Can biomarkers predict successful tapering of conventional disease-modifying therapy in rheumatoid arthritis patients in stable remission?
Clin Exp Rheumatol
; 41(1): 126-136, 2023 Jan.
Article
em En
| MEDLINE
| ID: mdl-35699062
ABSTRACT
OBJECTIVES:
Specific guidelines for managing RA patients in clinical remission for ≥6 months on cs-DMARDs are lacking. Tapering of treatment is encouraged, however, without validated biomarkers for success. We aimed to assess the rate of sustained remission after 12 months in patients who either (i) followed structured cs-DMARD tapering or (ii) continued therapy, focusing on the added value of biomarkers as predictors of outcome.METHODS:
RA patients fulfilling 3v-DAS28CRP<2.6 for ≥6 months on stable cs-DMARD therapy were included. Patients were offered structured tapering, with 117 accepting tapering and 83 continuing therapy. Clinical, ultrasound, immunological (T-cell subsets) and patient-reported outcome (PRO) data were collected. The primary endpoint was the proportion of patients in sustained remission without relapse after 12 months. Regression analyses were used to identify predictors of sustained remission.RESULTS:
Of those who tapered, 64% remained in clinical remission after 12 months compared with 80% (p=0.018) of patients on stable treatment. In the tapering group, higher levels of CRP, TJC, % inflammation-related T-cell (IRC) and PROs were associated with flare (all p<0.05), with a trend for total PD (p=0.066). A model predicting sustained remission retained RAQoL, total PD and IRC (85% accuracy, AUROC=0.893, p<0.0001). In the non-tapering group, higher CRP, ESR, SJC and shorter disease duration (all p<0.05) were associated with flare, with no parameter able to predict sustained remission.CONCLUSIONS:
In the tapering group, the combination of clinical, PRO, US and T-cell parameters demonstrated added value for predicting sustained remission compared with clinical parameters alone. These data may inform best tapering practice.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article