A EULAR/ACR (2019) SLE CLASSIFICATION CRITERIA SCORE ≥20 IS A MARKER OF SEVERE DISEASE IN A PREVALENT SLE COHORT FROM THE PORTUGUESE REUMA.PT REGISTRY
Bibliographic record
Abstract
PV214 / #533 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose Recently, a EULAR/ACR 2019 systemic lupus erythematosus (SLE) classification criteria (EULAR/ACR 2019) score≥20 was identified in a SLE inception cohort with less than 2 years from diagnosis as a marker for more severe disease, including higher disease activity, more frequent flares, higher use of immunosuppressants, lower probability of achieving remission, and more damage accrual. However, this analysis has not been performed in SLE patients with longer disease duration.[1] The aim of our study was to assess a EULAR/ACR 2019 score ≥20 as a marker for severe disease in a prevalent SLE cohort. Methods We performed a cross-sectional multicenter study of patients fulfilling the EULAR/ACR 2019 classification criteria for SLE in the Portuguese registry of rheumatic diseases (Reuma.pt). Disease activity (SLE-DAS) and the EULAR/ACR score were assessed at the last visit, between June 2023 and March 2024. Groups of patients with EULAR/ACR 2019 score ≥20 or <20 were compared for demographic, clinical and treatment features, with parametric and non-parametric tests, as appropriate. Separate models were tested using different definitions of severe SLE (dependent variable), as present/absent: (1) cumulative SLE major organ involvement; (2) moderate/severe disease activity, defined as SLE-DAS>7.64; (3) ongoing immunosuppressants; (4) ongoing systemic prednisolone>7.5 mg/day; (5) organ damage, defined as SLICC/ACR Damage Index (SDI) ≥ 1. Predictors for each of these definitions were assessed in a 2-step approach with logistic regression (LR) univariate analysis, followed by multivariate LR models including variables with p<0.10 in the first step, while excluding variables with multicollinearity. Multivariate analysis was used to identify independent predictors and estimate the respective adjusted odds ratios (OR) with 95% confidence intervals. Results There were 2459 patients registered in Reuma.pt, from 37 participating centers. A total of 709 patients, from 18 centers, who had data on and fulfilled the EULAR/ACR 2019 classification criteria and had a SLE-DAS scoring were included, 65.6% having an EULAR/ACR 2019 score≥20. These patients were younger at diagnosis (p<0.001), had longer disease duration (p<0.001), higher SLE-DAS score (p=0.001), received less frequently antimalarials (p=0.004), and were more frequently treated with synthetic and/or biologic immunosuppressants (p<0.001) and glucocorticoids (p<0.001). On univariate LR analysis, a EULAR/ACR 2019 score≥20 was associated with all definitions of severe disease (Table 1). On multivariate LR analysis, a EULAR/ACR 2019 score≥20 was an independent predictor of cumulative major organ involvement (OR 7.30, 95% CI 4.86-10.95, p<0.001), moderate/severe disease activity (OR 7.36, 95% CI 2.18-24.82, p=0.001), ongoing immunosuppressants (OR 2.73, 95% CI 1.82-4.09, p<0.001), and ongoing systemic prednisolone>7.5 mg/day (OR 2.71, 95% CI 1.29-5.69, p=0.009), adjusted for significant covariates. In the multivariate LR, a EULAR/ACR score≥20 was not associated with organ damage, defined as SDI≥1. Table 1 Univariate and multivariate logistic regression analysis for severe SLE Conclusions A EULAR/ACR 2019 score ≥20 is associated with severe disease in a prevalent SLE cohort. Although this is not surprising, given the similarity and close relationship between items included in all instruments, this score may, in association with measures of disease activity, contribute to management in clinical practice, stratification of cases in observational studies and selection of patients for clinical trials. References: [1.] Whittall-Garcia LP. Ann Rheum Dis. 2021;80(6):767-74. * Carolina Mazeda and Beatriz Mendes contributed equally and share first authorship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".