics explained 3% and 2% of the variance in radiographic knee and hand OA severity, respectively. Lipids were not associated with knee pain or function. Lipidomics accounted for 12% and 6% of variance in hand pain and function, respectively. The investigated OA severity outcomes were associated with the lipidomic fraction of bound and free arachidonic acid, bound palmitoleic acid, oleic acid, linoleic acid and docosapentaenoic acid. Conclusions: Within the APPROACH cohort lipidomics explained a minor portion of the variation in OA severity, which was most evident for the outcome hand pain. Our results suggest that eicosanoids may be involved in OA severity. (c) 2022 Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International.

Objective: To investigate the test-retest precision and to report the longitudinal change in cartilage thickness, the percentage of knees with progression and the predictive value of the machine-learning-estimated structural progression score (s-score) for cartilage thickness loss in the IMI-APPROACH cohort - an exploratory, 5-center, 2-year prospective follow-up cohort. Design: Quantitative cartilage morphology at baseline and at least one follow-up visit was available for 270 of the 297 IMI-APPROACH participants (78% females, age: 66.4 +/- 7.1 years, body mass index (BMI): 28.1 +/- 5.3 kg/m(2), 55% with radiographic knee osteoarthritis (OA)) from 1.5T or 3T MRI. Test-retest precision (root mean square coefficient of variation) was assessed from 34 participants. To define progressor knees, smallest detectable change (SDC) thresholds were computed from 11 participants with longitudinal test-retest scans. Binary logistic regression was used to evaluate the odds of progression in femorotibial cartilage thickness (threshold: similar to 211 mu m) for the quartile with the highest vs the quartile with the lowest s-scores. Results: The test-retest precision was 69 mu m for the entire femorotibial joint. Over 24 months, mean cartilage thickness loss in the entire femorotibial joint reached -174 mu m (95% CI: [-207, -141] mu m, 32.7% with progression). The s-score was not associated with 24-month progression rates by MRI (OR: 1.30, 95% CI: [0.52, 3.28]). Conclusion: IMI-APPROACH successfully enrolled participants with substantial cartilage thickness loss, although the machine-learning-estimated s-score was not observed to be predictive of cartilage thickness loss. IMI-APPROACH data will be used in subsequent analyses to evaluate the impact of clinical, imaging, biomechanical and biochemical biomarkers on cartilage thickness loss and to refine the machine-learning-based s-score. (c) 2022 The Author(s). Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

BackgroundThe characterization of differential molecular endotypes in osteoarthritis (OA) is essential for enabling patient stratification to enhance clinical trials, facilitate the development of targeted and individualized treatments.ObjectivesThis study aimed to characterize the profile and dynamics over 24 months (24M) of proteins present in the sera from patients in the IMI-Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) cohort who exhibited structural (radiographic) and pain progression compared to participants who did not progressed during this period.MethodsForty-five patients enrolled in the IMI-APPROACH cohort were selected for the proteomic analysis. Among these, 15 showed the highest structural progression (group S) and 15 the highest pain progression (group P) at 24M, according to the APPROACH criteria [1], while 15 did not progressed neither in S nor in P. Baseline (BL) and 24M serum samples were depleted of the top 14 most abundant proteins and then analysed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) on a nanoElute-LC coupled to a high-resolution TIMS-QTOF (timsTOF Pro, Bruker Daltonics). Proteins were identified and quantified using the LFQ algorithm of MaxQuant software. Further statistical and bioinformatic analyses were performed using Perseus and OmicsAnalyst software.ResultsThe proteomic analysis resulted in the identification of 558 proteins (10,466 peptides) in the serum samples. A label-free quantification algorithm was employed to quantify 468 proteins in the samples. Hierarchical clustering of the data showed the differences in protein abundance were more relevant longitudinally (BL to 24M) than in cross-sectional comparisons between the three groups under study (N, P or S). Sixty-three proteins were significantly altered (fold change >=1.5, pThe overlapping of these proteomic profiles was analyzed between groups and is shown in the Figure 1. Proteins modulated specifically in the N group may be associated with mechanisms related with joint repair. On the other hand, six proteins (including two apolipoproteins) were increased at 24M only in the P group. Finally, 30 proteins were modulated only in the S group: five of them increased and 25 decreased. Remarkably, this latter group includes lubricin, chaperones and proteins related with proteoglycan binding, such as COMP, fibronectin or histidine-rich glycoprotein.Figure 1.Circulating proteins identified as modulated after 24M follow-up in 45 patients from the APPROACH cohort that progressed in structure (S group; n=15), pain (P group; n=15) or did not progressed (N group; n=15). The numbers with arrows indicate those proteins that decrease (arrow pointing down) or increase (arrow pointing up) compared to baseline.ConclusionThe modulation of specific protein profiles in serum were identified as associated with the progression in structure, pain or non-progression in patients from the APPROACH cohort. Proteomic changes found specifically in the S group may be interesting circulating markers of the structural affectation occurring in the joint.References[1]van Helvoort EM, et al., BMJ Open. 2020 Jul 28;10(7):e035101. doi: 10.1136/bmjopen-2019-035101.Disclosure of InterestsCristina Ruiz-Romero: None declared, Patrik Önnerfjord: None declared, Valentina Calamia: None declared, Patricia Fernández Puente: None declared, Lucía Lourido: None declared, Rocío Paz González: None declared, Pawel Widera: None declared, Jaume Bacardit: None declared, Anne-Christine Bay-Jensen Shareholder of: Nordic Bioscience, Employee of: Nordic Bioscience, Francis Berenbaum Consultant of: AstraZeneca, Boehringer, Bone Therapeutics, CellProthera, Expanscience, Galapagos, Gilead, Grunenthal, GSK, Eli Lilly, Merck Sereno, MSD, Nordic, Nordic Bioscience, Novartis, Pfizer, Roche, Sandoz, Sanofi, Servier, UCB, Peptinov, 4P Pharma, 4Moving Biotech, Grant/research support from: TRB Chemedica, Ida K. Haugen Consultant of: Abbvie and Novartis, Grant/research support from: Pfizer, Margreet Kloppenburg Consultant of: Abbvie, Pfizer, Levicept, GlaxoSmithKline, Merck-Serono, Kiniksa, Flexion, Galapagos, Jansen, CHDR, Novartis, UCB, Simon Mastbergen: None declared, Jonathan Larkin Shareholder of: GlaxoSmithKline, Employee of: GlaxoSmithKline, Ali Mobasheri Consultant of: Merck KGaA, Kolon TissueGene, Pfizer Inc., Galapagos-Servier, Image Analysis Group (IAG), Artialis SA, Aché Laboratórios Farmacêuticos, AbbVie, Guidepoint Global, Alphasights, Science Branding Communications, GSK, Flexion Therapeutics, Pacira Biosciences, Sterifarma, Bioiberica, SANOFI, Genacol, Kolon Life Science, BRASIT/BRASOS, GEOS, MCI Group, Alcimed, Abbot, Laboratoires Expansciences, SPRIM Communications, Frontiers Media and University Health Network (UHN) Toronto, Grant/research support from: Merck KGaA, Kolon TissueGene, Pfizer Inc., Galapagos-Servier, Image Analysis Group (IAG), Artialis SA, Aché Laboratórios Farmacêuticos, AbbVie, Guidepoint Global, Alphasights, Science Branding Communications, GSK, Flexion Therapeutics, Pacira Biosciences, Sterifarma, Bioiberica, SANOFI, Genacol, Kolon Life Science, BRASIT/BRASOS, GEOS, MCI Group, Alcimed, Abbot, Laboratoires Expansciences, SPRIM Communications, Frontiers Media and University Health Network (UHN) Toronto, Francisco J. Blanco Consultant of: Gedeon Richter Plc., Bristol-Myers Squibb International Corporation (BMSIC), Sun Pharma Global FZE, Celgene Corporation, Janssen Cilag International N.V, Janssen Research & Development, Viela Bio, Inc., Astrazeneca AB, UCB BIOSCIENCES GMBH, UCB BIOPHARMA SPRL, AbbVie Deutschland GmbH & Co.KG, Merck KGaA, Amgen, Inc., Novartis Farmacéutica, S.A., Boehringer Ingelheim España, S.A, CSL Behring, LLC, Glaxosmithkline Research & Development Limited, Pfizer Inc, Lilly S.A., Corbus Pharmaceuticals Inc., Biohope Scientific Solutions for Human Health S.L., Centrexion Therapeutics Corp., Sanofi, TEDEC-MEIJI FARMA S.A., Kiniksa Pharmaceuticals, Ltd., Fundación para la Investigación Biomédica Del Hospital Clínico San Carlos, Grünenthal and Galapagos, Grant/research support from: Pfizer

BackgroundAlthough it prevents severe forms of the disease, vaccination does not completely protect against the occurrence of COVID19 disease. If, DMARDs used have been associated with variable humoral response to SARS-CoV-2 vaccination, the impact of their use after SARS-CoV-2 natural infection have been poorly studied.ObjectivesTo characterize humoral response after SARS-CoV-2 infection and viral persistence in the nasopharyngeal sphere (NP), stools and blood of patients with rheumatic disease under DMARDs, and compared to healthy controls.MethodsProspective monocentric longitudinal study including patients with rheumatoid arthritis or spondyloarthritis under DMARDs and with a confirmed SARS-CoV-2 infection (positive NP PCR and/or positive serology and/or pathognomonic thoracic tomography (CT)) during the first or second wave of the COVID pandemic. Patients were followed up until one year after infection and humoral response was assessed before vaccination. Serum IgG and IgA antibodies against spike (S) and nucleocapsid (N) proteins were measured at every visit. Viral persistence was assessed at the early visit in the NP and stools using conventional RT-PCR and in the blood using a high sensitive technique (droplet digital PCR).ResultsBetween June 2020 and July 2021, we include 96 patients (50 SpA and 46 RA) with a mean age of 53 +/- 14 years and 20 healthy controls (mean age 49 ± 16 years) corresponding to relatives of patients (spouses, children) living together and infected at the same time. The immune responses were analyzed according to 6 treatment groups: methotrexate (MTX)/salazopyrine (SLZ) monotherapy (n=17/2); anti-TNF monotherapy (n=24), anti-TNF + MTX (n=23); rituximab (RTX) (n=11); anti-IL17 or -23 (n=8); others (n=11). Visits were made at 1 month (29 ±13 days; n=18), 3 months (110 ±23 days; n=67), 6 months (231 ±35 days; n=48) and 12 months (368 ± 19 days; n=19) after infection. The anti-S and anti-N IgG Ab titers were not significantly different in the 6 treatment groups and the control population at 3 months. A significant decrease in anti-S IgA Ab titers was noted in the group treated with RTX (p=0.007) and with molecules targeting the IL17/23 pathway (p=0.007). A similar but non-significant trend was observed in these same treatment groups for anti-N IgA Ab (p=0.07). The titers of anti-SARS-CoV-2 antibodies at M3, was not associated with a severe COVID disease. Detection of SARS-Cov-2 RNA in stools and serum was negative for all samples taken at 1 month or 3 months. 4 patients (2 RA treated with abatacept/RTX and 2 SpA treated with anti-TNF/secukinumab) had a positive RT-PCR NP with low to very low viral load at the 1-month visit (mean Ct 36). None of these 4 patients had had a severe form of COVID19 infection.ConclusionDMARDs - treated patients with previous proven COVID-19 did not seem to alter IgG Ab response but RTX and anti-IL17/-IL-23 might alter IgA humoral response. This lower immune response was not associated with a more severe disease. In these patients, new infection may not be considered as a full boost for the immune system. DMARDs did not induce viral persistence in the serum, the NP or in the stool.Acknowledgementsfinancial support from Société Française de Rhumatologie and ANR RA COVIDDisclosure of InterestsNone declared

BackgroundCarpal tunnel syndrome (CTS) and hand osteoarthritis (HOA) are common diseases that can coexist in the same patient. Only one recent study showed that CTS was associated with a significant decrease in strength and performance of the OA-affected hand [1]. This observation suggested that CTS-induced neuropathic disorders may have effects on the surrounding joints symptomatically supporting the role of nerve-joint axis in OA pain.ObjectivesOur work aimed to study the impact of CTS on the symptoms and structural severity of HOA in the DIGICOD (DIGItal Cohort Design) cohort.MethodsDIGICOD is a single-center prospective hospital cohort which includes 426 patients over 35 years of age with symptomatic HOA [2]. Patients in our study were those in the DIGICOD cohort at inclusion for whom the dominant hand and laterality in case of CTS involvement were known. The analysis was based on the study of the dominant hand. We compared the demographic, clinical and radiographic characteristics (notably by the sum of the Kellgren Lawrence (KL) score) between patients with CTS and those without CTS. In case of comparison test, Chi-square or Fisher exact test were performed. Then, we investigated whether CTS was associated with grips strength, pinch strength and KL score by linear regression model and with number of joints painful pressure with negative-binomial model, after adjustment for age and sex.Results417 patients including 39 with CTS were included in our study. Obesity and metabolic syndrome were more frequent in patients with CTS than in those without CTS (obesity: 29.7% vs 10.2%, pConclusionThe risk factors for CTS in HOA are those known in the general population (hypothyroidism, obesity and metabolic syndrome). However, our study did not find any impact of CTS on the clinical signs and structural severity of HOA.References[1]Kim YH, Han EY, Kim J, Seo K-B, Jeon YT, Im SH. Associations between hand function and electrophysiological measurements in hand osteoarthritis patients of different ages with or without carpal tunnel syndrome. Sci Rep 2020;10:19278. https://doi.org/10.1038/s41598-020-74795-2.[2]Sellam J, Maheu E, Crema MD, Touati A, Courties A, Tuffet S, et al. The DIGICOD cohort: A hospital-based observational prospective cohort of patients with hand osteoarthritis - methodology and baseline characteristics of the population. Jt Bone Spine 2021;88:105171. https://doi.org/10.1016/j.jbspin.2021.105171.AcknowledgementsAll the patients who have accepted to participate to the DIGICOD cohort. All the investigators who manage or have managed patients’ recruitments, and the monitoring the clinical visits (Dr. Camille Deprouw, Dr. Sandra Desouches, Dr. Ariane Do, Dr. Emeline Gaigneux, Dr. Camille Glanowski, Dr. Karine Louati, Dr. Stéphanie Malbos, Dr. Sabine Trellu, Dr. Houda Ajlani, Dr. Juliette-Louise Petit and Dr. Clémence Gorlier all from the Rheumatology Department of AP–HP Saint-Antoine Hospital), the staff members of the URCEST and of the Centre des Ressources Biologiques from AP–HP Saint-Antoine Hospital.Funding of the DIGICOD cohortTRB Chemedica unrestricted research grantDisclosure of InterestsNone declared

BackgroundAmong the general population over 60 years-old, the decrease in grip strength is a marker of morbidity and mortality: its measurement during follow-up consultations is considered as a predictive marker of good health status or the patient’s overall fragility (1). However, hand osteoarthritis (HOA), which can modulate grip strength and is also associated with comorbidities is never taken into account, while it is a very common disease.ObjectivesThe objectives of this study are to describe grip strength in a symptomatic HOA population, to investigate painful osteoarthritic joints associated with decreased grip strength, and to determine whether decreased grip strength is independently associated with comorbidities in this population.MethodsDIGICOD is a hospital-based observational cohort including patients with radiographic features of HOA of at least 2 joints or radiographic thumb base OA. Inflammatory rheumatism or crystal arthropathy were excluded. The data at baseline were used for the analysis. Grip strength was the higher score of 3 repeated measures using a Jamar dynamometer. Baseline grip strength of the dominant hand was compared in the cohort between men and women (Student’s T test) and was described by age (by 10-year age groups using Kruskal-Wallis test). In this cross-sectional study, factors associated with a decreased grip strength were investigated using univariate and then multivariate linear regression analysis (with adjustment on age, BMI and variables with p ≤ 0.2 in univariate analysis) with stratification by sex. Results were presented by beta coefficients and their 95% confidence intervals. A first analysis focused on the association of grip strength with local factors: painful locations in the dominant hand by row and radiographic severity according to the total Kellgren-Lawrence (KL) score. The second analysis assessed the patient-level association between decreased grip strength and general characteristics, including cumulative comorbidities and markers of radio-clinical severity of hand OA, namely the AUSCAN pain score and total KL score. A sensitivity analysis was performed to look for association between grip strength and each comorbidity.Results394 patients were analyzed, including 329 women (mean ± SD of the dominant hand’s grip strength of 21.6 ± 6.9 kg) and 65 men (34.9 ± 9.8 kg) with a mean age of 66.9 ± 7.3 years. Grip strength decreased with age (pAmong women, locally, decreased grip strength was independently associated with painful involvement of at least 2 metacarpophalangeal joints (MCPs) (estimated coefficient [95% CI] -3.6 [-6.2; -1.0] kg versus no painful MCPs) but not with proximal and distal interphalangeal joints, and with a high KL total sum score (-0.06 [-0.10; -0.01] kg per additional point). At the patient-level, decreased grip strength was not associated with comorbidities but with radio-clinical severity (pAmong men, neither radiographic severity nor painful locations were independently associated with a decrease of grip strength. Conversely, decreased grip strength was associated with at least 3 comorbidities (-8.5 [-15.5; -1.43] kg versus a single comorbidity being OA), independently of radiographic severity. The study of comorbidities individually did not show any particular association with grip strength.ConclusionIn this cohort of symptomatic HOA, the decrease of grip strength reflects the radio-clinical severity of hand OA among women, whereas among men, it is independently associated with the accumulation of comorbidities. The presence of hand OA should be considered for further studies investigation the relationship between grip strength and morbi-mortality.References[1]Bohannon RW. Grip Strength: An Indispensable Biomarker For Older Adults. CIA. oct 2019;Volume 14:1681‑91.Graph 1.Grip strength according to the number of comorbidities among men and womenDisclosure of InterestsNone declared

BackgroundArtificial intelligence techniques, in particular machine learning (ML), are increasingly used in rheumatology and especially in osteoarthritis (OA). ML studies in OA are very heterogeneous, hence the need to have an overview of their field of application.ObjectivesThe aim of this systematic literature review is to provide a comprehensive and exhaustive landscape of the use of ML in the clinical care of OA.MethodsA systematic review of the literature was performed in July 2021 using the Medline database with key words and MeSH terms referring to ML methods in OA. Only original articles in English were considered. Articles related to replacement surgery, theorical imaging, rehabilitation, molecular biology, and spinal or temporomandibular OA were excluded. For each selected article, the number of patients, the ML algorithms used, the type of data analyzed, the validation methods, and the data availability were collected.ResultsFrom 1,148 screened articles, 46 were selected and analyzed, most of which were published after 2017 (Figure 1). Twelve articles were related to diagnosis, 7 to prediction, 4 to phenotyping, 12 to severity and 11 to progression. The number of patients included ranged from 18 to 5,749. Deep learning (DL) was used in 35% of the cases. Imaging analyses represented 74% of the studies. Knee OA was studied in 85% of these articles while 15% investigated hip OA. None were on hand OA. Most of the studies were done on the same cohort with data from the Osteoarthritis Initiative (OAI) used in 46% of the articles whereas the Multi-Center Osteoarthritis Study (MOST) and the Cohort Hip and Cohort Knee Study (CHECK) cohort were respectively used in 11 % and 7 % of the articles. Data and source code were publicly available in 54% and 22% of the articles. External validation was provided in only 7 % of the articles.Figure 1.Article selection flow chartConclusionThis review provides a comprehensive update of ML in OA research. The number of ML articles in OA has increased exponentially over the last 5 years with applications across all major research themes. However, there is methodological heterogeneity, with articles based mainly on radiological data, but also on knee OA. To date, there is no ML article on digital osteoarthritis. This work also shows the need to develop clinical cohorts to bring more diversity in ML work and to allow external validation This article is the first systemic review of the literature in OA and provides an overview of ML in OA, its applications, limitations and perspectives.Disclosure of InterestsMarie Binvignat: None declared, Valentina Pedoia: None declared, Atul Butte Shareholder of: a minor shareholder in Apple, Facebook, Alphabet (Google), Microsoft, Amazon, Snap, 10x Genomics, Illumina, CVS, Nuna Health, Assay Depot, Vet24seven, Regeneron, Sanofi, Royalty Pharma, AstraZeneca, Moderna, Biogen, Paraxel, and Sutro, and several other non-health related companies and mutual funds, Speakers bureau: invited talks from Johnson and Johnson, Roche, Genentech, Pfizer, Merck, Lilly, Takeda, Varian, Mars, Siemens, Optum, Abbott, Celgene, AstraZeneca, AbbVie, Westat, and many academic institutions, medical or disease specific foundations and associations, and health systems, Paid instructor for: boards for Geisinger Health, Regenstrief Institute, Gerson Lehman Group, AlphaSights, Covance, Novartis, Genentech, and Merck, and Roche, Consultant of: Personalis and NuMedii; consultant to Samsung, Mango Tree Corporation, and in the recent past, 10x Genomics, Helix, Pathway Genomics, and Verinata (Illumina), Grant/research support from: NIH, Northrup Grumman (as the prime on an NIH contract), Genentech, Johnson and Johnson, FDA, Robert Wood Johnson Foundation, Leon Lowenstein Foundation, Intervalien Foundation, Priscilla Chan and Mark Zuckerberg, the Barbara and Gerson Bakar Foundation, and in the recent past, the March of Dimes, Juvenile Diabetes Research Foundation, California Governor’s Office of Planning and Research, California Institute for Regenerative Medicine, L’Oreal, and Progenity., Karine Louati: None declared, David Klatzmann: None declared, Francis Berenbaum: None declared, Encarnita Mariotti-Ferrandiz: None declared, Jérémie SELLAM Consultant of: MSD, Pfizer, Abbvie, Fresenius Kabi, BMS, Roche Chugai, Sandoz, Lilly, Gilead, Novartis, Janssen and grant research from Pfizer, MSD, Schwa Medico, BMS.

BackgroundDespite a high morbi-mortality rate, there are no definite strategy for subclinical interstitial lung disease (ILD) screening in patients with rheumatoid arthritis (RA).ObjectivesOur objectives were: 1. to identify risk factors for subclinical RA-ILD in a prospective discovery cohort (ESPOIR) 2.to develop a risk score for subclinical RA-ILD and 3. to validate the risk score in an independent replication cohort (TRANSLATE 2).MethodsPatients without pulmonary symptoms from 2 prospective RA cohorts who underwent chest HRCT scans were included. All patients were genotyped for MUC5B rs35705950. A risk score based on independent risk factors for subclinical RA-ILD was developed using multiple logistic regression in the discovery cohort. The risk score was tested for validation in the replication cohort.ResultsDiscovery and replication cohorts included 163 and 89 patients, respectively. Subclinical ILD was detected in 19.0% and 16.9% of the patients, respectively. In the discovery cohort, independent risk factors for subclinical RA-ILD were the MUC5B rs35705950 T risk allele (odds ratio [OR]=3.74; 95% confidence interval [CI] [1.37–10.39], male sex (OR=3.93; 95%CI [1.40–11.39]), older age at RA onset (for each year, OR=1.10; 95%CI [1.04–1.16]) and increased mean DAS28-ESR (for each unit, OR=2.03; 95%CI [1.24–3.42]). We developed a risk score for subclinical RA-ILD with AUC=0.82; 95%CI [0.70–0.94] (sensitivity (Se)=71.0%) and specificity (Sp)=79.6%). The risk score was validated in the replication cohort with AUC=0.78; 95%CI [0.65–0.92] (Se=86.7%, Sp=62.2%).ConclusionOur risk score could help identifying patients at high-risk for subclinical RA-ILD before the onset of pulmonary symptoms.Disclosure of InterestsPierre-Antoine Juge Speakers bureau: AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Consultant of: Bristol Myers Squibb, Benjamin Granger: None declared, Marie-Pierre Debray: None declared, Esther Ebstein: None declared, Fabienne Louis-Sidney: None declared, Joanna KEDRA: None declared, Tracy Doyle: None declared, Raphael Borie: None declared, Arnaud Constantin Consultant of: Abbvie, Amgen, Biogen, BMS, Boehringer Ingelheim, Fresenius Kabi, Galapagos, Janssen, Lilly, Medac, MSD, Mylan, Novartis, Pfizer, Procter & Gamble, Roche, Sanofi, UCB, Viatris, Bernard Combe Consultant of: AbbVie, BMS, Eli-Lilly, Gilead, Janssen, Merck, Novartis, Pfizer, Roche-Chugai, Sanofi, UCB, René-Marc Flipo Consultant of: Abbvie, Janssen, MSD and Pfizer. He reports research grants from Abbvie, Janssen, Novartis and Pfizer, Xavier Mariette Consultant of: BMS, Gilead, Janssen, Pfizer, Samsung, UCB, Olivier VITTECOQ: None declared, Alain Saraux: None declared, Guillermo CARVAJAL ALEGRIA: None declared, Jean Sibilia Consultant of: AbbVie, Lilly, MSD, Amgen, Pfizer, BMS, Janssen, Roche, Sandoz, Sanofi-Genzyme, SOBI, UCB, Novartis, Grant/research support from: AbbVie, Lilly, MSD, Amgen, Pfizer, BMS, Janssen, Roche, Sandoz, Sanofi-Genzyme, SOBI, UCB, Novartis, Francis Berenbaum: None declared, Caroline Kannengiesser: None declared, Catherine Boileau: None declared, Jeffrey Sparks Consultant of: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Gilead, Inova Diagnostics, Janssen, Optum, and Pfizer, Grant/research support from: National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers R01 AR077607, P30 AR070253, and P30 AR072577), The R. Bruce and Joan M. Mickey Research Scholar Fund, Bristol Myers Squibb,Bruno Crestani Speakers bureau: Boehringer Ingelheim, AstraZeneca, Roche, Sanofi, Grant/research support from: MedImmune, Roche, Boehringer Ingelheim, Bruno Fautrel Consultant of: AbbVie, Amgen, Biogen, BMS, Celgene, Fresenius Kabi, Janssen, Lilly, Medac, MSD, NORDIC Pharma, Novartis, Pfizer, Roche, SOBI, UCB, Grant/research support from: AbbVie, Lilly, MSD, Pfizer, Philippe Dieudé Speakers bureau: Roche – Chugai, Bristol Myers Squibb, Consultant of: Pfizer, Roche – Chugai, Bristol Myers Squibb, Abbvie, MSD, Grant/research support from: Novartis

BackgroundThe Fibrosis-4 (FIB4) score, including age, transaminases and platelets, can detect severe fibrosis (F3-F4) in patients with Non Alcoolic Steato Hepatitis (NASH) and could be of interest in the follow-up of patients with RA. Indeed, platelets contribute to the pathophysiology of RA, transaminases are used in the liver monitoring of our treatments. In addition, retrospective data suggested the association between FIB4 and mortality in RA (1).ObjectivesWe aimed to evaluate the value of the FIB4 score as a prognostic factor in RA in the prospective ESPOIR cohort.MethodsPatients of the ESPOIR cohort diagnosed with RA according to ACR-EULAR criteria were included in our analysis. The formula for the FIB-4 score is as follows: [Age (years) × ASAT (U/L)] / [Platelet count (10^9/L) × ALT (U/L)1/2]. The analyses were based on linear mixed-effects models with a random effect on the subject to account for repeated measures throughout time.Results633 of the 813 patients included met the ACR/EULAR criteria for RA and had a calculable FIB4 score. Median FIB4 was 0.75 IQR (0.53-0.99) and 61 patients (9.6%) had a high FIB4 score at baseline. Baseline FIB4 was significantly higher in patients with a chronic alcohol consumption (p=0.021) or viral hepatitis (pTable 1.Associations of FIB4 score with DAS28 and modified Sharp score evolutions in multivariate analysesVariableVariables included in modelp-valueDAS28TimeAge0.97Baseline number of swollen jointsBaseline Rheumatoid Factor0.51evolution over timeBaseline ACPA (presence)0.97Baseline CRPBaseline modified Sharp score > 00.15Baseline FIB40.26Modified Sharp scoreTime0.052Age0.0005Baseline number of swollen joints0.38Baseline Rheumatoid Factor0.61evolution over timeBaseline ACPA (presence)0.012Baseline CRP0.84Baseline FIB40.25ConclusionOur study was the first to evaluate the value of FIB4 in a prospective cohort of RA patients. The present prospective cohort study with a 10-year follow-up did not find a prognostic role of FIB4 in RA, in contrast to previous retrospective studies. Reassuringly, FIB4 score was not increased by DMARD treatment after 10 years of follow-up, confirming the absence of long-term DMARD-related hepatotoxicity.References[1]Seung Up Kim, Beom Kyung Kim, Jun Yong Park, Do Young Kim, Sang Hoon Ahn, Yong-Beom Park, Kwang-Hyub Han & Sang-Won Lee (2018): Fibrosis-4 index at diagnosis can predict all-cause mortality in patients with rheumatoid arthritis: A retrospective monocentric study, Modern Rheumatology, DOI: 10.1080/14397595.2018.1558760Figure 1.Impact of baseline FIB4 score on DAS28, HAQ and total modified-Sharp score over time.AcknowledgementsAn unrestricted grant from Merck Sharp and Dohme (MSD) was allocated for the first 5 years. Two additional grants from INSERM were obtained to support part of the biological database. The French Society of Rheumatology, Pfizer, Abbvie, Lilly, Sanofi also supported the ESPOIR cohort study.We also wish to thank Nathalie Rincheval (CHU Montpellier and EA 2415) who did expert monitoring and data management and all the investigators who recruited and followed the patients (F. Berenbaum, Paris-Saint Antoine, MC. Boissier, Paris-Bobigny, A. Cantagrel, Toulouse, B. Combe, Montpellier, M. Dougados, Paris-Cochin, P. Fardellone et P. Boumier Amiens, B. Fautrel, Paris-La Pitié, RM. Flipo, Lille, Ph. Goupille, Tours, F. Liote, Paris- Lariboisière, O. Vittecoq, Rouen, X. Mariette, Paris Bicetre, P. Dieude, Paris Bichat, A. Saraux, Brest, T. Schaeverbeke, Bordeaux, J. Sibilia, Strasbourg) V. Devauchelle and C Lukas for expert X-ray reading.Disclosure of InterestsNone declared.