Evidence map›Paper›PMID 40210260›Full record

ArticleRMD open2025

Prognostic insights from symptom clustering analysis in systemic lupus erythematosus.

Erwan Le Tallec, Corentin Bourg, Guillaume Bouzillé, Nicolas Belhomme, Estelle Le Pabic, Stéphanie Guillot, Catherine Droitcourt, Antoinette Perlat, Stéphane Jouneau, Vincent Sobanski and 2 more

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Article in RMD open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Erwan Le TallecDepartment of Internal Medicine and Clinical Immunology, CHU de Rennes, Rennes, France erwan.le.tallec@chu-rennes.fr.ORCID 0009-0002-5768-3159
Corentin BourgDepartment of Cardiology, CHU de Rennes, Rennes, Bretagne, France.
Guillaume BouzilléINSERM, LTSI UMR 1099, CHU de Rennes, Rennes, Bretagne, France.
Nicolas BelhommeDepartment of Internal Medicine and Clinical Immunology, CHU de Rennes, Rennes, France.ORCID 0000-0002-9438-3350
Estelle Le PabicINSERM, CIC UMR 1414, CHU de Rennes, Rennes, Bretagne, France.
Stéphanie GuillotDepartment of Pulmonary Function Testing, CHU de Rennes, Rennes, Bretagne, France.
Catherine DroitcourtDepartment of Dermatology, CHU de Rennes, Rennes, Bretagne, France.
Antoinette PerlatDepartment of Internal Medicine and Clinical Immunology, CHU de Rennes, Rennes, France.
Stéphane JouneauINSERM, IRSET UMR 1085, Rennes 1 University, Rennes, Bretagne, France.
Vincent SobanskiINFINITE-Institute for Translational Research in Inflammation, Lille, France.ORCID 0000-0003-3083-2441
Erwan DonalDepartment of Cardiology, CHU de Rennes, Rennes, Bretagne, France.
Alain LescoatDepartment of Internal Medicine and Clinical Immunology, CHU de Rennes, Rennes, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSystemic lupus erythematosus (SLE), a systemic autoimmune disease with heterogeneous severity, poses a challenge in classifying patients due to its dynamic phenotype. We therefore aimed to identify clinical clusters at diagnosis and at the last available visit to define subgroups with different disease trajectories.

methodsThis retrospective study included 278 SLE patients fulfilling the 2019 EULAR/American College of Rheumatology classification criteria. Data were extracted from the patient's medical record, encompassing demographic, clinical and immunological features. Two hierarchical clustering analyses were performed: one at diagnosis and the other at the last available visit based on 23 clinical manifestations. We assessed the distribution of autoantibodies among clusters, and survival analyses compared prognosis using the Cox regression model.

resultsThree symptom clusters were identified at diagnosis and confirmed at the last available visit, with consistent clinical profiles. The largest, clusters 1/1', exhibited early articular (95.3%; p=0.0043) and mucocutaneous (58.7%; p=0.0031) symptoms with the best survival rate. Clusters 2/2' displayed the most severe phenotype, including renal involvement (62.2%; p<0.0001), positivity for anti-DNA (90.0%; p=0.0151) and anti-Sm (34.4%; p<0.0001) autoantibodies, and worse prognosis. Clusters 3/3' exhibited a high proportion of SLE patients fulfilling the definition of mixed connective tissue disease (MCTD) (50.0%; p<0.0001) with anti-U1-RNP 70 kDa autoantibodies (87.5%; p<0.0001). Clusters 1 and 2 remained stable during follow-up, cluster 2 even expanding over time, while over half of cluster 3 patients transitioned to a different subgroup.

conclusionWe identified a distinct MCTD phenotype within SLE patients, a severe SLE phenotype with poor prognosis, and a third group of SLE patients with lower visceral involvement. Clusters remained stable over time, providing insights into disease progression.

Indexed as

Lupus Erythematosus, SystemicAdultAntibodies, AntinuclearAutoantibodiesCluster AnalysisDisease ProgressionFemaleHumansMaleMiddle AgedPhenotypePrognosisRetrospective StudiesSeverity of Illness IndexAntibodies, AntinuclearAutoantibodiesAutoantibodiesConnective Tissue DiseasesSystemic Lupus Erythematosus

Identifiers

PMID40210260
PMCPMC11987115

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.