Prevention of disease flares by risk-adapted stratification of therapy withdrawal in juvenile idiopathic arthritis: results from the PREVENT-JIA trial

Joachim Gerss, Monika Tedy, Ariane Klein, Gerd Horneff, Maria Miranda-Garcia, Christoph Kessel, Dirk Holzinger, Valda Stanevica, Joost F Swart, David A Cabral, Hermine I Brunner, Dirk Foell (Corresponding Author)

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)
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Abstract

OBJECTIVES: To investigate the ability of high-sensitivity C-reactive protein (hsCRP) and S100A12 to serve as predictive biomarkers of successful drug withdrawal in children with clinical remission of juvenile idiopathic arthritis (JIA).

METHODS: This multicentre trial (PREVENT-JIA) enrolled 119 patients with JIA in clinical remission, and 100 patients reached the intervention phase in which the decision whether to continue or stop treatment was based on S100A12 and hsCRP levels. Patients were monitored for 12 months after stopping medication for flares of disease. Results were compared with withdrawal of therapy without biomarker-based stratification in patients from the German Biologika in der Kinderrheumatologie (BiKeR) pharmacovigilance registry.

RESULTS: In the PREVENT-JIA group, 49 patients had a flare, and 45% of patients stopping medication showed flares within the following 12 months. All patients (n=8) continuing therapy due to permanently elevated S100A12/hsCRP at more than one visit flared during the observation phase. In the BiKeR control group, the total flare rate was 62%, with 60% flaring after stopping medication. The primary outcome, time from therapy withdrawal to first flare (cumulative flare rate after therapy withdrawal), showed a significant difference in favour of the PREVENT-JIA group (p=0.046; HR 0.62, 95% CI 0.38 to 0.99). As additional finding, patients in the PREVENT-JIA trial stopped therapy significantly earlier.

CONCLUSION: Biomarker-guided strategies of therapy withdrawal are feasible in clinical practice. This study demonstrates that using predictive markers of subclinical inflammation is a promising tool in the decision-making process of therapy withdrawal, which translates into direct benefit for patients.

TRIAL REGISTRATION NUMBER: ISRCTN69963079.

Original languageEnglish
Pages (from-to)990-997
Number of pages8
JournalAnnals of the Rheumatic Diseases
Volume81
Issue number7
DOIs
Publication statusPublished - 8 Mar 2022

Keywords*

  • biomarker
  • immunological remission
  • Juvenile idiopathic arthritis (JIA)
  • relapse prevention
  • subclinical inflammation
  • therapy withdrawal

Field of Science*

  • 3.2 Clinical medicine

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database

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