INTEGRATING GENETIC RISK SCORES AND TRADITIONAL RISK FACTORS TO PREDICT DEVELOPMENT OF LUPUS NEPHRITIS BASED ON (CSTAR) COHORT
Bibliographic record
Abstract
PT007 / #602 Topic: AS15 - Lupus Nephritis-Clinical POSTER TOUR 02: RECENT INSIGHTS ON THE PATHOGENESIS OF LUPUS NEPHRITIS 23-05-2025 10:00 AM - 10:40 AM Background/Purpose Lupus nephritis (LN) is 1 of the most common and severe manifestations of systemic lupus erythematosus (SLE). However, identifying patients at high risk of LN remains challenging. This multicenter prospective cohort study aimed to evaluate the utility of clinical risk factors and genetic susceptibility for predicting new-onset LN in SLE patients. Methods Based on Chinese SLE treatment and research (CSTAR), SLE patients without LN at SLE diagnosis were consecutively enrolled. Clinical characteristics were recorded, and blood samples were collected for genotyping. The contribution of 112 non-HLA SLE susceptible variants was taken together as a genetic risk score (GRS). Results A total of the 2441 SLE patients without LN at baseline, 215 (8.8 %) developed LN within a mean follow-up of 2.9±1.6 years. Age < 30 years old, absence of arthritis, serositis, hypocomplementemia, and positive anti-dsDNA antibodies emerged as significant predictors of LN. We further enrolled 451 patients and performed genotyping. The 5 traditional risk factors were validated and the utility of GRS in affecting LN development was assessed. The hazard ratio of GRS was 3.19 after adjusting for the 5 clinical risk factors (p=4.36×10^-5). Furthermore, integrating GRS improved the classification of new-onset LN risk compared to compositing traditional risk factors alone (AUC 0.838 vs 0.799). Patients in the clinical low-risk group but with high GRS quartiles showed significantly higher LN probability than those without (18.5% vs 1.9%), similar to that in the clinical high-risk group (29.4%). Conclusions Our study gave further evidence to the role of traditional risk factors, including younger age, serositis, absence of arthritis, hypocomplementemia, and anti-dsDNA antibodies, in new-onset LN risk prediction. The integration of GRS and the 4 clinical risk factors may play a pivotal role in the individualized management of SLE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".