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Sex disparities in the phenotype at diagnosis of Sjögren's disease: artificial intelligence-driven characterisation in 17,416 patients

1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45

 

  1. Autoimmune Diseases Unit, Internal Medicine Department, Hospital CIMA Sanitas, Barcelona, Spain.
  2. Postgraduate Degree Program in Artificial Intelligence in Medicine, Department of Medicine, University of Barcelona, Spain.
  3. Division of Clinical Immunology, Faculty of Medicine, University of Debrecen, Hungary.
  4. Department of Internal Medicine and Medical Specialties, Rheumatology Clinic, Sapienza University of Rome; and Saint Camillus International University of Health Science, UniCamillus, Rome, Italy.
  5. Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, the Netherlands.
  6. Division of Rheumatology, Department of Internal Medicine, Hacettepe University, Faculty of Medicine, Ankara, Turkey.
  7. Division of Rheumatology, Department of Medicine, University of Udine, Hospital Santa Maria della Misericordia, ASUFC, Udine, Italy.
  8. Department of Rheumatology, University Medical Centre, Ljubljana, Slovenia.
  9. Division of Rheumatology, Kanazawa University Hospital, Kanazawa, Ishikawa, Japan.
  10. Immunology and Rheumatology Department, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, México City, Mexico.
  11. Rheumatology Department, Hospital de Santa Maria, Unidade Local de Saúde Santa Maria and Faculdade de Medicina, Universidade de Lisboa, Lisbon Academic Medical Centre, Lisbon, Portugal.
  12. Department and Clinic of Rheumatology and Internal Medicine, Wroclaw Medical University, Poland.
  13. Rheumatology Unit, Department of Medicine and Surgery, University of Perugia, Italy.
  14. Department of Rheumatology, The Queen Elizabeth Hospital, Discipline of Medicine, University of Adelaide, South Australia, Australia.
  15. Department of Internal Medicine, Hospital Vall d'Hebron, Barcelona, Spain.
  16. Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina da Universidade de Sao Paulo, Brazil.
  17. Rheumatology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
  18. Systemic Autoimmune Disease Unit, Internal Medicine, University Hospital Virgen de las Nieves, Granada, Spain; MP03-Medicina Interna-HVN Investiga, Instituto de Investigación Biosanitaria ibs, Granada, Spain.
  19. Department of Clinical Medicine, Life, Health and Environmental Sciences, Internal Medicine and Nephrology Division, ASL1 Avezzano-Sulmona-L’Aquila, San Salvatore Hospital, University of L’Aquila, Italy.
  20. Division of Health Based Evidence, Federal University of Sao Paulo, Brazil.
  21. Federal University of Espírito Santo, Brazil.
  22. Department of Rheumatology, Hospital 12 de Octubre, Madrid, Spain.
  23. Department of Internal Medicine, Complexo Hospitalario Universitario de Vigo, Spain.
  24. Department of Internal Medicine, Hospital de Cabueñes, Gijón, Spain.
  25. Autoimmune Diseases Unit, Internal Medicine Department, Hospital CIMA Sanitas, Barcelona; and Postgraduate Degree Program in Artificial Intelligence in Medicine, Department of Medicine, University of Barcelona, Spain.
  26. Division of Haematology and Rheumatology, Department of Medicine, Nihon University School of Medicine, Oyaguchi Kami-cho, Itabashi-ku, Tokyo, Japan.
  27. Department of Internal Medicine, Hospital Joan XXIII, Tarragona, Spain.
  28. Department of Rheumatology, Hospital de Clínicas, San Lorenzo, Paraguay.
  29. Department of Internal Medicine, Hospital Infanta Leonor, Madrid, Spain.
  30. Department of Internal Medicine, Girona Biomedical Research Institute-IDIBGI, Hospital Universitari Doctor Josep Trueta, Girona, Spain.
  31. Department of Internal Medicine, Hospital 12 de Octubre, Madrid, Spain.
  32. Autoimmune Diseases Unit, Internal Medicine Department, Hospital CIMA Sanitas, Barcelona, Spain.
  33. Division of Clinical Immunology, Faculty of Medicine, University of Debrecen, Hungary.
  34. Department of Internal Medicine and Medical Specialties, Rheumatology Clinic, Sapienza University of Rome, Italy.
  35. Department of Oral and Maxillofacial Surgery, University of Groningen, University Medical Center Groningen, The Netherlands.
  36. Division of Rheumatology, Department of Internal Medicine, Hacettepe University, Faculty of Medicine, Ankara, Turkey.
  37. Division of Rheumatology, Department of Medicine, University of Udine, Hospital Santa Maria della Misericordia, ASUFC, Udine, Italy.
  38. Department of Rheumatology, University Medical Centre, Ljubljana; and Department of Internal Medicine, Faculty of Medicine, University of Ljubljana, Slovenia.
  39. Division of Rheumatology, Kanazawa University Hospital, Kanazawa, Ishikawa, Japan.
  40. Rheumatology Department, Hospital de Santa Maria, Unidade Local de Saúde Santa Maria and Faculdade de Medicina, Universidade de Lisboa, Lisbon Academic Medical Centre, Lisbon, Portugal.
  41. Department and Clinic of Rheumatology and Internal Medicine, Wroclaw Medical University, Poland.
  42. Rheumatology Unit, Department of Medicine and Surgery, University of Perugia, Italy.
  43. Department of Rheumatology, The Queen Elizabeth Hospital, Discipline of Medicine, University of Adelaide, South Australia, Australia.
  44. Postgraduate Degree Program in Artificial Intelligence in Medicine, Department of Medicine, University of Barcelona, Spain.
  45. Postgraduate Degree Program in Artificial Intelligence in Medicine, Department of Medicine, University of Barcelona; and Department of Autoimmune Diseases, ICMiD, Hospital Clínic, Barcelona, Spain. mramos@clinic.cat

on behalf of the Sjögren Big Data Consortium

CER19325
2025 Vol.43, N°12
PI 2133, PF 2141
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PMID: 41410590 [PubMed]

Received: 18/09/2025
Accepted : 20/10/2025
In Press: 18/12/2025
Published: 18/12/2025

Abstract

OBJECTIVES:
Sjögren disease (SjD) predominantly affects females, but the early disease presentation in male patients remains poorly characterised due to historically small sample sizes. The aim of this study was to investigate sex‑based differences in the clinical phenotype at diagnosis of SjD and identify predictors of patient sex using a large international cohort and AI‑enhanced analysis.
METHODS:
Cross-sectional analysis of an anonymised dataset comprising 17,416 worldwide patients fulfilling the 2002/2016 classification criteria (Sjögren Big Data Registry). We stratified the dataset by sex and conducted a comparative analysis of baseline glandular and systemic involvement, organ-specific ESSDAI domains, and immunological profiles. Multivariate logistic regression models were developed, adjusting for epidemiological confounders (age and ethnicity) to identify predictors of sex classification. We used a generative AI (OpenAI’s GPT-4o model) environment with Python (version 3.9) and the pandas (1.4.3), numpy (1.21.5), and matplotlib (3.5.1) libraries. All analyses adhered to GDPR standards, with anonymized patient data and strictly controlled secure environments.
RESULTS:
The cohort included 1,161 (6.67%) men and 16,255 (93.33%) women, with a mean age at diagnosis of 51.11 years (SD=14.45). Men showed a higher mean age at diagnosis (54.09 vs. 51.42 years in women; t=6.08, p<0.0001), a higher average ESSDAI score (7.65 vs. 5.93; t=7.91, p<0.0001) and higher frequencies in severe DAS categories (i.e. high activity 20% vs. 12% in women, χ² = 81.15, p<0.0001). The epidemiologically-adjusted logistic regression model (pseudo R-squared value of 0.026) identified statistical significance for age (coefficient =0.009, p=0.024; each additional year in age increased the likelihood of being female by 1.4%), ethnicity (coefficient=0.579, HR=1.78, p=0.004), ocular dryness (coefficient=-0.607, HR=0.54, p<0.001), and systemic activity in the glandular (coefficient=0.359, HR=1.43, p=0.006) and pulmonary (coefficient=0.445, HR=1.56, p=0.004) ESSDAI domains.
CONCLUSIONS:
Male SjD patients present a distinct, more systemic phenotype at diagnosis. Awareness of sex‑specific features can improve early recognition and tailored management.

DOI: https://doi.org/10.55563/clinexprheumatol/m8cq3f

Rheumatology Article