Evidence map›Paper›PMID 35788140›Full record

ArticleScientific reports2022

Autoantibodies against IFNα in patients with systemic lupus erythematosus and susceptibility for infection: a retrospective case-control study.

Maxime Beydon, Pascale Nicaise-Roland, Arthur Mageau, Carine Farkh, Eric Daugas, Vincent Descamps, Philippe Dieude, Antoine Dossier, Tiphaine Goulenok, Fatima Farhi and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

10 citing papers in PubMed, 14 citations in OpenAlex.

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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

14 authors at 4 institutions in 1 country.

Maxime BeydonService de Médecine Interne, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, 46 rue Henri Huchard, 75018, Paris, France.
Pascale Nicaise-RolandService d'Immunologie « Autoimmunité, Hypersensibilités et Biothérapies », Hôpital Bichat, Assistance Publique Hôpitaux de Paris, Paris, France.
Arthur MageauService de Médecine Interne, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, 46 rue Henri Huchard, 75018, Paris, France.
Carine FarkhService d'Immunologie « Autoimmunité, Hypersensibilités et Biothérapies », Hôpital Bichat, Assistance Publique Hôpitaux de Paris, Paris, France.
Eric DaugasLaboratoire d'Excellence Inflamex, Faculté de Médecine Site Bichat, Centre de Recherche Sur L'Inflammation, INSERM UMR1149, CNRS ERL8252, Université de Paris, Paris, France.
Vincent DescampsDépartement de Dermatologie, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, Paris, France.
Philippe DieudeDépartement de Rhumatologie, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, Paris, France.
Antoine DossierService de Médecine Interne, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, 46 rue Henri Huchard, 75018, Paris, France.
Tiphaine GoulenokService de Médecine Interne, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, 46 rue Henri Huchard, 75018, Paris, France.
Fatima FarhiService de Médecine Interne, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, 46 rue Henri Huchard, 75018, Paris, France.
Pierre MutuonDépartement d'Information Médicale, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, Paris, France.
Jean-Francois TimsitIAME UMR1137, Equipe DeScID, Université de Paris, Paris, France.
Thomas PapoService de Médecine Interne, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, 46 rue Henri Huchard, 75018, Paris, France.
Karim SacreService de Médecine Interne, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, 46 rue Henri Huchard, 75018, Paris, France. karim.sacre@aphp.fr.
Hôpital Bichat-Claude-Bernard · FRAssistance Publique – Hôpitaux de Paris · FRInserm · FRUniversité Paris Cité · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IFNα and anti-IFNα autoantibodies have been implicated in susceptibility both for systemic lupus erythematosus (SLE) and viral infection. We aimed to analyze the SLE disease phenotype and risk for infection associated with anti-IFN-α IgG autoantibodies in SLE patients In this multidisciplinary retrospective single referral center study, all consecutive patients with SLE admitted between January 1st and November 30th 2020 were considered. All subjects fulfilled the ACR/EULAR 2019 criteria for SLE. Anti-IFNα IgG autoantibodies were quantified at admission by ELISA. Demographic, medical history, laboratory, treatment, and outcome data were extracted from electronic medical records using a standardized data collection form. 180 patients [female 87.2%, median age of 44.4 (34-54.2) years] were included. The median disease duration was 10 years [4-20] with a median SLEDAI score of 2 [0-4] at study time. Fifty-four (30%) patients had a past-history of lupus nephritis. One hundred and forty-four (80%) had received long-term glucocorticoids and 99 (55%) immunosuppressive drugs. Overall, 127 infections-mostly bacterial and viral-were reported in 95 (52.8%) patients. Twenty SLE patients (11.1%) had positive anti-IFNα IgG autoantibodies with a titer ranging from 10 to 103 UA/mL. Age, sex, SLE phenotype and treatment did not significantly differ between SLE patients with or without anti-IFNα. Infection rate was similar in both groups except for tuberculosis which was more frequent in patients with anti-IFNα (20% vs. 3.1%, p = 0.01). The prevalence of autoantibodies against IFNα is high in SLE and associated with a higher frequency of tuberculosis.

Indexed as

AutoantibodiesLupus Erythematosus, SystemicCase-Control StudiesFemaleHumansImmunoglobulin GInterferon-alphaRetrospective StudiesAutoantibodiesImmunoglobulin GInterferon-alpha

Identifiers

PMID35788140
PMCPMC9253327
OpenAlexW4283819109

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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.