Risk-updating nomogram for refractory systemic juvenile idiopathic arthritis in children: multicentre development and external validation

Clicks: 6
ID: 314910
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #10 of 200 articles by views in Lara D. Veeken

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 200 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Objectives To develop and externally validate a pragmatic prognostic model for identifying children at risk of refractory systemic juvenile idiopathic arthritis (rSJIA) by combining baseline disease activity with early treatment-response information. Methods In a multicentre retrospective cohort of newly diagnosed sJIA, we prespecified baseline predictors (systemic Juvenile Arthritis Disease Activity Score, sJADAS27; refractory rash, rerash) and an early response marker (time to sustained clinical inactive disease, tCID). We developed an update model (sJADAS27 + rerash + tCID) and a baseline-only model (sJADAS27 + rerash + CRP ≥75 mg/l), and assessed discrimination and calibration in training, internal testing, and pooled external validation cohorts. Results Among 128 children (training n = 55; internal testing n = 25; external validation n = 48), 42 (32.8%) met the prespecified composite rSJIA outcome during follow-up. In the update model, sJADAS27 (OR 1.34 per 1-point increase, 95% CI 1.06–1.69) and rerash (OR 7.38, 95% CI 1.07–51.16) were independently associated with rSJIA; tCID showed a positive but non-significant association (OR 1.04 per day, 95% CI 0.99–1.08). The update model showed excellent discrimination in internal testing (AUC 0.919, 95% CI 0.803–1.000) and external validation (AUC 0.907, 95% CI 0.818–0.996). The baseline-only model discriminated well in internal testing (AUC 0.882, 95% CI 0.746–1.000) but less well in external validation (AUC 0.803, 95% CI 0.679–0.926). The update model outperformed sJADAS27 alone in both cohorts (DeLong p= 0.040 and 0.019). Conclusion A nomogram-based approach integrating baseline disease activity with early response information enables risk updating after initial treatment and may support timely treatment individualisation for rSJIA.
Reference Key
openalex_W7162320890 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jianmin Wu, Shuangmei Chen, Xinyi Wei, Minfei Hu, Wenjie Xuan, Wei Zhang, Meiping Lu
Journal Lara D. Veeken
Year 2026
DOI
10.1093/rheumatology/keag272
URL
https://doi.org/10.1093/rheumatology/keag272
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.