Data‐Driven Patient Clustering and Differential Clinical Outcomes in the Brigham and Women’s Rheumatoid Arthritis Sequential Study Registry

OBJECTIVE: To use unbiased, data‐driven, principal component (PC) and cluster analysis to identify patient phenotypes of rheumatoid arthritis (RA) that might exhibit distinct trajectories of disease progression, response to treatment, and risk for adverse events. METHODS: Patient demographic, socioe...

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Detalles Bibliográficos
Autores principales: Curtis, Jeffrey R., Weinblatt, Michael, Saag, Kenneth, Bykerk, Vivian P., Furst, Daniel E., Fiore, Stefano, St John, Gregory, Kimura, Toshio, Zheng, Shen, Bingham, Clifton O., Wright, Grace, Bergman, Martin, Nola, Kamala, Charles‐Schoeman, Christina, Shadick, Nancy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Rheumatoid Arthritis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048846/
https://www.ncbi.nlm.nih.gov/pubmed/33002337
http://dx.doi.org/10.1002/acr.24471

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048846/
https://www.ncbi.nlm.nih.gov/pubmed/33002337
http://dx.doi.org/10.1002/acr.24471

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