A predictive model for progression to clinical arthritis in at-risk individuals with arthralgia based on lymphocyte subsets and ACPA
Authors' conclusion
We propose a predictive model based on baseline levels of lymphocyte subpopulations and ACPA to identify individuals with arthralgia with the highest risk of progression to clinical arthritis.
Study context
- Population
- At-risk individuals with arthralgias and either ACPA positivity or meeting the EULAR definition for clinically suspect arthralgia153 in predictive models
- Participants
- 207 individuals
- Outcome
- Progression to clinical arthritis
Methodological detailslogistic regression model, classification decision tree, Lymphocyte subsets by flow cytometry; anti-CCP by ELISA
- Logistic regression model
- Classification decision tree
- Lymphocyte subsets by flow cytometry; anti-CCP by ELISA
Performance
As reported in the abstract
Predictors of progression to arthritis
Progressed to arthritis
41
Original publication
A predictive model for progression to clinical arthritis in at-risk individuals with arthralgia based on lymphocyte subsets and ACPA. Rheumatology (Oxford). Published 9 August 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →