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      Propensity Score Methods in Rare Disease: A Demonstration Using Observational Data in Systemic Lupus Erythematosus.

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          Abstract

          Observational studies allow researchers to understand the natural history of rheumatic conditions, risk factors for disease development, and factors affecting important disease-related outcomes, and to estimate treatment effect from real-world data. However, this design carries a risk of confounding bias. A propensity score (PS) is a balancing score that aims to minimize the difference between study groups and consequently potential confounding effects. The score can be applied in 1 of 4 methods in observational research: matching, stratification, adjustment, and inverse probability weighting. Systemic lupus erythematosus (SLE) is a rare disease characterized by a relatively small sample size and/or low event rates. In this article, we review the PS methods. We demonstrate application of the PS methods to achieve study group balance in a rare disease using an example of risk of infection in SLE patients with hypogammaglobulinemia.

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          Author and article information

          Journal
          J Rheumatol
          The Journal of rheumatology
          The Journal of Rheumatology
          0315-162X
          0315-162X
          March 2021
          : 48
          : 3
          Affiliations
          [1 ] I. Almaghlouth, MBBS, MSc, Division of Rheumatology, Department of Medicine, University of Toronto, Ontario, Canada, and Rheumatology Unit, Department of Medicine, and College of Medicine Research Center, King Saud University, Saudi Arabia.
          [2 ] E. Pullenayegum, PhD, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, and Program in Child Health Evaluative Sciences, SickKids Research Institute, Toronto, Ontario, Canada.
          [3 ] D.D. Gladman, MD, FRCPC, M.B. Urowitz, MD, FRCPC, Division of Rheumatology, Department of Medicine, University of Toronto, and Centre for Prognosis in Rheumatic Diseases, University Health Network, and The Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.
          [4 ] S.R. Johnson, MD, PhD, Division of Rheumatology, Department of Medicine, and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada. Sindhu.Johnson@uhn.ca.
          Article
          jrheum.200254
          10.3899/jrheum.200254
          32611674
          a949b5d4-5a81-4d46-977b-1601bf719434
          History

          balancing score,observational,propensity score,selection bias

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