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TREATMENT ADHERENCE AND ASSOCIATED FACTORS IN PATIENTS WITH CUTANEOUS LUPUS, A PROSPECTIVE MULTICENTER STUDY

2025· article· en· W4410513112 on OpenAlexvenueno aff
A. Delpuech, Jason Shourick, Serge Boulinguez, Jean‐David Bouaziz, S. Hadj‐Khelifa, C. Paul, François Chasset

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMulticenter studyProspective cohort studySystemic lupus erythematosusLupus erythematosusInternal medicineDermatologyImmunologyDiseaseRandomized controlled trial

Abstract

fetched live from OpenAlex

PV081 / #18 Poster Topic: AS11 - Epidemiology and Public Health Background/Purpose Cutaneous lupus erythematosus (CLE) is an autoimmune disease with a significant impact on quality of life. Many patients with CLE do not improve with conventional treatments. While poor adherence to treatment is well-documented in systemic lupus, data on adherence in CLE is lacking. The aim of this study was to evaluate therapeutic adherence in CLE, and to identify factors associated with poor adherence. Methods This is a prospective, cross-sectional, multicenter study. Patients with CLE completed validated adherence assessment questionnaires (MASRI and MMAS4) at a follow-up visit. According to the MASRI, adherence was defined by a visual analog scale (VAS) greater than or equal to 80%. According to the MMAS4, adherence was defined by a maximum score of 4 out of 4. The CLASI score, which evaluates disease activity (CLASI-A) and damage (CLASI-D), was used to assess the severity of CLE. Quality of life (DLQI), anxiety and depression (HAD), opinion of medication (BMQ), feeling of illness (EVA), and quality of the doctor-patient relationship (CARE and CollaboRATE) were also assessed. Factors associated with adherence (according to MASRI and MMAS4) were assessed by multivariate analysis using logistic regression. Relationships between the different variables were examined using a correlation matrix. Results We included 108 patients with CLE from 3 university hospitals in France. Treatment adherence was 88% according to MASRI and 44.8% according to MMAS4. Younger age (p = 0.0233), presence of discoid lupus (p = 0.0004), disease severity (p = 0.0004) and number of therapy lines (p = 0.0209) were significantly associated with poorer adherence according to MMAS4. A higher number of physicians consulted (r_s = 0.23) and the presence of anxiety and depressive symptoms (r_s = 0.21) were correlated with lower adherence. Severity of cutaneous lupus was correlated with higher anxiety and depressive symptoms (r_s = 0.24) and greater impairment of quality of life (r_s = 0.28). Physician empathy (r_s = 0.26) and shared decision making (r_s = 0.22) were correlated with lower anxiety and depressive symptoms. Conclusions Adherence appears to be significantly impaired in patients CLE. The difference between the 2 adherence scores may be explained by the greater sensitivity of the MMAS4. In our study, there was a significant correlation between the 2 scores (Figure 1). Lower adherence is associated with more severe CLE, both in terms of activity and scarring. It would be interesting to improve the empathic dimension of the doctor-patient relationship and shared decision making, and to assess adherence during follow-up. Figure 1: Distribution of adherence according to the MASRI EVA and the MMAS4.

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)0.004
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.289
Teacher spread0.276 · 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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