OBJECTIVE: Optimizing therapeutic strategies to induce remission requires an understanding of the initial features predicting remission. Currently no suitable model exists. We aim to develop a remission score using predictors of remission in early rheumatoid arthritis (RA). METHODS: We used a dataset from a UK randomized controlled trial that evaluated intensive treatment with conventional combination therapy, to develop a predictive model for 24-month remission. We studied 378 patients in the trial who received 24 months' treatment. Our model was validated using data from a UK observational cohort (Early RA Network, ERAN). A group of 194 patients was followed for 24 months. Remission was defined as 28-joint Disease Activity Score < 2.6. Logistic regression models were used to estimate the associations between remission and potential baseline predictors. RESULTS: Multivariate logistic regression analyses showed age, sex, and tender joint count (TJC) were independently associated with 24-month remission. The multivariate remission score developed using the trial data correctly classified 80% of patients. These findings were replicated using ERAN. The remission score has high specificity (98%) but low sensitivity (13%). Combining data from the trial and ERAN, we also developed a simplified remission score that showed that younger men with a TJC of 5 or lower were most likely to achieve 24-month remission. Remission was least likely in older women with high TJC. Rheumatoid factor, rheumatoid nodules, and radiographic damage did not predict remission. CONCLUSION:Remission can be predicted using a score based on age, sex, and TJC. The score is relevant in clinical trial and routine practice settings.
RCT Entities:
OBJECTIVE: Optimizing therapeutic strategies to induce remission requires an understanding of the initial features predicting remission. Currently no suitable model exists. We aim to develop a remission score using predictors of remission in early rheumatoid arthritis (RA). METHODS: We used a dataset from a UK randomized controlled trial that evaluated intensive treatment with conventional combination therapy, to develop a predictive model for 24-month remission. We studied 378 patients in the trial who received 24 months' treatment. Our model was validated using data from a UK observational cohort (Early RA Network, ERAN). A group of 194 patients was followed for 24 months. Remission was defined as 28-joint Disease Activity Score < 2.6. Logistic regression models were used to estimate the associations between remission and potential baseline predictors. RESULTS: Multivariate logistic regression analyses showed age, sex, and tender joint count (TJC) were independently associated with 24-month remission. The multivariate remission score developed using the trial data correctly classified 80% of patients. These findings were replicated using ERAN. The remission score has high specificity (98%) but low sensitivity (13%). Combining data from the trial and ERAN, we also developed a simplified remission score that showed that younger men with a TJC of 5 or lower were most likely to achieve 24-month remission. Remission was least likely in older women with high TJC. Rheumatoid factor, rheumatoid nodules, and radiographic damage did not predict remission. CONCLUSION: Remission can be predicted using a score based on age, sex, and TJC. The score is relevant in clinical trial and routine practice settings.
Authors: Rocio V Gamboa-Cárdenas; Manuel F Ugarte-Gil; Massardo Loreto; Mónica P Sacnun; Verónica Saurit; Mario H Cardiel; Enrique R Soriano; Cecilia Pisoni; Claudio M Galarza-Maldonado; Carlos Rios; Sebastião C Radominski; Geraldo da R Castelar-Pinheiro; Washington Alves Bianchi; Simone Appenzeller; Inés Guimarães da Silveira; Cristiano A de Freitas Zerbini; Carlo V Caballero-Uribe; Adriana Rojas-Villarraga; Marlene Guibert-Toledano; Francisco Ballesteros; Rubén Montufar; Janitzia Vázquez-Mellado; Jorge Esquivel-Valerio; Ignacio García De La Torre; Leonor A Barile-Fabris; Fedra Irazoque Palezuelos; Lilia Andrade-Ortega; Pablo Monge; Raquel Teijeiro; Ángel F Achurra-Castillo; María H Esteva Spinetti; Graciela S Alarcón; Bernardo A Pons-Estel Journal: Clin Rheumatol Date: 2019-06-03 Impact factor: 2.980
Authors: Jeffrey R Curtis; Theresa McVie; Ted R Mikuls; Richard J Reynolds; Iris Navarro-Millán; James O'Dell; Larry W Moreland; S Louis Bridges; Veena K Ranganath; Stacey S Cofield Journal: J Rheumatol Date: 2013-04-15 Impact factor: 4.666
Authors: Carlo A Scirè; Mark Lunt; Tarnya Marshall; Deborah P M Symmons; Suzanne M M Verstappen Journal: Ann Rheum Dis Date: 2013-06-07 Impact factor: 19.103
Authors: Seth D Seegobin; Margaret H Y Ma; Chanaka Dahanayake; Andrew P Cope; David L Scott; Cathryn M Lewis; Ian C Scott Journal: Arthritis Res Ther Date: 2014-01-16 Impact factor: 5.156