Evidence map›Paper›PMID 36564813›Full record

ArticleArthritis research & therapy2022

Multiparametric autoantibody analysis: a new paradigm for the diagnosis of connective tissue diseases.

Nicola Bizzaro, Danilo Villalta, Vittorio Bini, Paola Migliorini, Franco Franceschini, Silvia Piantoni, Emirena Garrafa, Valeria Riccieri, Antonella Fioravanti, Francesca Bellisai and 16 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Arthritis research & therapy, 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
2.2field-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

26 authors at 14 institutions in 1 country.

Nicola BizzaroLaboratory of Clinical Pathology, San Antonio Hospital, Tolmezzo, Italy. nic.bizzaro@gmail.com.ORCID 0000-0002-4227-6983
Danilo VillaltaImmunology and Allergology, S. Maria degli Angeli Hospital, Pordenone, Italy.
Vittorio BiniInternal Medicine, Endocrine and Metabolic Science Section, University of Perugia, Perugia, Italy.
Paola MiglioriniClinical Immunology, University of Pisa, Pisa, Italy.
Franco FranceschiniRheumatology and Clinical Immunology Unit, Department of Clinical and Experimental Sciences, ASST Spedali Civili and University of Brescia, Brescia, Italy.
Silvia PiantoniRheumatology and Clinical Immunology Unit, Department of Clinical and Experimental Sciences, ASST Spedali Civili and University of Brescia, Brescia, Italy.
Emirena GarrafaLaboratory of Clinical Chemistry, Department of Molecular and Translational Medicine, ASST Spedali Civili and University of Brescia, Brescia, Italy.
Valeria RiccieriRheumatology, "Sapienza" University, Rome, Italy.
Antonella FioravantiRheumatology Unit, Department of Medicine, Surgery and Neuroscience, Azienda Ospedaliera Universitaria Senese, Policlinico Le Scotte, Siena, Italy.
Francesca BellisaiRheumatology Unit, Department of Medicine, Surgery and Neuroscience, Azienda Ospedaliera Universitaria Senese, Policlinico Le Scotte, Siena, Italy.
Marilina TampoiaClinical Pathology, Presidio Ospedaliero SS. Annunziata, Taranto, Italy.
Marco FornaroRheumatology Unit, Department of Emergence and Transplantation (DETO), University of Bari, Bari, Italy.
Florenzo IannoneRheumatology Unit, Department of Emergence and Transplantation (DETO), University of Bari, Bari, Italy.
Anna GhirardelloRheumatology Unit, Department of Medicine, University of Padua, Padua, Italy.
Margherita ZenRheumatology Unit, Department of Medicine, University of Padua, Padua, Italy.
Boaz PaltererDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Paola ParronchiDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Maria InfantinoLaboratory of Immunology and Allergology, San Giovanni di Dio Hospital, Florence, Italy.
Maurizio BenucciRheumatology Unit, San Giovanni di Dio Hospital, Florence, Italy.
Amelia RigonClinical Immunology and Rheumatology, University Campus Biomedico, Rome, Italy.
Luisa ArcareseClinical Immunology and Rheumatology, University Campus Biomedico, Rome, Italy.
Stefania Del RossoIRCCS San Raffaele, Milan, Italy.
Valentina CantiIRCCS San Raffaele, Milan, Italy.
Elena Bartoloni *Rheumatology Unit, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
Roberto Gerli *Rheumatology Unit, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
FIRMA Collaborators
University of Brescia · ITUniversity of Perugia · ITAzienda Ospedaliera Universitaria Senese · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITNuovo Ospedale San Giovanni di Dio · ITUniversità Campus Bio-Medico · ITUniversity of Bari Aldo Moro · ITUniversity of Florence · ITUniversity of Padua · ITAzienda Ospedaliera Santa Maria Degli Angeli · ITOspedale Sant Antonio · ITPresidio Ospedaliero · ITSapienza University of Rome · ITUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn patients affected by connective tissue diseases (CTDs), the identification of wide autoantibody profiles may prove useful in early diagnosis, in the evaluation of prognosis (risk stratification), and in predicting response to therapy. The aim of the present study was to evaluate the utility of multiparametric autoantibody analysis performed by a new fully automated particle-based multi-analyte technology (PMAT) digital system in a large multicenter cohort of CTD patients and controls.

methodsSerum samples from 787 patients with CTD (166 systemic lupus erythematosus; 133 systemic sclerosis; 279 Sjögren's syndrome; 106 idiopathic inflammatory myopathies; 103 undifferentiated CTD), 339 patients with other disorders (disease controls) (118 infectious diseases, 110 organ-specific autoimmune diseases, 111 other rheumatic diseases), and 121 healthy subjects were collected in 13 rheumatologic centers of the FIRMA group. Sera were analyzed with the Aptiva-PMAT instrument (Inova Diagnostics) for a panel of 29 autoantibodies.

resultsMultiparametric logistic regression showed that enlarged antibody profiles have a higher diagnostic efficiency than that of individual antibodies or of antibodies that constitute classification criteria for a given disease and that probability of disease increases with multiple positive autoantibodies.

conclusionsThis is the first study that analyzes the clinical and diagnostic impact of autoantibody profiling in CTD. The results obtained with the new Aptiva-PMAT method may open interesting perspectives in the diagnosis and sub-classification of patients with autoimmune rheumatic diseases.

Indexed as

Connective Tissue DiseasesLupus Erythematosus, SystemicRheumatic DiseasesSjogren's SyndromeAutoantibodiesHumansAutoantibodiesAutoantibody profilingConnective tissue diseasesMultiplex testingParticle-based multi-analyte technology

Identifiers

PMID36564813
PMCPMC9783721
OpenAlexW4312179028

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Registered trials

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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.