DIFFERENT PHENOTYPES OF SEVERE FLARES IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS (SLE): RESULTS OF A CLUSTERING ANALYSIS IN A MONOCENTRIC COHORT.
Bibliographic record
Abstract
PV222 / #475 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose to identify and compare different phenotypes of severe flares in a monocentric cohort of SLE patients. Methods This is a retrospective study of prospectively collected data from a monocentric cohort of adult SLE patients (2019 EULAR-ACR classification criteria), hospitalized in the last 5 years, due to a severe flare (SELENA-SLEDAI flare index definition). Patients with concomitant infections, oncologic and onco-hematologic conditions were excluded. Hospitalization was defined as baseline (t0). At t0 demographics, clinical, laboratory and treatment data were collected. Disease activity was assessed with SLEDAI-2K and BILAG-2004. Disease outcomes (Lupus Low Disease Activity State (LLDAS) and DORIS remission) and treatment were evaluated at 3, 6, 12-months (t3, t6, t12) after the flare. Organ damage (SLICC Damage Index (SLICC-DI)) was assessed at baseline and t12. A clustering analysis was performed on SLE flares, with a hierarchical method. Post hoc elaborations (1-way analysis of variance with Bonferroni test for quantitative variables, and Chi-square test for qualitative variables) were performed to estimate any statistically significant differences between the clusters. Results 122 severe flares in 110 patients (female 83%, Caucasian 89%) were included. 3 clusters were identified, composed of 40, 34 and 48 flares respectively. Cluster 1 included flares that occurred in younger patients (mean age 38.2±12 vs 46.3±13.9 and 43.2±11.1 in clusters 2 and 3 respectively; p=0.007) with a shorter disease duration (9.1±6 years vs 17.5±11.5 and 15±8.7; p=0.0001), characterized by a higher frequency of BILAG A manifestations in the constitutional, cardiopulmonary and musculoskeletal domains (p= 0.0001). These flares presented hyperinflammatory stigmata (higher C-reactive protein, more severe lymphopenia, a tendency for higher ferritin values) and a richer autoantibody profile (anti-dsDNA, anti-Smith, anti-nucleosome, anti-hystone), compared to the other clusters. Cluster 2 included less severe flares with more BILAG B scores (59% vs 28% and 19%; p=0.0001) and mainly joint and skin manifestations. Cluster 3 was characterized by a clear predominance of renal flares (96%) (p=0.0001). 85% of flares in each cluster required adding/changing the immunsuppressant, mainly Mycophenolate in c lusters 1 and 3 (30% and 47% vs 9%; p=0.001). Glucocorticoid pulses were less frequently used in c luster 2 , accordingly to a milder flare phenotype (15% vs 50% and 83%; p= 0.0001). Belimumab was added in 25% and 30% of flares in cl uster 1 and 2 respectively, only in 8.5% in c luster 3 (p=0.02), as the majority of flares occurred before the approval of Belimumab for lupus nephritis. At t6 and t12, flares in clusters 1 and 3 presented a significantly higher cumulative glucocorticoid dose, compared to cluster 2 . At the different timepoints, c luster 1 and 3 presented a comparable and quite low percentage of patients that achieved LLDAS and remission (Table 1). No differences emerged among the clusters for SLICC-DI at t12. Table 1. *Cluster 2 vs 1 and 3 Conclusions different phenotypes of severe SLE flares exist. We identified a “hyperinflammatory” phenotype presenting with fever, arthritis and serositis, deserving similar aggressive therapeutic strategies as renal flares and burdened by a comparable proportion of unsatisfying response to treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".