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Kidney Transplant RejectionEU-TRAINNCT03652402

Precision Risk Stratification in Kidney Transplant Patients - EU-TRAIN

An observational study of Kidney Transplant Rejection and Kidney Transplantation, run by Assistance Publique - Hôpitaux de Paris at 9 sites in 4 countries.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record
Search all trials

Trial summary

Main objective: To design a precision risk stratification system that predicts individual risk of rejection Read more about this study

Who is it for?
Ages 18 to 100 years
What is being tested?
kidney transplantation
Type of treatment
Surgery or procedure
How many people
558 participants
Where
9 sitesin 4 countries
Study dates
27 Nov 2018to 28 Oct 2021
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 to 100 years
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: New kidney transplants patients

Who may be able to join

  • Men and women, Age ≥ 18 years old at the time of transplantation.
  • Patients receiving a living or deceased donor kidney allograft.
  • Patients who signed the informed consent form and willing to comply with study procedures.
  • Female patients of child-bearing potential must have a negative pregnancy test (serum beta-hCG) and must be practicing an effective, reliable and medically approved contraceptive regimen

Who cannot join

  • History of multi-organ transplant (interference with rejection natural history).
  • Participant is unable or unwilling to comply with study procedures (including foreign language speakers who are not assisted by a native language speaker).
  • Vulnerable participants (minors, protected adults, legally detained)

Trial locations and contacts

9 sites in 4 countries.

9 sites in 4 countries

France4 sites

  • Hôpital du Kremlin Bicêtre

    Le Kremlin-Bicêtre, Paris, 94270

  • CHU Nantes

    Nantes, 44093

  • Hôpital Necker

    Paris, 75015

  • Hopital Saint Louis

    Paris, Île-de-France Region, 75010

Other trials in France

Germany2 sites

  • Hospital La Charité Campus Virchow

    Berlin, 10117

  • Hospital La Charité

    Mitte, State of Berlin, 10117

Other trials in Germany

Spain2 sites

  • Hospital Bellvitge

    Barcelona, 08907

  • Hospital Vall d'Hebron

    Barcelona, 08907

Other trials in Spain

Switzerland1 site

  • Hôpitaux Universitaires de Genève

    Geneva, 4 CH 1211

Other trials in Switzerland

About this study

Official title: The EUropean TRAnsplantation and INnovation Consortium for Risk Stratification in Kidney Transplant Patients

Main objective: To design a precision risk stratification system that predicts individual risk of rejection

Read the detailed description

Allograft rejection is still a major threat to allografts with thousands of allografts failing every year worldwide due to organ rejection, with immediate consequences for the patients in terms of mortality and morbidity. With a prevalence around 20% in the first-year post transplant, rejection also carries high economic impact representing a 72% increase in transplantation price and downstream cost because of return on dialysis (60,000€ health care increase per patient). The rough estimates from 200,000 kidney allograft failures per year equals to 12 billion extra cost for the health care system per year.

Various explanations may be involved: 1) The current stratification system relies on various elements of the follow up of standard of care after kidney transplantation (histology, immunology) taken separately and, 2) Current therapeutic strategy is a "one fit for all" approach. Literature data show that therapeutics are not individualized, with 98% of patients having the same immunosuppressive regimens without analysis of response to therapy; 3) Lack of integration of omics in the stratification process. Today, the only approaches used to monitor the advent of immune-mediated allograft damage are nonspecific markers such as serum creatinine level and proteinuria which are not integrated in a dynamic approach. Some kidney transplant programs have implemented surveillance allograft biopsies, but they lack specificity and sensitivity and do not provide etiopathology of the underlying process. This impairs the risk stratification process.

In this project, leading European scientific teams, which have created relevant population cohorts and expertise, have joined forces to allow for large-scale (>5,000 patients) risk prediction studies in the field of kidney transplantation. The overall goal of the EUropean TRAnsplantation and INnovation consortium (EU-TRAIN) is to prevent kidney allograft failure and improve allograft survival by informing clinical decision and delivering optimised interventions to patients at individual level. The project aims to improve the current gold standard for risk stratification and prognosis among kidney transplant recipients.

The members of the EU-TRAIN consortium have invested heavily in the last decade to create large highly detailed European kidney transplant cohorts and to achieve best level scientific expertise in the assessment of innovative biomarkers and rejection reclassification on the basis of disease mechanism using gene expression. Ground-breaking concrete results have already been obtained that have changed patient care and transplant medicine guidelines: This is underlined by highly cited publications in the leading specialised journals and also in journals aimed at a popular audience that underlines the systemic nature of this approach, (NEJM (n=10), Lancet (n=2), BMJ (n=1), JASN (n=18)). Using this approach, the investigators have recently identified new forms of allograft rejection, resulting in changes in the most recent international allograft Banff classification and reclassifying rejection diagnosis and disease stage. This research strategy also led to recently demonstrate the clinical relevance of new non-invasive biomarkers for defining the pathogenicity of anti-HLA antibodies and allograft loss risk assessment and incorporate gene expression measurements in allograft rejection risk stratification.

The EU-TRAIN project will further elevate these cohorts synergistically by adding data on novel biomarkers, so far underdeveloped in kidney transplant research, in particular genomics and immunological data. A comprehensive integration strategy of these exceptionally large and complete cohorts constitutes a quantum leap in transplant research, and offers a unique opportunity, out of reach so far, to design strategies for truly personalised medicine.

The expected benefit for participants and society will be to reduce the financial burden of graft rejection for society.

500 new transplanted patients in the 7 clinical transplant sites will be included in the prospective multicentre EU-TRAIN cohort with centralised analysis of samples in CHUN (blood mRNA), ICS (blood cellular assays), Charité (non-HLA antibodies and blood endothelial targets), AP-HP (blood anti-HLA DSA), and INSERM (Biopsy mRNA).

Vulnerable participants excluded.

Schedule for the study:

  • inclusion period: 12 months
  • participation period (treatment - follow-up): 12 months
  • total duration of the study: 24 months

Exclusion period for participation in other studies, and justification: the participation to other minimal risks and constraints studies and observational non-interventional studies is allowed during this study. There is no exclusion period at the end of study. The participation to other interventional and observational non-interventional studies is allowed after the end of the study.

Number of enrolments expected per site and per month :

  • Necker Hospital, Paris: 10 patients / month
  • Saint-Louis Hospital, Paris: 6 patients / month
  • CHU Nantes: 10 patients / month
  • Charité-Universitätsmedizin, Campus Virchow Klinikum, Berlin: 4 patients / month
  • Charité-Universitätsmedizin, Campus Mitte, Berlin: 3 patients / month
  • Bellvitge University Hospital, Barcelona: 7 patients / month
  • Geneva University Hospitals, Geneva: 2 patients / month
  • Vall d'Hebron Hospital, Barcelona : 6 patients / month
  • Kremlin Bicêtre Hospital, Paris : 4 patients / month
Being tested
kidney transplantation
Keywords
Kidney, Allogenic transplantation, Cohort study, Rejection, Biomarkers, Response to treatment, Integrative medicine
Medical subject headings
Rejection, Psychology

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • kidney transplantationProcedure or surgery

    Also called Gene expression analysis in the biopsy, Non-HLA antibody analysis in the blood, Protein biomarker analysis in the blood, T and B cell analyses in the blood

    samples additional to the standard of care' (SOC)will be taken at each visit (Day 0, Month 3, Month12, clinical indication)

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Capacity of non-invasive biomarkers and intragraft gene expression profiles combined to standard of care data (HLA system, clinical and biological data)

    Prognosis value of non-invasive biomarkers and intragraft gene expression profile changes combined to standard of care data changes (HLA system, clinical and biological data), to identify high versus low risk profiles of rejection as measured by DSA characteristics (Donor-Specific Antibody) by Luminex single antigen assay and non DSA characteristics by functional in vitro assay on endothelial targets, alloreactive T and B cells profiles by ELISPOT, blood mRNA expression by NanoString technologies and gene expression on DNA chips.

    Measured: Day 0, Month 3, Month 12, clinical indication over 12 months

Secondary outcomes (6)

  1. Correlation of blood biomarkers concentration with allograft rejection (rejection assessed by histopathology)

    Blood biomarkers measured: HLA and non-HLA DSA characteristics (by Luminex Single Antigen and functional in vitro assay on endothelial targets), alloreactive T and B cell profiles (by ELISPOT) and candidate gene profiles by NanoString technologies: AKR1C3, CD40, CTLA4, ID3, MZB1, TCL1A, TRIB1, TLR4 TUBA4A, WHAZ, CD3E, CD8A, CD4, MS4A1, FOXP3, GZMB, ENTPD1, POU2AAF1, POU2F1, CD9, IL7R, BLK, MMP9, CXCL9, CXCL10, CXCL11, UPK1A, TGFB1, IL2RA, PRF1, TIMP1, PAI1, FN1, TIGIT and 4 reference genes: HPRT1, B2M, GAPDH and ACTB

    Measured: Day 0, Month 3, Month12, clinical indication over 12 months

  2. Correlation of blood biomarker concentrations with allograft function (function measured by the Glomerular Filtration Rate (GFR)).

    Blood biomarkers measured: HLA and non-HLA DSA characteristics (by Luminex Single Antigen and functional in vitro assay on endothelial targets), alloreactive T and B cell profiles (by ELISPOT) and candidate gene profiles by NanoString technologies: AKR1C3, CD40, CTLA4, ID3, MZB1, TCL1A, TRIB1, TLR4 TUBA4A, WHAZ, CD3E, CD8A, CD4, MS4A1, FOXP3, GZMB, ENTPD1, POU2AAF1, POU2F1, CD9, IL7R, BLK, MMP9, CXCL9, CXCL10, CXCL11, UPK1A, TGFB1, IL2RA, PRF1, TIMP1, PAI1, FN1, TIGIT and 4 reference genes: HPRT1, B2M, GAPDH and ACTB

    Measured: Day 0, Month 3, Month12, clinical indication over 12 months

  3. Assessment of changes in biomarker levels in serial measurements and association with allograft function (function measured by the GFR)

    Blood biomarkers measured: HLA and non-HLA DSA characteristics (by Luminex Single Antigen and functional in vitro assay on endothelial targets), alloreactive T and B cell profiles (by ELISPOT) and candidate gene profiles by NanoString technologies: AKR1C3, CD40, CTLA4, ID3, MZB1, TCL1A, TRIB1, TLR4 TUBA4A, WHAZ, CD3E, CD8A, CD4, MS4A1, FOXP3, GZMB, ENTPD1, POU2AAF1, POU2F1, CD9, IL7R, BLK, MMP9, CXCL9, CXCL10, CXCL11, UPK1A, TGFB1, IL2RA, PRF1, TIMP1, PAI1, FN1, TIGIT and 4 reference genes: HPRT1, B2M, GAPDH and ACTB Biomarkers measured in the biopsy: pangenomic approach of gene expression profiles using Affymetrix DNA chips and comparing gene expression in low- and high-risk patients

    Measured: Day 0, Month 3, Month12, clinical indication over 12 months

  4. Correlation of gene expression in kidney allografts with allograft rejection (rejection assessed by histopathology)

    Biomarkers measured in the biopsy: pangenomic approach of gene expression profiles using Affymetrix DNA chips and comparing gene expression in low- and high-risk patients

    Measured: Day 0, Month 3, Month 12, clinical indication over 12 months

  5. Gene expression related risk stratification of response to treatment in kidney allograft rejection (rejection assessed by histopathology)

    Blood biomarkers measured: Candidate gene profiles by NanoString technologies: AKR1C3, CD40, CTLA4, ID3, MZB1, TCL1A, TRIB1, TLR4 TUBA4A, WHAZ, CD3E, CD8A, CD4, MS4A1, FOXP3, GZMB, ENTPD1, POU2AAF1, POU2F1, CD9, IL7R, BLK, MMP9, CXCL9, CXCL10, CXCL11, UPK1A, TGFB1, IL2RA, PRF1, TIMP1, PAI1, FN1, TIGIT and 4 reference genes: HPRT1, B2M, GAPDH and ACTB Biomarkers measured in the biopsy: pangenomic approach of gene expression profiles using Affymetrix DNA chips and comparing gene expression in low- and high-risk patients

    Measured: Day 0, Month 3, Month12, clinical indication over 12 months

  6. Assessment of the changes of patient's well-being across time and centres

    Assessment of the changes of patient's well-being across time and centres using the results of a self health-questionnaire filled in by each patient at each time point. All items are measured on a scale of 1 to 3. The first 3 items measure mobility, self-care and performance of usual activities, with higher values indicating lower mobility and unability to take care of one's self or to perform usual activities, respectively. The 4th item measures pain and discomfort, with higher values indicating extreme pain or discomfort. The last item measures anxiety and depression, with higher values indicating extreme anxiety or depression. A general self-reported health state measures patient's opinion about his/her own health on a scale of 0 to 100, with a 0 score as the worst state and 100 as the best state.

    Measured: Day 0, Month 3, Month12, clinical indication over 12 months

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted29 Aug 2018
  2. Study start27 Nov 2018
  3. Primary completion28 Oct 2021
  4. Study completion28 Oct 2021

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
558 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT03652402
Sponsor's protocol ID
K170203J
Other IDs
IDRCB 2018-A00733-52
Acronym
EU-TRAIN
Status last verified
Jun 2024
First submitted
16 Jul 2018
Last updated
5 Jun 2024
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No

Publications

  • Montero N, Farouk S, Gandolfini I, Crespo E, Jarque M, Meneghini M, Torija A, Maggiore U, Cravedi P, Bestard O. Pretransplant Donor-specific IFNgamma ELISPOT as a Predictor of Graft Rejection: A Diagnostic Test Accuracy Meta-analysis. Transplant Direct. 2019 Apr 25;5(5):e451. doi: 10.1097/TXD.0000000000000886. eCollection 2019 May.

    PubMed 31165086

  • Danger R, Feseha Y, Brouard S. The Pseudokinase TRIB1 in Immune Cells and Associated Disorders. Cancers (Basel). 2022 Feb 17;14(4):1011. doi: 10.3390/cancers14041011.

    PubMed 35205759

  • Brinas F, Danger R, Brouard S. TCL1A, B Cell Regulation and Tolerance in Renal Transplantation. Cells. 2021 Jun 1;10(6):1367. doi: 10.3390/cells10061367.

    PubMed 34206047

  • Danger R, Moiteaux Q, Feseha Y, Geffard E, Ramstein G, Brouard S. FaDA: A web application for regular laboratory data analyses. PLoS One. 2021 Dec 20;16(12):e0261083. doi: 10.1371/journal.pone.0261083. eCollection 2021.

    PubMed 34928943

  • Ba R, Geffard E, Douillard V, Simon F, Mesnard L, Vince N, Gourraud PA, Limou S. Surfing the Big Data Wave: Omics Data Challenges in Transplantation. Transplantation. 2022 Feb 1;106(2):e114-e125. doi: 10.1097/TP.0000000000003992.

    PubMed 34889882

  • Massart A, Danger R, Olsen C, Emond MJ, Viklicky O, Jacquemin V, Soblet J, Duerinckx S, Croes D, Perazzolo C, Hruba P, Daneels D, Caljon B, Sever MS, Pascual J, Miglinas M; Renal Tolerance Investigators; Pirson I, Ghisdal L, Smits G, Giral M, Abramowicz D, Abramowicz M, Brouard S. An exome-wide study of renal operational tolerance. Front Med (Lausanne). 2023 May 17;9:976248. doi: 10.3389/fmed.2022.976248. eCollection 2022.

    PubMed 37265662

  • Yoo D, Goutaudier V, Divard G, Gueguen J, Astor BC, Aubert O, Raynaud M, Demir Z, Hogan J, Weng P, Smith J, Garro R, Warady BA, Zahr RS, Sablik M, Twombley K, Couzi L, Berney T, Boyer O, Duong-Van-Huyen JP, Giral M, Alsadi A, Gourraud PA, Morelon E, Le Quintrec M, Brouard S, Legendre C, Anglicheau D, Villard J, Zhong W, Kamar N, Bestard O, Djamali A, Budde K, Haas M, Lefaucheur C, Rabant M, Loupy A. An automated histological classification system for precision diagnostics of kidney allografts. Nat Med. 2023 May;29(5):1211-1220. doi: 10.1038/s41591-023-02323-6. Epub 2023 May 4.

    PubMed 37142762

  • Ed-Driouch C, Mars F, Gourraud PA, Dumas C. Addressing the Challenges and Barriers to the Integration of Machine Learning into Clinical Practice: An Innovative Method to Hybrid Human-Machine Intelligence. Sensors (Basel). 2022 Oct 29;22(21):8313. doi: 10.3390/s22218313.

    PubMed 36366011

  • Kerouac S, Taggart ME, Lescop J, Fortin MF. Dimensions of health in violent families. Health Care Women Int. 1986;7(6):413-26. doi: 10.1080/07399338609515756. No abstract available.

    PubMed 3641838

  • Divard G, Raynaud M, Tatapudi VS, Abdalla B, Bailly E, Assayag M, Binois Y, Cohen R, Zhang H, Ulloa C, Linhares K, Tedesco HS, Legendre C, Jouven X, Montgomery RA, Lefaucheur C, Aubert O, Loupy A. Comparison of artificial intelligence and human-based prediction and stratification of the risk of long-term kidney allograft failure. Commun Med (Lond). 2022 Nov 23;2(1):150. doi: 10.1038/s43856-022-00201-9.

    PubMed 36418380

  • Tripathi N, Danger R, Chesneau M, Brouard S, Laurent AD. Structural insights into the catalytic mechanism of granzyme B upon substrate and inhibitor binding. J Mol Graph Model. 2022 Jul;114:108167. doi: 10.1016/j.jmgm.2022.108167. Epub 2022 Mar 22.

    PubMed 35366507

  • Danger R, Le Berre L, Cadoux M, Kerleau C, Papuchon E, Mai HL, Nguyen TV, Guerif P, Morelon E, Thaunat O, Legendre C, Anglicheau D, Lefaucheur C, Couzi L, Del Bello A, Kamar N, Le Quintrec M, Goutaudier V, Renaudin K, Giral M, Brouard S; DIVAT Consortium. Subclinical rejection-free diagnostic after kidney transplantation using blood gene expression. Kidney Int. 2023 Jun;103(6):1167-1179. doi: 10.1016/j.kint.2023.03.019. Epub 2023 Mar 27.

    PubMed 36990211

  • Ed-Driouch C, Cheneau F, Simon F, Pasquier G, Combes B, Kerbrat A, Le Page E, Limou S, Vince N, Laplaud DA, Mars F, Dumas C, Edan G, Gourraud PA. Multiple sclerosis clinical decision support system based on projection to reference datasets. Ann Clin Transl Neurol. 2022 Dec;9(12):1863-1873. doi: 10.1002/acn3.51649. Epub 2022 Nov 22.

    PubMed 36412095

  • Girardin FR, Nicolet A, Bestard O, Lefaucheur C, Budde K, Halleck F, Brouard S, Giral M, Gourraud PA, Horcholle B, Villard J, Marti J, Loupy A. Immunosuppressant drugs and quality-of-life outcomes in kidney transplant recipients: An international cohort study (EU-TRAIN). Front Pharmacol. 2023 Apr 27;14:1040584. doi: 10.3389/fphar.2023.1040584. eCollection 2023.

    PubMed 37180729

  • Girardin FR, Cohen K, Schwenkglenks M, Durand-Zaleski I. Editorial: Pharmacoeconomics in the era of health technology assessment and outcomes research to prioritize resource use, innovation and investment. Front Pharmacol. 2023 May 16;14:1210002. doi: 10.3389/fphar.2023.1210002. eCollection 2023. No abstract available.

    PubMed 37261286

Questions about this trial

What is this clinical trial studying?

An observational study of Kidney Transplant Rejection and Kidney Transplantation, run by Assistance Publique - Hôpitaux de Paris at 9 sites in 4 countries.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: finished, as of the sponsor's last update on 5 Jun 2024. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 9 sites in France, Germany, Spain, Switzerland. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Capacity of non-invasive biomarkers and intragraft gene expression profiles combined to standard of care data (HLA system, clinical and biological data) (time frame: Day 0, Month 3, Month 12, clinical indication over 12 months). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT03652402, which also lists 15 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Jun 2024.

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