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IMMUNOSUPPRESSANTS AND LUPUS-RELATED DAMAGE: A PROPENSITY SCORE ANALYSIS OF THE BIRMINGHAM LUPUS COHORT

2025· article· en· W4410512915 on OpenAlexvenueno aff
Ahmed Saleh, Caroline Gordon, John P. Reynolds

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusCohortPropensity score matchingCohort studyLupus erythematosusInternal medicineImmunologyDiseaseAntibody

Abstract

fetched live from OpenAlex

PV272 / #675 Poster Topic: AS24 - SLE-Treatment Background/Purpose Non-corticosteroid immunosuppressants as azathioprine (AZA), mycophenolate mofetil (MMF), cyclophosphamide (CYC), calcineurin inhibitors (CNIs) and methotrexate (MTX) are widely used in the treatment of SLE. However, their effectiveness in preventing organ damage remains unclear as observational studies are subject to confounding by indication (where patients with more severe disease are more likely to receive these medications). This study aimed to identify the relationship between the use of immunosuppressive medications and the development of organ damage in SLE patients. Methods The Birmingham Lupus Cohort is a longitudinal observational cohort of patients with SLE. All patients fulfilled the 1997 ACR Updated Classification Criteria for SLE. At each medical consultation, the disease activity was assessed using the classic BILAG index (or BILAG-2004), and damage was evaluated using the SLICC/ACR damage index (SDI). In addition, serological test results, and treatment plans, including any change in the management plan, were recorded. Propensity scores were estimated for the likelihood of receiving each immunosuppressive medication based on covariates including age, gender, ethnicity, year of diagnosis, year of enrollment, disease duration, smoking, antimalarial use, immunosuppressive use, and baseline SDI. For the treatment group, the baseline was the first exposure to the index medication, while for the control group, baseline was the first date with a disease activity score of A or B in any domain of the BILAG index. Multivariable Cox Proportional Hazard models were developed to study the effect of each immunosuppressive medication on organ damage in SLE patients over 10 years of follow-up, adjusted for propensity score, disease activity, and corticosteroid use. Results We included 361 SLE patients of whom 334 (92.5%) were female. There were 214 (59.2%) White, 66 (18.2%) African or Caribbean, 69 (19.1%) South Asian, 8 (2.2%) East Asian patients, and 16 (4.4%) from other ethnic backgrounds. The median (IQR) age at enrollment was 34 (26 - 45) years. The frequencies of patients who were ever treated with non-corticosteroids-immunosuppressive drugs were as follows: AZA (49.8%), MMF (30.7%), CNI (16.3%), MTX (22.9%), and CYC (25%). After 10 years of follow-up, a total of 166 (45.9%) had 1 or more items of organ damage. In separate multivariable Cox Proportional Hazard models with the development of a new item of damage as the dependent variable, after adjusting for propensity scores, use of corticosteroids, and disease activity. There was an inverse association between the development of organ damage and the use of AZA (hazard ratio [HR] 0.59 [95% CI: 0.44, 0.79]), MMF (HR 0.41 [95% CI: 0.27, 0.62]), CNI (HR 0.34 [95% CI: 0.19, 0.60]), and MTX (HR 0.49 [95% CI: 0.30, 0.78]), suggesting a protective effect. However, the use of CYC (HR 1.12 [95% CI: 0.62, 2.04]) was not found to be protective against further organ damage (Table 1). The multivariable Cox models prior to propensity adjustment are summarized in Table 1. Table 1: Multivariate analysis of immunosuppressive medications and the presence of organ damage, pre and post propensity adjustment Conclusions AZA, MMF, CNI, and MTX may have protective effect against the development of organ damage. Treatment with CYC was not associated with new organ damage although further residual confounding cannot be excluded.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.288
Teacher spread0.268 · 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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