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TIME OF ONSET OF DISCOID LUPUS ERYTHEMATOSUS IMPACTS DISEASE OUTCOMES IN SYSTEMIC LUPUS ERYTHEMATOSUS: A LARGE-SCALE, PROPENSITY-MATCHED RETROSPECTIVE COHORT STUDY

2025· article· en· W4410513270 on OpenAlexvenueno aff
Saloni Patel, Jun Goo Kang

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRetrospective cohort studyPropensity score matchingSystemic diseaseDiscoid lupus erythematosusLupus erythematosusCohortConnective tissue diseaseCohort studySystemic lupus erythematosusImmunologyImmunopathologyDiseaseDermatologyAutoimmune diseaseInternal medicineAntibody

Abstract

fetched live from OpenAlex

PV064 / #310 Poster Topic: AS07 - Cutaneous Lupus Background/Purpose Discoid lupus erythematosus (DLE) is the most common form of chronic cutaneous lupus erythematosus, and up to 25% of patients with systemic lupus erythematosus (SLE) develop DLE lesions during their disease course. Prior research has suggested that the presence of DLE may modify the risk of disease complications, such as lupus nephritis and serositis, in patients with SLE, however, no studies have assessed the impact of time of onset of DLE on SLE outcomes. To address this gap, we investigated the impact of DLE incidence across 3 different time points on long-term disease complications in patients with SLE. Methods We conducted a retrospective cohort study using TriNetX, a Global Collaborative Network that provides access to the deidentified medical records of more than 130 million patients across 95 healthcare organizations worldwide. TriNetX data is derived from ICD10 codes in patient records; L93.0 was used for DLE and M32.1, M32.8, or M32.9 for SLE. Four cohorts were constructed: early-onset DLE (>1 year prior to SLE), concurrent DLE (within 1 year prior to or following SLE), late-onset DLE (>1 year following SLE), and SLE patients who were never diagnosed with DLE. Within each cohort, we included adults who were diagnosed with SLE within the past 10 years and excluded patients with other systemic connective tissue disorders (M30-M31 and M33-M36). Cohorts were propensity-matched at a 1:1 ratio based on demographics, metabolic syndrome, and other chronic conditions, using greedy nearest neighbor matching. The index event was defined as the date of SLE diagnosis and the risk of 5-year incident outcomes following SLE diagnosis was compared between late-onset DLE and either early-onset DLE, concurrent DLE, or SLE without DLE using relative risk (RR) and 95% CI. All statistical analyses were conducted using the R studio package, version 3.2.3, incorporated within TriNetX. Results Following propensity score matching, 4,595 patients were included in the analyses. Across all 3 analyses, patients with late-onset DLE had increased risk of malignant neoplasms (RR 1.42 [1.06,1.90] compared to early-onset DLE, RR 1.48 [1.09,2.01] compared to concurrent DLE, and RR 2.43 [1.69,3.49] compared to SLE without DLE). In the analysis comparing early-onset to late-onset DLE, the largest number of significant differences in 5-year incident outcomes was observed. SLE patients with late-onset DLE patients had a higher RR of chronic kidney disease (RR 1.49 [1.02,2.18]), major adverse cardiovascular events (RR 1.61 [1.16,2.21]), bacterial and viral infections (RR 1.60 [1.19,2.16]), and hospitalizations (RR 1.30 [1.03,1.63]). Compared to SLE patients without DLE, patients with late-onset DLE had increased risk of UTI (RR 1.53 [1.08,2.17]) and arthritis (RR 1.39 [1.16,1.66]). In the analysis comparing SLE patients with concurrent DLE to SLE patients with late-onset DLE, the latter had increased risk of hematuria, but patients with concurrent DLE diagnosis had increased risk of mortality (RR 1.98 [1.32,2.97]) and hospitalization (RR 1.24 [1.04,1.48]). Conclusions Our findings suggest that the timing of DLE onset relative to SLE diagnosis has a substantial impact on long-term disease outcomes following SLE diagnosis. Late-onset DLE was associated with a notably higher risk of serious complications, particularly when compared to early-onset DLE. This risk stratification based on DLE onset timing highlights the importance of monitoring SLE patients for DLE development, particularly in the later stages of disease, and distinct DLE endotypes to enable earlier intervention and potentially mitigate adverse outcomes.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.294
Teacher spread0.281 · 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
Has abstractyes

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