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COMPLEMENTARY LUPUS-SPECIFIC INDEXES INFORMED BY SELECT IMMUNE MEDIATORS CHARACTERIZE RISK OF CONCURRENT DISEASE ACTIVITY AND FUTURE IMPENDING FLARE IN SYSTEMIC LUPUS ERYTHEMATOSUS

2025· article· en· W4410715670 on OpenAlexvenueno aff
Melissa E. Munroe, Daniele C. DeFreese, Adrian Holloway, Bernard Rubin, Mohan Purushothaman, Wade DeJager, Susan Macwana, Joel M. Guthridge, Stan Kamp, Nancy Redinger, Teresa Aberle, Eliza Chakravarty, Cristina Arriens, Yanfeng Li, Hu Zeng, Uma Thanarajasingam, Judith James, Eldon R. Jupe

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusImmunologyImmune systemLupus erythematosusImmunopathologySystemic diseaseFlareConnective tissue diseaseDiseaseAutoimmune diseaseAntibodyInternal medicine

Abstract

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PT002 / #417 Topic: AS09 - Emerging Approaches in SLE Management POSTER TOUR 01: CLINICAL OUTCOMES IN SLE 22-05-2025 10:00 AM - 10:40 AM Background/Purpose Systemic lupus erythematosus (SLE) is driven by immune dysregulation, with increased risk for heightened clinical disease activity and flare that lead to permanent end-organ damage, morbidity, and early mortality. Capturing immune dysregulation as lab-based screening tests would help prioritize SLE patients for early intervention. This study assesses the utility of employing a Lupus Flare Risk Index (L-FRI) and Lupus Disease Activity Index (L-DAI) in parallel to assess simultaneous risk of future disease flare and concurrent disease activity to guide therapy. Methods We assessed levels of 17 SLE-associated plasma mediators to calculate L-FRI and L-DAI scores in 80 preflare vs 76 prenonflare visits, as well as 49 flare vs 51 nonflare follow-up visits with available samples, from a unique cohort of prospectively followed SLE patients. Hybrid SLEDAI (hSLEDAI) scores, clinical features, medication usage, and the presence of SLE-associated autoantibody specificities, including dsDNA, chromatin, Ro/SSA, La/SSB, Sm, SmRNP, and RNP, were also compared. The L-FRI algorithm reflects the sum of 11 log-transformed, standardized immune mediators, weighted by the Spearman r correlation coefficient for each preflare (PF)/pre-nonflare (PNF) analyte vs subsequent hSLEDAI scores at the time of future flare/nonflare.[1,2] The L-DAI algorithm reflects the sum of 10 log-transformed, standardized immune mediators, weighted by the Spearman r correlation coefficient of each active (hSLEDAI ≥4)/low (hSLEDAI<4) disease activity analyte vs the composite of concurrent hSLEDAI scores and number of SLE-associated autoantibody specificities.[3] Results Forty of 80 (50%) preflare vs 24 of 76 (32%) pre-nonflare visits were associated with concurrent active disease (hSLEDAI≥4; p=0.0230). The L-FRI differentiated preflare vs pre-nonflare visits and subsequent flare vs nonflare visits, irrespective of disease activity state (Figure 1A), with severe flare visits present above the high-risk cut-off (decision curve analysis, [1,2]). The L-DAI differentiated concurrent active vs low (hSLEDAI<4) disease activity, irrespective of preflare/pre-nonflare or flare/nonflare status (Figure 1B), with renal manifestations present above the high-risk cut-off (decision curve analysis, [3]). All SLE groups had significantly higher L-FRI and L-DAI scores than demographically matched healthy Ctrl (n=71, p<0.0001, Figure 1A,B). Plasma levels of BLyS (L-FRI, L-DAI), as well as L-FRI informing mediators MCP-3, TNFRI, and TNFRII were highest in preflare visits with concurrent active disease (p<0.05), while IL-17A levels were highest in preflare visits with concurrent low disease activity (p<0.05), Figure 1C. IL-7 (L-FRI, L-DAI) levels were increased with both flare and disease activity risk (p<0.05), while L-DAI informing mediators IFN-α and IP-10 were highest in active disease, with preflare increased over pre-nonflare levels (p<0.05), Figure 1C. Of interest, although the L-FRI and L-DAI performed well at assessing flare and disease activity risk, respectively (AUC>0.9), parallel assessment of L-FRI and L-DAI performed better than either alone to identify simultaneous risk of concurrent active disease and imminent flare risk, Table 1. Figure 1. Using Lupus Flare Risk Index (L-FRI, A) and Lupus Disease Activity Index (L-DAI, B) to evaluate combination of impending flare and concurrent disease activity risk. Select L-FRI and L-DAI informing mediators reflect flare and/or disease activity rsk (C) PF-Preflare; PNF=PreNonflare; Active (hSLEDAI≥4); Low (hSLEDAI<4); *p<0.05; **p<0.01, ****p<0.0001 by Kruskal-Wallis test with Dunn’s multiple comparison. Table 1. Combination of L-FRI and L-DAI Tests Optimally Informs Future Flare and Concurrent Disease Activity Risk Conclusions The L-FRI used with the L-DAI optimally identified risk of imminent lupus disease flare and concurrent active disease, including severe flare and renal manifestations. A subset of mediators consistently enhanced the L-FRI and L-DAI tests to identify SLE patients who may benefit from early intervention strategies. Such an approach would improve disease management and be advantageous in prospective clinical trials for study participant recruitment and assessment. References: [1.] Munroe M. Arthritis Rheumatol 2023;75:723-5. [2.] Munroe M. Annal Rheum Dis 2024;83:402-3. [3.] Munroe M. Annal Rheum Dis 2024;83:19-20.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.281
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
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