Evidence map›Paper›PMID 30568660›Full record

ArticleFrontiers in immunology2018

Low Percentage of Signal Regulatory Protein α/β

Laura Magill, Marsilio Adriani, Véronique Berthou, Keguan Chen, Aude Gleizes, Salima Hacein-Bey-Abina, Agnes Hincelin-Mery, Xavier Mariette, Marc Pallardy, Sebastian Spindeldreher and 5 more

Open access · goldAbstract readEvaluation StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
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

15 authors at 9 institutions in 4 countries.

Laura MagillDivision of Medicine, Centre for Rheumatology, University College London, London, United Kingdom.
Marsilio AdrianiDivision of Medicine, Centre for Rheumatology, University College London, London, United Kingdom.
Véronique BerthouSanofi, Chilly-Mazarin, France.
Keguan ChenClinical Immunology, GlaxoSmithKline, Philadelphia, PA, United States.
Aude GleizesINSERM UMR996, Faculté Pharmacie, Université Paris Sud, Châtenay-Malabry, France.
Salima Hacein-Bey-AbinaClinical Immunology Laboratory, AP-HP, Le Kremlin-Bicêtre Hospital, Paris-Sud University Hospitals, Le Kremlin-Bicêtre, France.
Agnes Hincelin-MerySanofi, Chilly-Mazarin, France.
Xavier MarietteCentre for Immunology of Viral Infections and Autoimmune Diseases, INSERM UMR1184, AP-HP, Université Paris-Sud, Hôpitaux Universitaires Paris-Sud, Le Krelin-Bicetre, France.
Marc PallardyINSERM UMR996, Faculté Pharmacie, Université Paris Sud, Châtenay-Malabry, France.
Sebastian SpindeldreherNovartis Pharma AG, Novartis Institutes for BioMedical Research, Basel, Switzerland.
Natacha SzelyINSERM UMR996, Faculté Pharmacie, Université Paris Sud, Châtenay-Malabry, France.
David A IsenbergDivision of Medicine, Centre for Rheumatology, University College London, London, United Kingdom.
Jessica J MansonDepartment of Rheumatology, University College London Hospital, London, United Kingdom.
Elizabeth C JuryDivision of Medicine, Centre for Rheumatology, University College London, London, United Kingdom.
Claudia MauriDivision of Medicine, Centre for Rheumatology, University College London, London, United Kingdom.
University College London · GBSanofi (France) · FRUniversité Paris-Sud · FRAssistance Publique – Hôpitaux de Paris · FRDélégation Paris 5 · FRGlaxoSmithKline (United States) · USInserm · FRNovartis (Switzerland) · CHUniversity College Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An important goal for personalized treatment is predicting response to a particular therapeutic. A drawback of biological treatment is immunogenicity and the development of antibodies directed against the drug [anti-drug antibodies (ADA)], which are associated with a poorer clinical outcome. Here we set out to identify a predictive biomarker that discriminates rheumatoid arthritis (RA) patients who are more likely to develop ADA in response to adalimumab, a human monoclonal antibody against tumor necrosis factor (TNF)α. By taking advantage of an immune-phenotyping platform, LEGENDScreen™, we measured the expression of 332 cell surface markers on B and T cells in a cross-sectional adalimumab-treated RA patient cohort with a defined ADA response. The analysis revealed seven differentially expressed markers (DEMs) between the ADA

Indexed as

AdalimumabAdultAgedAntigens, DifferentiationAntirheumatic AgentsArthritis, RheumatoidBiomarkersB-LymphocytesCross-Sectional StudiesDrug HypersensitivityFemaleHumansImmunologic MemoryLymphocyte CountMaleMiddle AgedAdalimumabAntigens, DifferentiationAntirheumatic AgentsBiomarkersNeural Cell Adhesion MoleculesReceptors, Cell SurfaceReceptors, ImmunologicSIRPA protein, humanSIRPB1 protein, humanSIRPB2 protein, humanTNF protein, humanTumor Necrosis Factor-alphaadalimumabanti-drug antibodiesanti-TNFB cellsimmunogenicitymemory B cellsrheumatoid arthritisSIRP

Identifiers

PMID30568660
PMCPMC6290031
OpenAlexW2903481362

What OpenQuestion holds

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Registered trials

None linked

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.