Evidence map›Paper›PMID 31029086›Full record

Trial reportBMC immunology2019

A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation.

Nicole Wittenbrink, Sabrina Herrmann, Arturo Blazquez-Navarro, Chris Bauer, Eric Lindberg, Kerstin Wolk, Robert Sabat, Petra Reinke, Birgit Sawitzki, Oliver Thomusch and 4 more

Registry-linked trialOpen access · goldAbstract readClinical Trial
In one paragraph

Trial report in BMC immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00724022 (Triple Arm, Prospectively Randomized Multi Centre Study Phase IV to Evaluate Calcineurin Inhibitor Reduced, Steroid Free Immunosuppression After Renal Transplantation in Non-risk Patients), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 18% 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.

NCT00724022 phase4completednot on this map

Triple Arm, Prospectively Randomized Multi Centre Study Phase IV to Evaluate Calcineurin Inhibitor Reduced, Steroid Free Immunosuppression After Renal Transplantation in Non-risk Patients

TypeinterventionalSponsorUniversity Hospital FreiburgRan2008 to 2014Enrolled600ConditionsDisorder Related to Renal TransplantationArmsBasiliximab, Tacrolimus, MMF, Prednisolon, Basiliximab, Tacrolimus, MMF, Tacrolimus, MMF, rATG
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Artificial intelligence and kidney transplantation.World journal of transplantation · 2021
    Review
  6. 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

14 authors at 8 institutions in 1 country.

Nicole WittenbrinkSystems Immunology Lab, Department of Biology, Humboldt University Berlin, Berlin, Germany.
Sabrina HerrmannFraunhofer Institute for Cell Therapy and Immunology, Bioanalytics und Bioprocesses, Potsdam, Germany.
Arturo Blazquez-NavarroSystems Immunology Lab, Department of Biology, Humboldt University Berlin, Berlin, Germany.
Chris BauerMicroDiscovery GmbH, Berlin, Germany.
Eric LindbergMicroDiscovery GmbH, Berlin, Germany.
Kerstin WolkBerlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany.
Robert SabatPsoriasis Research and Treatment Center, Institute of Medical Immunology, Department of Dermatology and Allergy, Charité University Medicine Berlin, Berlin, Germany.
Petra ReinkeBerlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany.
Birgit SawitzkiBerlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany.
Oliver ThomuschKlinik für Allgemein- und Viszeralchirurgie, Universitätsklinikum Freiburg, Freiburg, Germany.
Christian HugoUniversity Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany.
Nina BabelBerlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany.
Harald SeitzFraunhofer Institute for Cell Therapy and Immunology, Bioanalytics und Bioprocesses, Potsdam, Germany.
Michal Or-GuilSystems Immunology Lab, Department of Biology, Humboldt University Berlin, Berlin, Germany. m.orguil@biologie.hu-berlin.de.
Charité - Universitätsmedizin Berlin · DEHumboldt-Universität zu Berlin · DEFraunhofer Institute for Cell Therapy and Immunology · DEMicroDiscovery (Germany) · DEBerlin-Brandenburger Centrum für Regenerative Therapien · DEUniversitätsklinik Marien Hospital Herne · DEUniversity Hospital Carl Gustav Carus · DEUniversity Medical Center Freiburg · DE

Funding

Visceral Leishmaniasis in Bihar State, IndiaU19AI074321 · NIAID · BANARAS HINDU UNIVERSITY · PI SUNDAR, SHYAM · 2017 to 2021
$2.8M
NIAID NIH HHS U19 AI074321
6 · The paper itself

Abstract

backgroundAcute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach.

resultsThe data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA < 30%) who showed detectable pre-transplant anti-HLA 1 antibodies. To assess whether the reactivity profiles provide a means for ACR risk assessment, we established a novel approach which differs from standard approaches in two aspects: the use of quantitative continuous data and the use of a multiparameter classification method. Remarkably, it achieved significant prediction of the 38 graft recipients who experienced ACR with a balanced accuracy of 82.7% (sensitivity = 76.5%, specificity = 88.9%).

conclusionsThe resultant classifier achieved one of the highest prediction accuracies in the literature for pre-transplant risk assessment of ACR. Importantly, it can facilitate risk assessment in non-sensitized patients who lack donor-specific antibodies. As the classifier is based on continuous data and includes weak signals, our results emphasize that not only strong but also weak binding interactions of antibodies and HLA 1 antigens contain predictive information.

trial registrationClinicalTrials.gov NCT00724022 . Retrospectively registered July 2008.

Indexed as

Kidney TransplantationAcute DiseaseAdultAgedFemaleGraft RejectionHistocompatibility Antigens Class IHistocompatibility TestingHLA AntigensHumansIsoantibodiesMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk AssessmentHistocompatibility Antigens Class IHLA AntigensIsoantibodiesAcute cellular rejectionAnti-HLA-1 antibodiesImmune signaturesMachine learningPre-transplantation risk assessmentRenal transplantationSingle HLA antigen bead assay

Identifiers

PMID31029086
PMCPMC6486998
OpenAlexW2947525426

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.