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The bm12 Inducible Model of Systemic Lupus Erythematosus SLE in C57BL/6 Mice
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Lupus Cohorts.

Christopher Redmond1, Omer Pamuk1, Sarfaraz A Hasni1

  • 1National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA.

Rheumatic Diseases Clinics of North America
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PubMed
Summary
This summary is machine-generated.

Real-world data from diverse systemic lupus erythematosus (SLE) cohorts inform treatment safety and efficacy. Social media can rapidly expand patient outreach for studying this rare autoimmune disease.

Keywords:
CohortDatabaseLupusRegistry

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Area of Science:

  • Rheumatology and Immunology
  • Clinical Research Methodologies

Background:

  • Systemic lupus erythematosus (SLE) research benefits from large, diverse patient cohorts.
  • Established lupus cohorts have significantly advanced understanding of SLE.
  • Real-world data are crucial for evaluating treatment safety and efficacy.

Purpose of the Study:

  • To highlight the value of diverse patient cohorts in SLE research.
  • To explore the potential of social media in augmenting cohort-based studies for rare diseases like SLE.
  • To discuss the advantages and limitations of cohort studies in SLE.

Main Methods:

  • Analysis of existing literature on SLE cohorts.
  • Discussion of data collection strategies in real-world settings.
  • Evaluation of social media's role in patient recruitment and data gathering.

Main Results:

  • Large cohorts with varied ethnic backgrounds and clinical features provide essential real-world data on SLE treatments.
  • Social media platforms offer a rapid method to increase patient recruitment for rare disease studies.
  • Cohort studies, while valuable, may face challenges like selection bias and incomplete data.

Conclusions:

  • Diverse, real-world data from SLE cohorts are vital for understanding disease and treatment.
  • Innovative approaches like social media can enhance the reach and efficiency of rare disease research.
  • Careful consideration of potential biases is necessary for robust long-term cohort studies.