BELIMUMAB REDUCES THE RISK OF FLARES ASSOCIATED WITH THE BAFF OVEREXPRESSING TNFSF13B GENE VARIANT: A HINT FOR PERSONALIZED TREATMENT IN SLE.
Bibliographic record
Abstract
PV183 / #357 Poster Topic: AS20 - Precision Medicine Background/Purpose The TNFSF13B gene functional variant (BAFFvar) is an insertion-deletion (GCTGT→A) introducing an alternative polyadenylation motif generating a truncated/shorter gene transcript that escapes miRNA inhibition, yielding increased production of soluble BAFF.[1] The consequent overexpression of BAFF, in turn, up-regulates humoral immunity, increases the production of autoantibodies, and increases the risk of developing SLE. The present study investigates if Baffvar status influences the risk of overall and renal SLE flares and whether patients stratified according to Baffvar status might show a differential benefit from anti-BAFF treatment. Methods This study used data from patients included in a monocentric SLE inception cohort between 1 January 2006 and 31 December 2022. Inclusion criteria were: (a) SLE classified according to the ACR/EULAR 2019 and/or SLICC 2012 and/or ACR 1997 criteria; (b) evaluation in at least 3 consecutive visits (not less than 2 visits every 12 months); (c) genotyping for BAFFvar. Demographic, clinical, serologic, and treatment variables were recorded. Flare was defined as the onset of a new SLE manifestation or worsening of a preexisting clinical manifestation resulting in a therapy change. Renal flares were nephritic (≥10 RBCs/hpf with or without a decrease in eGFR by ≥10%, irrespective of changes in proteinuria) or nephrotic (doubling of proteinuria to >1g/24h or to >2g/24h depending on the previous complete or partial response). Kaplan-Meier curves were used to analyze the association between BAFFvar and overall or renal SLE flares. Multivariate Cox regression models were built, including demographic, clinical, and serologic data and past or ongoing treatment as covariates. Results 194 (89.2% female) out of 256 screened patients were analyzed (Table 1). The mean age was 41.1 (± 14.8) years, the mean number of follow-up visits was 17 (± 8) and 119 (61.3%) were BAFFvar carriers. During follow-up, 119 patients (56.2%) experienced at least 1 flare, with 60 patients (30.9%) having more than 1 flare. The median number of flares was higher (p=0.038) in Baffvar carriers (1; IQR 0-2) than in BAFF-wt carriers (0; IQR 0-1). Cox regression model showed BAFFvar (HR 1.5 per copy variant; 95% CI 1.2 - 2.0; p = 0.002), disease duration <1 year (HR 0.46; 95% CI 0.30 – 0.71; p<0.001), DORIS remission (HR 0.41; 95% CI 0.24 – 0.71; p = 0.001), renal (HR 1.7; 95% CI 1.1 – 2.6; p = 0.017), and musculoskeletal (HR 5.3; 95% CI 1.3 – 21.5; 0.019) involvement as baseline factors independently associated with the risk of flare development. Out of 38 patients with biopsy-confirmed LN, 33 (86.8%) were female, 21 (55.3%) were BAFFvar carriers, and 24 (63.2%) were diagnosed with proliferative lupus nephritis class III or IV. Flares occurred in 12 (33.3%) patients, with 22 flares (5 nephritic and 17 nephrotic). The BAFFvar was independently associated with the risk of renal flare (HR 9.3; 95% CI 1.8 to 49.5; p=0.008). Out of 35 patients treated with belimumab after a flare, 9 had at least 1 flare during a median 48-month follow-up (total of 11 flares). Patients with BAFFvar had a flare rate of 13.6% (3/22), while BAFFwt carriers had a flare rate of 46.1% (6/13) (HR 0.22; 95% CI 0.05-0.90; p=0.035). Table 1. Baseline characteristics of the lupus cohort at entry into the study. Conclusions Belimumab reduces the risk of overall and renal SLE flares conferred by the BAFFvar. BAFFvar identifies patients at higher risk for flare and those best responders to belimumab and may represent a potential predicting and prognostic biomarker for personalized treatment in SLE patients. References: [1.] Steri M. NEJM 2017;376:1615-26.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".