Multidimensional System to Dynamically Predict Graft Survival After Kidney Transplantation
NCT ID: NCT04258891
Last Updated: 2020-09-16
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
14000 participants
OBSERVATIONAL
2004-01-01
2020-06-30
Brief Summary
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As highlighted in several studies, kidney function repeated measurements (i.e., trajectories) are highly associated with graft survival after kidney transplantation. The investigators made the hypothesis that these trajectories may bring relevant information in the context of graft survival risk prediction model. Hence, combining these trajectories with standard graft survival risk factors may enhance prediction performance. This could permit to derive a robust tool that could be updated over time by continuously capturing patient' personal evolution.
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Detailed Description
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In kidney transplantation, numerous parameters such as demographic, clinical and functional factors drive the deterioration of the kidney, sometimes leading to graft failure. Current approaches for investigating the relationship between these factors and graft failure have been limited by standard statistical approaches and by registries with an overall lack on granular data, including infrequent kidney function measurements for a single patient and convenience clinical samples. Identifying the determinants of graft failure with a dynamic approach may bring an original perspective to the traditional graft survival risk prediction model that are impeded by their reliance on low-granularity datasets, cross-sectional parameters, and limited follow-up.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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No intervention
Kidney recipients aged over 18 and of all sexes recruited from 2004 in European, North American and South American centers, who have estimated glomerular filtration rate and proteinuria follow-up and data from protocol and for cause biopsies for allograft survival assessment; Randomized controlled trials conducted over the past 20 years with available data on protocol biopsy within the first year and follow-up, clinical, biological and histological data.
Eligibility Criteria
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Inclusion Criteria
* Kidney recipients over 18 years of age
* Kidney recipients with at least two estimated glomerular filtration rate and proteinuria measurements after transplantation
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Paris Translational Research Center for Organ Transplantation
OTHER
Responsible Party
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Principal Investigators
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Alexandre Loupy, Professor
Role: PRINCIPAL_INVESTIGATOR
Paris Translational Research Center for Organ Transplantation
Locations
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Department of Medicine, Division of Nephrology, Comprehensive Transplant Center, Cedars Sinai Medical Center
Los Angeles, California, United States
Division of Transplantation, Department of Surgery, Feinberg School of Medicine, Northwestern University
Chicago, Illinois, United States
Department of Surgery, Johns Hopkins University School of Medicine
Baltimore, Maryland, United States
William J. von Liebig Center for Transplantation and Clinical Regeneration, Mayo Clinic
Rochester, Minnesota, United States
Albert Einstein College of Medicine, Renal Division Montefiore Medical Center, Kidney Transplantation Program
New York, New York, United States
Unidad de Trasplante Renopáncreas, Centro de Educación Médica e Investigaciones Clínicas
Buenos Aires, , Argentina
Universidade Federal de São Paulo, Hospital do Rim, Escola Paulista de Medicina
São Paulo, , Brazil
Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Renal Transplantation Service
São Paulo, , Brazil
Clinica Alemana de Santiago
Santiago, , Chile
Department of Nephrology, Arterial Hypertension, Dialysis and Transplantation, University Hospital Centre Zagreb, School od Medicine University of Zagreb
Zagreb, , Croatia
Department of Nephrology, Centre Hospitalier Universitaire de Montpellier
Montpellier, , France
Nephrology Dialysis Transplantation Department, University of Lorraine, Centre Hospitalier Universitaire de Nancy
Nancy, , France
Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris
Paris, , France
Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris
Paris, , France
Department of Transplantation, Nephrology and Clinical Immunology, Hôpital Foch
Suresnes, , France
Department of Nephrology and Organ Transplantation, Centre Hospitalier Universitaire Rangueil
Toulouse, , France
Bretonneau Hospital, Nephrology and Immunology Department
Tours, , France
Department of Nephrology, Hospital del Mar
Barcelona, , Spain
Countries
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References
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Raynaud M, Aubert O, Divard G, Reese PP, Kamar N, Yoo D, Chin CS, Bailly E, Buchler M, Ladriere M, Le Quintrec M, Delahousse M, Juric I, Basic-Jukic N, Crespo M, Silva HT Jr, Linhares K, Ribeiro de Castro MC, Soler Pujol G, Empana JP, Ulloa C, Akalin E, Bohmig G, Huang E, Stegall MD, Bentall AJ, Montgomery RA, Jordan SC, Oberbauer R, Segev DL, Friedewald JJ, Jouven X, Legendre C, Lefaucheur C, Loupy A. Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study. Lancet Digit Health. 2021 Dec;3(12):e795-e805. doi: 10.1016/S2589-7500(21)00209-0. Epub 2021 Oct 28.
Related Links
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Paris Transplant Group Website
Other Identifiers
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DYNAKT
Identifier Type: -
Identifier Source: org_study_id
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