DeathmBoxNCT06531967
Predicting Mortality in Kidney Transplant Recipients
An observational study of Death, run by Paris Translational Research Center for Organ Transplantation at 11 sites in 4 countries.
Trial summary
Accurately predicting kidney recipient risk of death has a crucial interest because of the organ shortage, the need to optimize allograft allocation by identifying high-risk patients who may not benefit from a transplant and improve the clinical decision-making after transplant to ensure that each patient survives as… Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- Death
- How many people
- 13,000 participants
- Where
- 11 sitesin 4 countries
- Study dates
- 1 Jan 2004to 1 Aug 2024
- 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: Adult, de novo, kidney recipients who received only a kidney transplant
Who may be able to join
- Adult kidney recipients
Who cannot join
- Multi-organ transplantation
- Prior kidney transplant
Trial locations and contacts
11 sites in 4 countries.
11 sites in 4 countries
France5 sites
Necker hospital
Paris
Saint-Louis hospital
Paris
Tenon hospital
Paris
Department of Nephrology and Organ Transplantation, Toulouse University Hospital
Toulouse
Department of Nephrology and Clinical Immunology, University Hospital of Tours
Tours
United States3 sites
Penn Transplant Institute, Hospital of the University of Pennsylvania
Philadelphia, Pennsylvania, 19104
Department of Medicine, Mayo Clinic
Phoenix, Arizona, 85054
Bakar Computational Health Sciences Institute, University of California
San Francisco, California, 94158
Belgium2 sites
Department of Nephrology and Renal Transplantation, University Hospitals Leuven
Leuven
Division of Nephrology, University Hospital Liège (CHU)
Liège
Netherlands1 site
Leiden Transplant Center, Leiden University Medical Center
Leiden
About this study
Official title: Development and Validation of a Prediction Model for Risk of Death in Kidney Transplant Recipients
Accurately predicting kidney recipient risk of death has a crucial interest because of the organ shortage, the need to optimize allograft allocation by identifying high-risk patients who may not benefit from a transplant and improve the clinical decision-making after transplant to ensure that each patient survives as long as possible.
However, according to a literature review the investigators performed, studies attempting to develop a kidney recipient death prediction model suffer from many shortcomings, including the lack of key risk factors, use of biased registry data, small sample size, lack of external validation in different countries and subpopulations, and short follow-up.
The present study thus aimed to address these limitations and develop a robust, generalizable kidney recipient death prediction model.
Read the detailed description
The number of individuals suffering from end-stage chronic renal disease (ESRD) worldwide has increased over time, exceeding seven million of patients in 2020. For individuals with ESRD, kidney transplantation is the best treatment in terms of patient survival, quality of life and from a cost-effective standpoint, as compared with dialysis, even in comorbid or elderly populations.
Although the number of kidney transplantations performed each year has increased as well, it follows a lower pace than the increase of individuals on the waiting-list, resulting in an organ shortage. There is therefore a need to optimize allograft allocation by identifying the high-risk patients who may not benefit from a transplant and improve the clinical decision-making after transplant to ensure that each patient survives as long as possible.
In this context, a kidney recipient death prediction model may improve transplant clinical practice, allowing for the ability to evaluate the individual risk of post transplant mortality, already before undergoing transplantation, thereby guiding decision making. However, developing such a model is a very difficult task, as death after kidney transplantation depends on many parameters, such as donor age, history or cause of death, imaging parameters, patients' past medical history (e.g. diabetes, dialysis duration, hypertension), patients' biological parameters, as well as the function of the allograft, which depends on patients' immunological factors, or allograft related parameters such as HLA mismatches or cold ischemia time.
The goal of the present study was therefore to identify the determinants of death after kidney transplantation, and to develop and validate a prediction model that would help optimize allograft allocation and post-transplant patient management, using a large, international, highly phenotyped cohort of kidney recipients with extensive data collection and long-term follow-up.
- Conditions
- Death
- Being tested
- No intervention
- Medical subject headings
- Death
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
No intervention
| Study group | Role | What they receive |
|---|---|---|
| Necker hospital from Paris, France | Kidney recipients from Necker hospital Receives: Other: No intervention | |
| Saint-Louis hospital from Paris, France | Kidney recipients from Saint-Louis hospital Receives: Other: No intervention | |
| Bichat hospital from Paris, France | Kidney recipients from Bichat hospital Receives: Other: No intervention | |
| Bretonneau hospital from Tours, France | Kidney recipients from Bretonneau hospital Receives: Other: No intervention | |
| Toulouse hospital, France | Kidney recipients from Toulouse hospital Receives: Other: No intervention | |
| KU Leuven, Belgium | Kidney recipients from KU Leuven Receives: Other: No intervention | |
| Liege hospital from Belgium | Kidney recipients from Liege hospital Receives: Other: No intervention | |
| Leiden University Medical Center from the Netherlands | Kidney recipients from Leiden University Medical Center Receives: Other: No intervention | |
| Hospital of the University of Pennsylvania from Philadelphia, US | Kidney recipients from Hospital of the University of Pennsylvania Receives: Other: No intervention | |
| Mayo Clinic from Phoenix, US | Kidney recipients from Mayo Clinic Receives: Other: No intervention | |
| UCSF database | Kidney recipients data from real-world UCSF database Receives: Other: No intervention | |
| AP-HP database | Kidney recipients data from real-world AP-HP database Receives: Other: No intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
Patient death
Patient death
Measured: Up to 10 years after kidney transplantation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Aug 2024
- Study start1 Jan 2004
- Primary completion1 Jun 2024
- Study completion1 Aug 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for DeathStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
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
- 13,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Paris Translational Research Center for Organ Transplantation
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Alexandre Loupy, Principal investigator, Paris Institute for Transplantation and Organ Regeneration (PITOR)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06531967
- Sponsor's protocol ID
- mBox_001
- Acronym
- mBox
- Status last verified
- Jul 2024
- First submitted
- 25 Jul 2024
- Last updated
- 1 Aug 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 1 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of a Prediction Model for Risk of Death in Kidney Transplant Recipients
- ClinicalTrials.gov ID
- NCT06531967
- Acronym / sponsor ID
- mBox / mBox_001
- Conditions
- Death
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 13,000 participants (estimated)
- Lead sponsor
- Paris Translational Research Center for Organ TransplantationUniversity, hospital or other
- Study start
- 1 Jan 2004 (actual)
- Primary completion
- 1 Jun 2024 (actual)
- Study completion
- 1 Aug 2024 (estimated)
- First posted
- 1 Aug 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Accurately predicting kidney recipient risk of death has a crucial interest because of the organ shortage, the need to optimize allograft allocation by identifying high-risk patients who may not benefit from a transplant and improve the clinical decision-making after transplant to ensure that each patient survives as long as possible.
However, according to a literature review the investigators performed, studies attempting to develop a kidney recipient death prediction model suffer from many shortcomings, including the lack of key risk factors, use of biased registry data, small sample size, lack of external validation in different countries and subpopulations, and short follow-up.
The present study thus aimed to address these limitations and develop a robust, generalizable kidney recipient death prediction model.
Detailed description
The number of individuals suffering from end-stage chronic renal disease (ESRD) worldwide has increased over time, exceeding seven million of patients in 2020. For individuals with ESRD, kidney transplantation is the best treatment in terms of patient survival, quality of life and from a cost-effective standpoint, as compared with dialysis, even in comorbid or elderly populations.
Although the number of kidney transplantations performed each year has increased as well, it follows a lower pace than the increase of individuals on the waiting-list, resulting in an organ shortage. There is therefore a need to optimize allograft allocation by identifying the high-risk patients who may not benefit from a transplant and improve the clinical decision-making after transplant to ensure that each patient survives as long as possible.
In this context, a kidney recipient death prediction model may improve transplant clinical practice, allowing for the ability to evaluate the individual risk of post transplant mortality, already before undergoing transplantation, thereby guiding decision making. However, developing such a model is a very difficult task, as death after kidney transplantation depends on many parameters, such as donor age, history or cause of death, imaging parameters, patients' past medical history (e.g. diabetes, dialysis duration, hypertension), patients' biological parameters, as well as the function of the allograft, which depends on patients' immunological factors, or allograft related parameters such as HLA mismatches or cold ischemia time.
The goal of the present study was therefore to identify the determinants of death after kidney transplantation, and to develop and validate a prediction model that would help optimize allograft allocation and post-transplant patient management, using a large, international, highly phenotyped cohort of kidney recipients with extensive data collection and long-term follow-up.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 12
| Arm | Type | Receives |
|---|---|---|
| Necker hospital from Paris, France | – | Other: No interventionKidney recipients from Necker hospital |
| Saint-Louis hospital from Paris, France | – | Other: No interventionKidney recipients from Saint-Louis hospital |
| Bichat hospital from Paris, France | – | Other: No interventionKidney recipients from Bichat hospital |
| Bretonneau hospital from Tours, France | – | Other: No interventionKidney recipients from Bretonneau hospital |
| Toulouse hospital, France | – | Other: No interventionKidney recipients from Toulouse hospital |
| KU Leuven, Belgium | – | Other: No interventionKidney recipients from KU Leuven |
| Liege hospital from Belgium | – | Other: No interventionKidney recipients from Liege hospital |
| Leiden University Medical Center from the Netherlands | – | Other: No interventionKidney recipients from Leiden University Medical Center |
| Hospital of the University of Pennsylvania from Philadelphia, US | – | Other: No interventionKidney recipients from Hospital of the University of Pennsylvania |
| Mayo Clinic from Phoenix, US | – | Other: No interventionKidney recipients from Mayo Clinic |
| UCSF database | – | Other: No interventionKidney recipients data from real-world UCSF database |
| AP-HP database | – | Other: No interventionKidney recipients data from real-world AP-HP database |
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult, de novo, kidney recipients who received only a kidney transplant
Key inclusion criteria (1 listed)
- Adult kidney recipients
Key exclusion criteria (2 listed)
- Multi-organ transplantation
- Prior kidney transplant
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| No interventionNo intervention | Other | AP-HP database, Bichat hospital from Paris, France, Bretonneau hospital from Tours, France, Hospital of the University of Pennsylvania from Philadelphia, US, KU Leuven, Belgium, Leiden University Medical Center from the Netherlands, Liege hospital from Belgium, Mayo Clinic from Phoenix, US, Necker hospital from Paris, France, Saint-Louis hospital from Paris, France, Toulouse hospital, France, UCSF database |
Primary outcome
Patient death
Time frame: Up to 10 years after kidney transplantation
Patient death
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 1 Aug 2024.
- Individual participant dataSharing planned: Undecided
Related trials for Death
Not yet recruiting
Miniature In-line Respirator
Brain Death, Respiration, Artificial
Active, not recruitingPhase 2
Treating Muscle-invasive Bladder Cancer With A Non-surgical Method Consisting of Anti-PD-1 Therapy and Chemoradiation
Muscle-Invasive Bladder Carcinoma, Programmed Cell Death Protein 1 Inhibitor
RecruitingPhase 3
ROSETTA Breast-01: The Effects and Safety of Pumitamig in Patients With Triple-Negative Breast Cancer
Breast Neoplasms
Not yet recruitingPhase 1/2
STAR0602 With Nivolumab in Non Small Cell Lung Cancer and in Metastatic Castrate-Resistant Prostate Cancer, and STAR0602 Alone in Thymic Carcinoma
NSCLC, Non-Small Cell Lung Cancer
Active, not recruitingPhase 4
Improving Neonatal Health Through Rapid Malaria Testing in Early Pregnancy With High-Sensitivity Diagnostics
Malaria,Falciparum, Malaria in Pregnancy
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Alexandre Loupy principal investigator
Paris Institute for Transplantation and Organ Regeneration (PITOR)
11 sites in 4 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Death, run by Paris Translational Research Center for Organ Transplantation at 11 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 1 inclusion and 2 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: status not confirmed, as of the sponsor's last update on 1 Aug 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 11 sites in France, United States, Belgium, Netherlands. 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?
Results are not available in the source record.
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?
Patient death (time frame: Up to 10 years after kidney transplantation). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 1 Aug 2024.