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Learn more: PMC Disclaimer | PMC Copyright Notice Sci Rep . 2026 Feb 24;16:10339. doi: 10.1038/s41598-026-40493-8 Search in PMC Search in PubMed View in NLM Catalog Add to search Clustering reveals diagnostic overlap between Still’s disease and a hyperinflammatory subset of seronegative rheumatoid arthritis Alexandre Mercier-Guery Alexandre Mercier-Guery 1 University of Lyon, University Lyon 1, Lyon, 69100 France 2 Department of Rheumatology, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, 69003 France 3 INSERM UMR 1033, Lyon, 69100 France Find articles by Alexandre Mercier-Guery 1, 2, 3, ✉, # , Thomas El-Jammal Thomas El-Jammal 4 Internal medicine, National Reference Center for AutoInflammatory Diseases (CEREMAIA), University Hospital Croix-Rousse, Hospices Civils de Lyon, Lyon, 69004 France 5 Tissular Biology Laboratory, Institute of Protein Biology and Chemistry, UMR CNRS 5305 Therapeutic Engineering, Lyon, 69007 France Find articles by Thomas El-Jammal 4, 5, # , Nour El-Nayef Nour El-Nayef 1 University of Lyon, University Lyon 1, Lyon, 69100 France 3 INSERM UMR 1033, Lyon, 69100 France 6 Department of Rheumatology, Lyon Sud Hospital, Hospices Civils de Lyon, Pierre- Bénite, F-69495 France Find articles by Nour El-Nayef 1, 3, 6 , Emmanuel Massy Emmanuel Massy 1 University of Lyon, University Lyon 1, Lyon, 69100 France 6 Department of Rheumatology, Lyon Sud Hospital, Hospices Civils de Lyon, Pierre- Bénite, F-69495 France Find articles by Emmanuel Massy 1, 6 , Nicolas Fournier Nicolas Fournier 4 Internal medicine, National Reference Center for AutoInflammatory Diseases (CEREMAIA), University Hospital Croix-Rousse, Hospices Civils de Lyon, Lyon, 69004 France 5 Tissular Biology Laboratory, Institute of Protein Biology and Chemistry, UMR CNRS 5305 Therapeutic Engineering, Lyon, 69007 France Find articles by Nicolas Fournier 4, 5 , Pascal Sève Pascal Sève 4 Internal medicine, National Reference Center for AutoInflammatory Diseases (CEREMAIA), University Hospital Croix-Rousse, Hospices Civils de Lyon, Lyon, 69004 France 5 Tissular Biology Laboratory, Institute of Protein Biology and Chemistry, UMR CNRS 5305 Therapeutic Engineering, Lyon, 69007 France Find articles by Pascal Sève 4, 5 , Cyrille Confavreux Cyrille Confavreux 1 University of Lyon, University Lyon 1, Lyon, 69100 France 6 Department of Rheumatology, Lyon Sud Hospital, Hospices Civils de Lyon, Pierre- Bénite, F-69495 France Find articles by Cyrille Confavreux 1, 6 , Yvan Jamilloux Yvan Jamilloux 4 Internal medicine, National Reference Center for AutoInflammatory Diseases (CEREMAIA), University Hospital Croix-Rousse, Hospices Civils de Lyon, Lyon, 69004 France 5 Tissular Biology Laboratory, Institute of Protein Biology and Chemistry, UMR CNRS 5305 Therapeutic Engineering, Lyon, 69007 France Find articles by Yvan Jamilloux 4, 5, # , Fabienne Coury Fabienne Coury 1 University of Lyon, University Lyon 1, Lyon, 69100 France 2 Department of Rheumatology, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, 69003 France 3 INSERM UMR 1033, Lyon, 69100 France Find articles by Fabienne Coury 1, 2, 3, # Author information Article notes Copyright and License information 1 University of Lyon, University Lyon 1, Lyon, 69100 France 2 Department of Rheumatology, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, 69003 France 3 INSERM UMR 1033, Lyon, 69100 France 4 Internal medicine, National Reference Center for AutoInflammatory Diseases (CEREMAIA), University Hospital Croix-Rousse, Hospices Civils de Lyon, Lyon, 69004 France 5 Tissular Biology Laboratory, Institute of Protein Biology and Chemistry, UMR CNRS 5305 Therapeutic Engineering, Lyon, 69007 France 6 Department of Rheumatology, Lyon Sud Hospital, Hospices Civils de Lyon, Pierre- Bénite, F-69495 France ✉ Corresponding author. # Contributed equally. Received 2025 Nov 28; Accepted 2026 Feb 13; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13031936 PMID: 41735429 Abstract Still’s disease (SD) and rheumatoid arthritis (RA), particularly seronegative RA, may overlap clinically and biologically, complicating diagnosis. We explored data-driven overlaps between SD, seronegative RA, and seropositive RA using unsupervised clustering. We retrospectively included 312 adults: 98 SD from the multicentric AURAL Still cohort and 214 RA (93 seropositive, 121 seronegative). Baseline clinical and laboratory data were analysed using factor analysis of mixed data followed by k-means clustering. SD patients were younger than RA patients and more frequently presented with fever and systemic features. Inflammatory markers (notably CRP and ferritin) were higher in SD than in both RA subsets. Three clusters were identified: Cluster 1 ( n = 196) mainly comprised seropositive (45%) and seronegative RA (50%), with mild systemic inflammation and symmetrical polyarthritis; Cluster 2 ( n = 73) was predominantly SD (92%), with systemic features, high inflammation and polyarthritis, and more frequent spontaneous remission without treatment; Cluster 3 ( n = 43) mixed SD (49%) and seronegative RA (42%), characterised by moderate inflammation and asymmetrical oligoarthritis with low autoantibody rates. Most seronegative RA clustered with classical RA, but ~ 20% overlapped with SD-like phenotypes, suggesting a hyper-inflammatory subset which could be conceptualized as Systemic Inflammatory RA (SIRA). This proposal is hypothesis-generating and warrants prospective validation. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-026-40493-8. Subject terms: Diseases, Immunology, Medical research, Rheumatology Introduction Still’s disease (SD) is a rare systemic polygenic autoinflammatory disease characterised by remittent fever, articular manifestations, and transient maculopapular skin rash associated with a striking neutrophilic leukocytosis 1 – 3 . Hyperferritinemia, low glycosylated ferritin levels, and sore throat are other frequently observed and distinctive features 4 , 5 . Three clinical course patterns have been identified: a monocyclic self-limited illness; a polycyclic illness with intermittent flares; and a chronic articular disease, which may lead to joint damage 6 . Articular involvement is common in SD (occurring in 70 to 100% of cases) and typically includes both arthralgia and arthritis, most frequently affecting the wrists, knees, and ankles, although any joint may be involved. While arthritis is initially mild and transient, it can progress to chronic, destructive, symmetrical polyarthritis that can fulfil the classification criteria for rheumatoid arthritis (RA) 7 . RA is the most common chronic inflammatory arthritis, with a prevalence ranging from 0.5 to 1% 8 . If not properly treated, the disease can lead to bone erosion and joint deformities, resulting in disability. RA is typically associated with the presence of rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPA), detected in approximately 70 and 60% of patients, respectively 9 . However, seropositivity is not mandatory for the diagnosis of RA. Indeed, seronegative RA, defined by the absence of these autoantibodies despite fulfilling the 2010 ACR/EULAR classification criteria, accounts for approximately 20–30% of all RA cases 10 , 11 . This seronegative subgroup, characterized by variable clinical presentations, broad differential diagnoses, and heterogeneous therapeutic responses, poses significant diagnostic challenges and may represent a distinct clinical and pathogenetic phenotype 12 . Several studies suggest that SD may represent a clinical entity that overlaps with other systemic diseases. It shares important similarities with RA, especially the seronegative form, as both are seronegative conditions associated with joint inflammation, and potential articular destruction 6 , 13 . In 2013, Ichida et al. identified two distinct subtypes among patients with SD: an RA-like subtype marked by severe articular involvement and a non-RA subtype characterised by systemic features and macrophage activation syndrome 14 . In this study, we aimed to characterise similarities and differences between seropositive RA, seronegative RA, and SD. Methods Study populations We conducted a retrospective analysis comparing data from three cohorts of patients: those with SD, seropositive RA, and seronegative RA. Patients with SD were retrospectively selected from the observational AURAL Still Study cohort, which includes patients diagnosed between January 2001 and March 2021 across 10 regional clinical centers 15 . Diagnosis was confirmed at the last follow-up by the referring physician, and all medical records were independently validated by at least two investigators. Only adult SD patients with joint involvement (arthritis or arthralgia) were included. Patients with more than 50% missing baseline data were excluded. RA patients were retrospectively recruited from the Rheumatology Department of Lyon Sud University Hospital (Pierre-Bénite, France) between January 2010 and September 2022. Cases were identified using keyword searches in the institutional medical records system (Easily ® , Hospices Civils de Lyon). All cases were reviewed and validated by two experienced rheumatologists. Inclusion criteria were age over 18 years, and a diagnosis of either (i) adult-onset seropositive RA (positive RF and/or ACPA) fulfilling the 2010 ACR/EULAR classification criteria, or (ii) seronegative RA (negative RF and ACPA) presenting as polyarthritis or oligoarthritis, with exclusion of alternative rheumatic diagnosis (e.g., pseudogout, gout, psoriatic arthritis, osteoarthritis, systemic lupus erythematosus, etc.). Patients with more than 50% missing data were excluded. Fautrel’s and Yamaguchi’s criteria scores were calculated for all RA patients 16 , 17 . Measurements All data were retrospectively collected using an anonymous and standardized electronic Case Report Form (Ennov Clinical ® , v.7.5.720.1, Ennov, Paris, France) for the AURAL Still study and a standardized form for the RA cohorts. Clinical data were obtained from the AURAL database or from RA patient records at the time of diagnosis. Collected variables included age, ethnicity, general symptoms, adenopathy, splenomegaly, joint involvement (number of affected joints, location, synovitis, and ankylosing carpal arthritis), and extra-articular manifestations (pulmonary, cardiac, nasopharyngeal, ophthalmologic). Biological data collected near the time of diagnosis included blood count, C-reactive protein (CRP), transaminases, lactate dehydrogenase (LDH), ferritin, glycosylated ferritin, lipid profile, and proteinuria. The autoimmune profile encompassed antinuclear antibodies (ANA, titers > 1:160), anti-extractable nuclear antigens (anti-ENA), antineutrophil cytoplasmic antibodies (ANCA), RF, ACPA, complement levels (C3, C4, CH50), and cryoglobulinemia when available. In the seronegative RA group, patients who developed RF or ACPA positivity during follow-up, were excluded. RF was measured using immunonephelometry (BN ProSpec, Siemens; positive > 20 IU/mL), and ACPA using second-generation anti-CCP flow immunoassay (BIORAD; positive > 3 IU/mL). Statistical analysis We compared the baseline characteristics between the three groups (SD, seropositive RA, and seronegative RA) using ANOVA for numeric variables when residuals met the normality assumption and Chi squared test or Fisher’s exact test for qualitative variables when appropriate. A significance threshold of p < 0.05 was applied, and p-values were adjusted for multiple testing using Bonferroni method. All of the tests were two-tailed. Subsequently, we performed a Factor Analysis of Mixed Data (FAMD) on patients’ baseline data to explore both quantitative and qualitative variables. Missing values in numerical variables were imputed using the median of each respective column. For categorical columns, missing values were imputed with the highest value of each respective column. The k-means algorithm was then applied to the FAMD coordinates along the first two dimensions, grouping individuals into three clusters based on Euclidean distances between them. Variables with more than 20% missing data were excluded from the clustering algorithm. To select the number of clusters (k), we evaluated candidate values (k = 2–6) using complementary criteria: (i) within-cluster sum of squares (WSS; elbow method), (ii) average silhouette width, and (iii) cluster stability under bootstrap resampling quantified by Jaccard similarity (mean and minimum across clusters). Analyses were performed on FAMD individual coordinates (ncp = 10), using the first two dimensions for clustering, and k-means was run with nstart = 50. Cluster stability was assessed using B = 200 bootstrap resamples. The final k was chosen based on the best compromise between quantitative support (fit/stability) and clinical interpretability, avoiding overly small or unstable clusters (Table S3, Figures S1 -S2). All statistical analyses were performed using R-4.2.2 (2022-10-31 ucrt) (R Core Team, 2022; R Foundation for Statistical Computing, Vienna, Austria). Ethical considerations All patients—adult-onset Still’s disease and rheumatoid arthritis (seropositive/seronegative)—were retrospectively included within the AURAL Still study framework. The study has been approved by the HCL internal personal protection committee and reported on the transparency portal. Data processing complies with the European General Data Protection Regulation 2016/679 (GDPR) and the amended law of January 6, 1978 relating to information technology, files, and civil liberties (Data Protection Act) and the French data protection authority CNIL (#19_348) and is registered on ClinicalTrials.gov ( NCT05055882 ). This retrospective study was conducted in accordance with applicable regulations. In line with French law for retrospective studies, patients were informed through an information notice and were given the opportunity to object to the use of their data; no written informed consent was required. Results Characteristics of the populations A total of 318 patients were initially included: 98 with articular SD, 94 with seropositive RA, and 126 with seronegative RA (Fig. 1 ). Among the 94 patients initially identified as having seropositive RA, one was excluded after expert review because of secondary seronegativity, leaving 93 seropositive RA patients included in the final analysis. Among the 126 seronegative RA patients, 5 were excluded: 1 was later diagnosed with SAPHO syndrome, 1 was with Sharp’s syndrome, 2 were classified as Immune checkpoint inhibitor (ICI)–induced inflammatory arthritis and 1 had excessive missing data at baseline. No patient was subsequently tested positive for RF or ACPA during follow-up. Fig. 1. Open in a new tab Study flow chart. Flowchart depicting the selection and categorization of 318 patients into three groups: Still’s disease (SD), seropositive rheumatoid arthritis (RA), and seronegative RA. Patients excluded due to early diagnosis, differential diagnosis, missing data, or absence of joint involvement are highlighted. RA: Rheumatoid Arthritis; SD: Still’s disease. Baseline characteristics of the study population are summarized in Table 1 . At diagnosis, the mean age and sex ratio differed across groups: 42 years (58% women) in the SD group, 51 years (76% women) in seropositive RA, and 63 years (66% women) in seronegative RA ( p < 0.001). Fever was frequent in SD (93%), rare in seropositive RA (3%), and more common in seronegative RA (8%, p < 0.001). Weight loss, defined as ≥ 5% of baseline body weight within 1 month or ≥ 10% within 6 months, was most prevalent in SD (57%), less common in seronegative RA (22%), and rare in seropositive RA (10%, p < 0.001). The mean follow-up duration up to the time of recruitment (September 2022) was 7.4 years for seronegative RA and 5.9 years for seropositive RA. Table 1. Baseline characteristics. SD ( n = 98) Seropositive RA ( n = 93) Seronegative RA ( n = 121) P -value Demographics Age at diagnosis (Mean (± SD)) 41.9 (± 15.2) 51.5 (± 14.8) 62.8 (± 14.1) *** Sex: women (%, (n)) 58.2% (57/98) 76.3% (71/93) 66.1% (80/121) * General symptoms Fever (%, (n)) 93.8% (91/98) 3.2% (3/93) 8.3% (10/121) *** Weight loss (%, (n)) 56.6% (47/83) 9.7% (9/93) 22.3% (27/121) *** Clinical manifestations Synovitis (%, (n)) 49.2% (31/63) 96.8% (90/93) 90.1% (109/121) *** Bilateral (%, (n)) 84.4% (76/90) 97.8% (91/93) 95.0% (115/121) ** Symmetrical (%, (n)) 59.0% (46/78) 90.3% (84/93) 86.0% (104/121) *** Monoarticular (%, (n)) 14.6% (6/41) 1.1% (1/92) 5.0% (6/121) *** Oligoarticular (%, (n)) 29.2% (12/41) 3.3% (3/92) 14.2% (18/121) *** Polyarticular (%, (n)) 56.1% (23/41) 95.6% (86/92) 80.8% (97/121) *** Small joints (%, (n)) 68.3% (67/98) 98.9% (92/93) 84.3% (102/121) ns Large joints (%, (n)) 61.2% (60/98) 71.0% (66/93) 52.9% (91/121) *** Extra articular manifestations SRE (%, (n)) 49.5% (47/95) 12.9% (12/93) 9.1% (11/121) *** Splenomegaly (%, (n)) 14.6% (12/82) 1.1% (1/90) 1.7% (2/121) *** Hepatomegaly (%, (n)) 11.3% (9/80) 5.6% (5/90) 4.1% (5/121) ns Ophthalmic (%, (n)) 5.2% (5/97) 0% (0/93) 0.8% (1/121) ns ENT(%, (n)) 67.0% (63/94) 0% (0/93) 4.1% (5/121) *** Skin rash (%, (n)) 73.2% (71/97) 3.2% (3/93) 6.6% (8/121) *** Respiratory (%, (n)) 19.8% (19/96) 7.8% (7/90) 9.9% (12/121) ** Pleural effusion (%, (n)) 12.5% (10/80) 3.3% (3/90) 2.5% (3/121) *** Pericarditis (%, (n)) 17.5% (14/80) 1.1% (1/89) 0.8% (1) *** Lab findings Haemoglobin (g/L) (Mean (± SD)) 115 (± 18) 132 (± 19) 131 (± 18) *** Leukocytes (G/L) (Mean (± SD)) 14.5 (± 5.8) 8.7 (± 2.8) 8.7 (± 3.0) *** CRP (mg/L) (Mean (± SD)) 185.0 (± 106) 19.2 (± 28.5) 38.2 (± 47.7) *** ALT (UI/L) (Mean (± SD)) 87 (± 152) 24 (± 16) 25 (± 18) *** AST (UI/L) (Mean (± SD)) 78 (± 162) 24 (± 10) 24 (± 10) *** Ferritin (µg/L) (Mean (± SD)) 11214.2 (± 21318.2) 136.3 (± 118.5) 243.6 (± 258.6) *** Glycosylated ferritin (%) (Mean (± SD)) 18.2± (12.2) NA NA NA Positive RF (%, (n)) 10.0% (7/69) 80.6% (75/93) 0% (0/121) *** Positive ACPA (%, (n)) 3.3% (2/60) 98.9% (92/93) 0% (0/121) *** Open in a new tab We compared the baseline characteristics between the three groups (SD, seropositive and seronegative RA) using the ANOVA method. Weight loss was defined as ≥ 5% within 1 month or ≥ 10% within 6 months. CRP: C-reactive protein, ALT: alanine transaminase, AST : aspartate aminotransferase, GGT: gamma glutamyl transferase, large joints were defined as the shoulder, elbow, hip, knee, and ankle, while small joints included all other joints of the limbs. NA: Non Available, ns: non significant, ENT: ear-nose-throat involvement. * p value < 0.05, ** <0.01, ***<0.001. Articular involvement was present in all groups but varied notably (Table 1 , Table S2). SD patients exhibited predominantly bilateral (84%) and symmetrical (59%) arthritis, frequently affecting wrists (47%) and knees (46%). In seropositive RA, polyarthritis was bilateral (98%) and symmetrical (90%), predominantly involving metacarpophalangeal (MCP) (85%) and proximal interphalangeal joints (81%), with erosions in 37%. Seronegative RA patients had a similar joint distribution, with slightly lower bilateral polyarthritis (80%) and fewer erosions (23%). Using a small- versus large-joint grouping, small-joint involvement was frequent in both RA subsets (seropositive RA: 98.9%; seronegative RA: 84.3%) and less common in Still’s disease (68.3%) (Table 1 ). These differences did not reach statistical significance. Large-joint involvement was also common across groups (Still’s disease: 61.2%; seropositive RA: 71.0%; seronegative RA: 52.9%). Extra-articular manifestations were common in SD, particularly skin rash (73%), ENT (Ear-Nose-Throat) involvement (67%), pericarditis (17.5%), and pleural effusion (12.5%). These manifestations were uncommon in the RA groups and were mainly limited to respiratory involvement (8% in seropositive RA and 10% in seronegative RA). Regarding laboratory findings, mean CRP (185 mg/L), ferritin (11,214 µg/L), transaminases, and leukocyte count were markedly higher in SD compared to both RA groups. Seropositive RA patients displayed moderate CRP elevation (mean, 19 mg/L) and near-universal positivity for ACPA (99%) and frequent positivity for RF (81%). Seronegative RA had intermediate CRP elevation (mean, 38 mg/L) and consistently negative RF and ACPA status. Fautrel and Yamaguchi criteria were respectively met by 63 and 58% of SD patients, while only one seronegative RA patient met both sets of criteria. No other seronegative or seropositive RA patients met either of these diagnostic criteria. Clustering analysis reclassifies patients into three (non-redundant) groups Clinicobiological presentation Among the 312 patients analyzed, clustering allowed us to identify 3 distinct clusters, including 196, 73 and 43 patients for clusters 1 to 3, respectively. Each cluster was homogeneous and distinctive in terms of symptom presentation. The descriptive analysis and comparison of the clusters are outlined in Table 2 . Table 2. Comparison of demographic, clinical, and biological characteristics across the three clusters. Variables Cluster 1 Cluster 2 Cluster 3 p .overall p .C1 vs. C3 p .C2 vs. C3 p .C1 vs. C2 N = 196 N = 73 N = 43 Demographics and general symptoms Women Sex, n (%) 135/196 (68.9%) 43/73 (58.9%) 30/43 (69.8%) ns ns ns ns Fever, n (%) 12/196 (6.15%) 69/73 (94.5%) 22/43 (51.2%) *** *** *** *** Weight Loss, n (%) 160/195 (82.1%) 22/62 (35.5%) 33/40 (82.5%) *** ns *** *** Eruption, n (%) 10/195 (5.13%) 57/73 (78.1%) 15/43 (34.9%) *** *** *** *** Clinical manifestations Oligoarticular, n (%) 3/196 (1.56%) 2/25 (8.00%) 26/38 (68.4%) *** *** *** * Polyarticular, n (%) 186/192 (96.9%) 21/25 (84.0%) 3/38 (7.89%) *** *** *** * Monoarticular, n (%) 3/196 (1.56%) 2/25 (8.00%) 9/38 (23.7%) *** *** *** * Bilateral, n (%) 196/196 (100%) 63/67 (94.0%) 23/41 (56.1%) *** *** *** ** Symmetrical, n (%) 181/196 (92.3%) 44/57 (77.2%) 9/39 (23.1%) *** *** *** ** Synovitis, n (%) 179/193 (92.7%) 19/49 (38.8%) 32/35 (91.4%) *** ns *** *** Small joints, n (%) 186/196 (94.9%) 54/73 (74.0%) 21/43 (48.8%) *** *** *** ** Large joints, n (%) 145/196 (74.0%) 50/73 (68.5%) 22/43 (51.2%) *** *** * ns Extra articular manifestations ENT, n (%) 6/167 (3.61%) 49/72 (68.1%) 12/40 (30.0%) *** *** *** *** Splenomegaly, n (%) 3/192 (1.56%) 11/62 (17.7%) 1/39 (2.56%) *** ns * *** Hepatomegaly, n (%) 8/192 (4.17%) 8/61 (13.1%) 3/39 (7.69%) ns ns ns ns Ophthalmic, n (%) 1/149 (0.67%) 4/73 (5.48%) 0/43 (0.0%) ns ns ns ns Lab findings Hemoglobin (G/L), Median [IQR] 132 [123;142] 116 [104;128] 128 [117;137] *** * * *** Leukocytes (G/L), Median [IQR] 8.30 [6.80;10.5] 14.9 [9.33;17.0] 9.95 [6.70;14.0] *** * ** *** Creatinine (µmol/L), Median [IQR] 64.0 [56.8;74.0] 63.5 [57.0;75.0] 66.0 [57.0;74.2] ns ns ns ns CRP (mg/L), Median [IQR] 13.6 [4.10;33.0] 166 [77.0;249] 81.0 [9.25;174] *** *** ** *** AST (U/L), Median [IQR] 22.0 [19.0;28.0] 42.0 [25.0;67.0] 21.0 [18.0;28.0] *** ns ** *** ALT (U/L), Median [IQR] 21.0 [15.0;29.0] 44.0 [21.0;86.0] 20.0 [15.0;28.0] *** ns ** *** Gamma-GT (U/L),, Median [IQR] 30.0 [20.0;59.0] 74.0 [41.2;156] 36.5 [22.2;80.8] *** ns * *** ANA, Median [IQR] 50 (26.3%) 10 (16.1%) 5 (13.5%) ns ns ns ns Positive ACPA, n (%) 90 (46.4%) 2 (4.44%) 4 (11.8%) *** *** ns *** Positive RF, n (%) 75 (38.9%) 6 (11.5%) 2 (5.41%) *** ** ns ** Diagnosis *** *** *** *** Seronegative RA 98 (50.0%) 5 (6.85%) 18 (41.9%) Seropositive RA 88 (44.9%) 1 (1.37%) 4 (9.30%) SD 10 (5.10%) 67 (91.8%) 21 (48.8%) Open in a new tab This table presents the distribution of key demographic, clinical, and laboratory variables across the three clusters identified by K-means analysis (Cluster 1 – green, Cluster 2 – yellow, Cluster 3 – purple). Values are expressed as n (%) for categorical variables and median [interquartile range] for continuous variables. Statistical significance is assessed globally across all clusters (p.overall) and between pairwise comparisons (p.C1 vs. C2, p.C1 vs. C3, p.C2 vs. C3) using appropriate tests (Chi² or Kruskal-Wallis as applicable). Weight loss was defined as ≥ 5% within 1 month or ≥ 10% within 6 months, large joints were defined as the shoulder, elbow, hip, knee, and ankle, while small joints included all other joints of the limbs. * p value < 0.05, ** <0.01, ***<0.001. RA: Rheumatoid arthritis SD: Still’s disease CRP: C-reactive protein AST: Aspartate aminotransferase, ALT: Alanine aminotransferase, GGT (Gamma-GT): Gamma-glutamyl transferase, ANA: Antinuclear antibodies, ACPA: Anti-citrullinated protein antibodies, RF: Rheumatoid factor. K-means clustering identified three distinct phenotypic clusters within the study population (Table 2 ; Fig. 2 ): Fig. 2. Open in a new tab K-means clustering representation (k = 3) based on the first two dimensions obtained from Factor Analysis of Mixed Data (FAMD). Each color indicates a distinct clinical phenotype identified through unsupervised analysis of patients with SD, seropositive RA and seronegative RA: cluster 1 (green), cluster 2 (yellow), cluster 3 (purple). Cluster 1 ( n = 196) included predominantly seronegative RA (50.0%) and seropositive RA (44.9%), with few SD patients (5.1%). General manifestations were uncommon, with infrequent fever (6.2%) and skin rash (5.1%). Joint involvement was classically polyarticular (96.9%), bilateral (100%), symmetrical (92.3%), predominantly affecting wrists (80.6%), PIP (71.4%), and MCP joints (81.6%). This cluster showed mild inflammatory markers (median CRP, 13.6 mg/L) and frequent autoantibody positivity (ACPA: 46.4%; RF: 38.9%). Cluster 2 ( n = 73) was predominantly composed of SD patients (91.8%), with limited representation of RA (8.2%), including 6.85% seronegative RA and 1.37% seropositive RA. This cluster exhibited pronounced general manifestations, such as fever (94.5%), weight loss (defined as ≥ 5% within 1 month or ≥ 10% within 6 months) (64.5%), and skin rash (78.1%). Joint involvement was predominantly polyarticular (84%), bilateral (94%), moderately affecting shoulders (28.8%) and wrists (49.3%), with limited involvement of small joints (PIP, 31.5%; MCP, 24.7%). High levels of inflammatory markers were observed (median CRP, 166 mg/L) alongside elevated transaminases (median AST, 42 U/L; ALT, 44 U/L). Autoantibodies were rarely detected (ACPA, 4.4%; RF, 11.5%). Cluster 3 ( n = 43) comprised a mixed population of SD (48.8%), seronegative RA (41.9%), and a minority of seropositive RA (9.3%). General manifestations were moderately frequent, including fever (51.2%) and skin rash (34.9%). Joint involvement was predominantly oligoarticular (68.4%), frequently asymmetrical (76.9%), and bilateral (56.1%) with low involvement of small joints (MCP, 16.3%; PIP, 11.6%). This cluster presented intermediate inflammatory markers (median CRP, 81 mg/L) and low frequency of autoantibodies (ACPA, 11.8%; RF, 5.4%). The three clusters showed significant differences. Cluster 2 demonstrated the highest frequencies of fever (94.5%), skin rash (78.1%), and weight loss (64.5%), significantly differing from clusters 1 and 3 (all, p < 0.001). Articular involvement patterns also varied notably: cluster 1 was characterized by symmetrical (92.3%), bilateral (100%), polyarticular arthritis predominantly involving wrists (80.6%), MCP (81.6%), and PIP joints (71.4%), significantly contrasting with cluster 3, which displayed predominantly asymmetrical (76.9%) and oligoarticular (76.3%) involvement ( p < 0.001). Shoulder involvement was most frequent in cluster 1 (55.4%; p < 0.001), while forefoot involvement was almost exclusive to cluster 1 (51.0%; p < 0.001). Biological markers also differed significantly: cluster 2 exhibited the highest median CRP level (166 mg/L) compared to clusters 3 (81 mg/L) and 1 (13.6 mg/L, p < 0.001). Likewise, transaminases (AST, ALT) and leukocyte counts were markedly higher in cluster 2 (all p < 0.001). Autoantibody positivity was significantly higher in cluster 1 (ACPA, 46.4%; RF, 38.9%) compared to clusters 2 and 3 ( p < 0.001). Splenomegaly and ENT manifestations were significantly more frequent in cluster 2 than in clusters 1 and 3 (both, p < 0.001). Notably, cluster 2 showed a higher rate of spontaneous remission without treatment compared to the other clusters ( p = 0.01 and 0.03, respectively). Regarding diagnostic distribution across clusters, 67/98 (68.4%) SD patients were assigned to Cluster 2, 10/98 (10.2%) to Cluster 1, and 21/98 (21.4%) to Cluster 3. Among seronegative RA patients, 98/121 (81.0%) were classified in Cluster 1, 5/121 (4.1%) in Cluster 2, and 18/121 (14.9%) in Cluster 3. For seropositive RA, 88/93 (94.6%) were found in Cluster 1, 1/93 (1.1%) in Cluster 2, and 4/93 (4.3%) in Cluster 3. Treatments Additional analysis revealed distinct treatment distribution among the three cohorts (SD, seropositive RA and seronegative RA). In the SD cohort, corticosteroids (CST, 88%), methotrexate (MTX, 39%), and IL-1 inhibitors (anakinra, 35%) were the most frequently administered treatments. Across RA cohorts, methotrexate (MTX) was the most commonly used therapy overall (history: 54% in seropositive RA; 61% in seronegative RA). Focusing on the last regimen associated with ≥ 3-month clinical remission (therapy recorded at inclusion), in seropositive RA this was MTX in 49%, followed by tocilizumab (TCZ) in 22.8% and TNF inhibitors in 16%. In seronegative RA, MTX remained predominant (58%), while bDMARDs were less frequent; among them, TCZ was the most commonly used agent (16%), and TNF inhibitors were used in 14% of cases. Cluster analysis revealed significant differences between groups. Cluster 1 showed the highest use of MTX (58.7%), while the most frequent therapy in cluster 2 was CST (82.9%) followed by MTX (34.3%). Cluster 3 showed a mixed treatment pattern, with a notable use of MTX (59.5%). These findings highlight variations in therapeutic strategies across cohorts and clusters, depending on clinical guidelines and prescribing habits. The last therapy associated with ≥ 3-month remission was predominantly methotrexate in Cluster 1 (104/196, 53.1%) and corticosteroids in Cluster 2 (58/70, 82.9%), while Cluster 3 showed a mixed pattern (methotrexate 25/42, 59.5%; corticosteroids 23/42, 54.8%) (Table S1 ). IL-1 inhibition (anakinra) was more frequent in Clusters 2 and 3 (22/70, 31.4%; 6/42, 14.3%) than in Cluster 1 (6/196, 3.1%). Cure without treatment was more frequent in Cluster 2 (25/54, 46.3%) than in Cluster 1 (23/183, 12.6%) and Cluster 3 (13/37, 35.1%) (Table S1 ). Discussion Various patterns of joint involvement have been described in SD, some resembling RA. Recent studies pointed out significant differences between seronegative and seropositive RA in terms of clinical presentation, disease severity, and response to therapy 18 – 20 . In this context, we compared seronegative RA with both seropositive RA and articular SD using a clustering approach, to determine whether this entity aligns more closely with an RA phenotype or an SD phenotype. In this study, we identified three distinct clusters based on clinical features and inflammatory markers at disease onset. The first cluster was characterized by mild systemic inflammation and a phenotype typical of seropositive RA. The second cluster exhibited high levels of inflammation, with polyarthritis predominantly affecting small and medium-sized joints, and was associated with systemic and extra-articular features such as fever and skin rash, closely resembling the classic presentation of SD. The third cluster showed moderate inflammatory activity, with bilateral, asymmetrical, poorly systematized oligoarthritis, and a non-negligible proportion of general symptoms—less frequent than in cluster 2—suggesting an overlap phenotype between RA and SD. Notably, 80% of patients with seronegative RA were classified into cluster 1, supporting the notion that seronegative RA is, in most cases, closer to RA than SD. One hypothesis is that some patients categorized as seronegative in our study may in fact display autoantibodies other than ACPA or RF and should therefore be considered as seropositive. Indeed, several recent studies have reported the presence of newly discovered autoantibodies in a significant proportion of both seropositive and seronegative RA patients 18 , 21 , suggesting that some individuals in the latter category may actually represent false-seronegative RA cases. These autoantibodies are mainly AMPA (anti-modified protein antibody) 22 , i.e. antibodies targeted to proteins that have undergone posttranslational modifications, such as carbamylation, as well as anti-mitochondrial antibodies. The remaining 20% of seronegative RA patients were primarily distributed between clusters 2 and 3, suggesting that approximately 5% of seronegative RA cases in our cohort exhibited a clinical profile compatible with SD (cluster 2). This accords with real-world data highlighting diagnostic heterogeneity and frequent reclassification in seronegative RA 12 . Cluster 3 (nearly equal SD and seronegative RA) reinforces SD’s clinical heterogeneity 23 – 25 , may reflect either SD with milder, more chronic articular expression or a distinct, as-yet uncharacterized entity. These observations suggest that seronegative RA may overlap with SD, making the distinction between the two entities challenging. However, given that cluster 3 differed markedly from the other clusters in several aspects, another interpretation is that it may represent a distinct, as-yet uncharacterized rheumatic entity. Consistently, Cluster 3 exhibited less systematized, asymmetrical, non-bilateral joint involvement, and intermediate CRP levels (higher than Cluster 1, lower than Cluster 2). Though close, analysis of baseline characteristics highlighted slight differences between seropositive and seronegative RA suggesting that they may be different entities. We found notably less metacarpophalangeal joint involvement and more carpal joint involvement in seronegative patients compared to seropositive patients as described in prior studies 26 , 27 . The extra-articular manifestations of RA have also been found to differ between both entities; for example, a meta-analysis reported that interstitial lung disease was more associated with high titres of ACPAs 28 which was observed in our study. Scleritis and rheumatoid nodules have also been reported to be more likely present in seropositive patients 29 , 30 . However, this was not observed in our study. As previous studies stated 31 , seronegative RA subjects came up with a better prognosis through better response to treatment, a higher sustained drug-free remission (24 vs. 3% in seropositive RA subjects), and a less likely progressive erosive disease (23% vs. 36%). While CRP was markedly higher in Still’s disease, within RA, CRP levels differed substantially between groups; seronegative RA showed higher and more variable values, with a subset of markedly elevated CRP that drives the overall increase compared with seropositive RA. Current tools show limitations for seronegative RA. Although the 2010 ACR/EULAR criteria define RA with a score ≥ 6 32 , their reliance on RF/ACPA reduces specificity in seronegative presentations. In our cohort, some seronegative RA overlapped with SD—particularly in Cluster 3—suggesting potential misclassification. Prior work indicates that, without autoantibodies, seronegative RA must display greater clinical/inflammatory severity to reach the threshold 33 , which may partly explain this overlap. Hence, seronegative RA should remain a diagnosis of exclusion, grounded in careful history, examination, and elimination of mimicking conditions. Moreover, one reason for a potentially more inflammatory profile in seronegative RA compared to seropositive RA could lie in distinct immunopathogenic mechanisms in the synovium. Specifically, analyses indicate that ACPA-negative RA is characterized by a greater number of pro-inflammatory M1-like macrophages which highly express cytokines such as TNF-alpha and IL-6. Furthermore, these macrophages and dendritic cells in seronegative RA show upregulated gene expression of chemokines like CCL13 and CCL18, and the joint-destructive enzyme MMP3. In addition, synovial CD4 + T cells appear more pro-inflammatory with higher TNF-alpha expression, and increased levels of IL-6 may instigate STAT3 signaling in these T cells, all contributing to a more aggressive infiltration of immune cells and a heightened inflammatory state locally and result in higher serum CRP profile in such case 34 . For SD, the Yamaguchi and Fautrel criteria are most used 16 , 17 . Yamaguchi criteria show high sensitivity (96.2%) and specificity (92.1%), whereas Fautrel criteria are more specific (98.5%) but less sensitive (80.6%). In our cohort, only 58% and 53% of SD patients met Fautrel and Yamaguchi criteria, respectively, underscoring their constraints in real-world settings. Although our study was not designed to assess treatment response, the contrast in treatment patterns across clusters likely reflects both phenotype-driven choices and channeling. Cluster 1 displayed a more RA-like presentation with comparatively lower systemic inflammatory burden, consistent with methotrexate as an anchor first-line therapy. In contrast, Cluster 2 concentrated the most systemic and hyperinflammatory—and often more acute—presentations, for which rapid control is clinically prioritized, likely explaining the predominance of systemic corticosteroids, while methotrexate was used less frequently as a slower-onset conventional DMARD. These differences should be interpreted cautiously because of confounding by indication and specialty-driven management (internist-led Still’s disease care versus rheumatology-led RA care). Finally, the higher frequency of drug-free remission observed in Cluster 2 may partly reflect the monocyclic course described in a subset of Still’s disease rather than a treatment effect per se. In current practice, seronegative RA is managed similarly to seropositive RA per SFR recommendations based on EULAR guidelines 33 . However, methotrexate appears less effective in seronegative RA 35 , and bDMARDs show lower efficacy and poorer retention in seronegative than in seropositive disease 36 , 37 . These differences may be partly confounded by care patterns (internists for SD phenotypes vs. rheumatologists for RA phenotypes) and the retrospective design. Nevertheless, IL-1 receptor antagonists and IL-6 receptor inhibitors—effective in both SD and RA—could be considered for overlap phenotypes 38 , 39 . Anti-IL-6 agents are particularly attractive given their established use and suggested benefit in seronegative RA 40 . Our study was not designed to evaluate treatment effectiveness, and treatment patterns likely reflect specialty-specific prescribing habits and disease severity at presentation. Consequently, we cannot draw comparative conclusions regarding response to specific agents. Nevertheless, the identification of a hyper-inflammatory/systemic phenotype overlapping SD features suggests that, in selected presentations, clinicians may consider SD in the differential diagnosis and discuss whether IL-1/IL-6–targeted approaches could be relevant. To our knowledge, this is the first study to compare seronegative and seropositive RA with SD using cluster analysis in a relatively large cohort and with rigorous data collection. While seronegative RA is generally close to seropositive RA, it retains distinctive features. Few studies have specifically examined articular patterns in SD and its overlap with RA 14 . Another strength of this study lies in the substantial number of SD cases, combined with detailed clinical and biological characterization. In addition, the use of k-means clustering represents a robust and innovative statistical approach, enabling a reliable and reproducible phenotypic analysis. Cluster 3 should be interpreted as a mixed hyper-inflammatory phenotype rather than evidence of a new disease entity, acknowledging that this cluster may reflect phenotypic overlap, diagnostic uncertainty at onset, or a shared inflammatory spectrum. Prospective and external validation, including biomarker-driven approaches, will be required before any nosological or therapeutic reclassification can be considered. The retrospective design and differing care pathways in France (rheumatologists for RA vs. internists for SD) may have influenced some findings; we focused on baseline presentation to mitigate this. Missing radiographic data on ankylosing carpal arthritis for a substantial number of patients and frequent absence of ferritin measurements in RA cohorts and partial missing data for glycosylated ferritin in SD and RA cohorts, may have affected analyses. Detailed glucocorticoid dosing, treatment duration, and time-to-remission were inconsistently documented and therefore not suitable for comparative analyses. These gaps reflect practice variability across specialties and underscore the need to harmonize assessment strategies. These observations also suggest the need to harmonize certain assessment strategies across disciplines. Although clustering delineated an SD-enriched phenotype within the overall sample, our analysis cannot determine whether these patients represent misclassified Still’s disease, atypical seronegative RA, or intermediate forms along a shared inflammatory spectrum. This distinction is clinically relevant but cannot be resolved without prospective standardized assessment at onset and longitudinal validation. Therefore, our results should be considered hypothesis-generating rather than practice-changing, and they should not be used to reclassify individual patients. In conclusion, while seronegative RA was overall closer to seropositive RA than to SD, nearly one fifth of seronegative RA patients showed clinically meaningful overlap with SD, reinforcing SD as a key differential diagnosis in highly inflammatory seronegative presentations. Beyond this overlap, our clustering identified a mixed phenotype combining systemic inflammation and atypical articular features, which may reflect a distinct subset within the seronegative inflammatory arthritis spectrum. As a pragmatic, descriptive and hypothesis-generating concept, such cases could be referred to as Systemic Inflammatory RA (SIRA). This entity will require validation through prospective studies, standardized phenotyping and biomarker-driven approaches to confirm its relevance and therapeutic implications. Supplementary Information Below is the link to the electronic supplementary material. Supplementary Material 1 (287KB, pdf) Acknowledgements The authors thank all participating patients. We are grateful to the contributors to the participating registries for case identification and data curation, including Leopold Adelaide, Orlane Chol, Charline Estublier, Marine Gaude, Mathieu Gerfaud-Valentin, Clément Javaux, Jean-Paul Larbre, Pierre-Antoine Neau, and Muriel Piperno. Author contributions Conceptualization: AMG, TE, YJ, FC. Methodology: AMG, TE, YJ, FC. Data acquisition/Investigation: AMG, NE, NF. Data curation: AMG, TE, NE. Formal analysis: AMG, TE. Interpretation of data: AMG, TE, PS, YJ, FC. Writing – original draft: AMG, NE. Writing – review & editing: EM, PS, NF, CC, YJ, FC. Supervision: YJ, FC. Project administration: AMG, FC. All authors approved the submitted version and agree to be personally accountable for their own contributions, and to ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated, resolved, and documented in the literature. Data availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Declarations Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Alexandre Mercier-Guery, Thomas El-Jammal, Yvan Jamilloux and Fabienne Coury contributed equally to this work. References 1. Hayem, F. Is still’s disease an autoinflammatory syndrome? Joint Bone Spine . 76 , 7–9 (2009). [ DOI ] [ PubMed ] [ Google Scholar ] 2. Kim, Y. J., Koo, B. S., Kim, Y. G., Lee, C. K. & Yoo, B. Clinical features and prognosis in 82 patients with adult-onset still’s disease. Clin. Exp. Rheumatol. 32 , 28–33 (2014). [ PubMed ] [ Google Scholar ] 3. Mitrovic, S. & Fautrel, B. 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