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出境医 / 临床实验 / Human Versus Computer-based Predictions of Long Allograft Survival (iBox vs Human)
Human Versus Computer-based Predictions of Long Allograft Survival (iBox vs Human)
Study Description
Brief Summary:
The clinical decision-making after kidney transplantation is mainly driven by patient individual assessment. However, this task remains difficult and uncertain due to the integration of complex and numerous parameters. We aim to evaluate and compare the ability of transplant physicians to predict long term allograft survival compared with a computer-based survival prediction algorithm (iBox system).
| Condition or disease | Intervention/treatment |
|---|---|
| Kidney Transplant Failure | Device: Computer based assessment (iBox) Other: Physician assessement |
Detailed Description:
400 kidney transplant recipients among the cohort of 4,000 patients from the Paris Transplant Group prospective kidney transplant cohort (NCT03474003) were randomly selected. We generated an anonymized electronic health record for each included patient including a total of 60 classical kidney transplant prognostic parameters comprising baseline transplant and recipient characteristics, together with post-transplant parameters including allograft function, proteinuria, histology, diagnoses, and immunological profile collected during the first-year post-transplant. The time of risk evaluation for the human and the iBox system were at 1-year post transplant and the death censored allograft survival predictions made at 7 years after risk assessment. We enrolled transplant physicians at various stages of their careers (residents, fellows and seniors) to assign death censored graft survival probabilities at 7 years post risk assessment. The physicians were blinded to the actual patient outcome (allograft failure) and the iBox predictions. The physicians-based predictions will then be compared with the iBox system, a validated computer-based kidney survival prediction system.
Study Design
| Study Type : | Observational |
| Estimated Enrollment : | 400 participants |
| Observational Model: | Cohort |
| Time Perspective: | Retrospective |
| Official Title: | Computer Based, vs Human Based Assessment of Kidney Allograft Failure Prediction and Stratification |
| Actual Study Start Date : | March 1, 2018 |
| Estimated Primary Completion Date : | December 31, 2021 |
| Estimated Study Completion Date : | December 31, 2021 |
Arms and Interventions
| Group/Cohort | Intervention/treatment |
|---|---|
|
Paris Transplant Group cohort
400 (10%) of the patients were randomly selected from 4,000 consecutive patients over 18 years of age prospectively enrolled at the time of kidney transplantation from a living or deceased donor at Necker Hospital, Saint-Louis Hospital, Foch Hospital, and Toulouse Hospital between January 1, 2005, and January 1, 2014, in France.
|
Device: Computer based assessment (iBox)
Individual allograft survival probabilities of death censored allograft survival seven years after the time of risk evaluation, computed using the iBox (NCT03474003), a qualified prognostication system designed to predict long term allograft survival up to seven years after evaluation.
Other: Physician assessement Based on anonymized electronic health records, physicians have to determine a percentage of death censored allograft survival seven years after the time of risk evaluation,
|
Outcome Measures
Primary Outcome Measures :
- Death censored allograft failure seven years after risk assessment [ Time Frame: 7 years ]Predictions performances to predict allograft failure defined as a patient's definitive return to dialysis or preemptive kidney retransplantation after risk assessment.
Secondary Outcome Measures :
- Evaluation of the parameters' importance in the prediction for physicians [ Time Frame: 7 years ]Mean decrease in accuracy from a random survival forest from each physician will be used to determine the relative importance of the first ten parameters that led to their predictions.
- Inter-rater agreement [ Time Frame: 7 years ]Fleiss kappa will be used to measure inter-rater agreement between each physician's ranking
Eligibility Criteria
| Ages Eligible for Study: | 18 Years and older (Adult, Older Adult) |
| Sexes Eligible for Study: | All |
| Accepts Healthy Volunteers: | No |
| Sampling Method: | Probability Sample |
Study Population
400 (10%) of the patients were randomly selected with an evaluation available at one-year post-transplant from the Paris Transplant Group cohort, which gathers 4,000 consecutive patients over 18 years of age prospectively enrolled at the time of kidney transplantation from a living or deceased donor at Necker Hospital, Saint-Louis Hospital, Foch Hospital, and Toulouse Hospital between January 1, 2005, and January 1, 2014, in France.
Criteria
Inclusion Criteria:
- transplant evaluation available at one year post-transplant
Exclusion Criteria:
- no
Contacts and Locations
Contacts
| Contact: Alexandre Loupy, MD, PhD | (33)612491082 | alexandre.loupy@inserm.fr | |
| Contact: Gillian Divard, MD, MPH | (33)631421663 | gillian.divard@inserm.fr |
Locations
| France | |
| Paris Translational Centre for Organ Transplantation | Recruiting |
| Paris, Île-de-France, France, 75015 | |
| Contact: Alexandre Loupy, MD, PhD (33)612491082 alexandre.loupy@inserm.fr | |
| Contact: Gillian Divard, MD, MPH (33)631421663 gillian.divard@inserm.fr | |
Sponsors and Collaborators
Paris Translational Research Center for Organ Transplantation
| Tracking Information | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| First Submitted Date | June 2, 2021 | ||||||||
| First Posted Date | June 8, 2021 | ||||||||
| Last Update Posted Date | June 8, 2021 | ||||||||
| Actual Study Start Date | March 1, 2018 | ||||||||
| Estimated Primary Completion Date | December 31, 2021 (Final data collection date for primary outcome measure) | ||||||||
| Current Primary Outcome Measures |
Death censored allograft failure seven years after risk assessment [ Time Frame: 7 years ] Predictions performances to predict allograft failure defined as a patient's definitive return to dialysis or preemptive kidney retransplantation after risk assessment.
|
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| Original Primary Outcome Measures | Same as current | ||||||||
| Change History | No Changes Posted | ||||||||
| Current Secondary Outcome Measures |
|
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| Original Secondary Outcome Measures | Same as current | ||||||||
| Current Other Pre-specified Outcome Measures | Not Provided | ||||||||
| Original Other Pre-specified Outcome Measures | Not Provided | ||||||||
| Descriptive Information | |||||||||
| Brief Title | Human Versus Computer-based Predictions of Long Allograft Survival | ||||||||
| Official Title | Computer Based, vs Human Based Assessment of Kidney Allograft Failure Prediction and Stratification | ||||||||
| Brief Summary | The clinical decision-making after kidney transplantation is mainly driven by patient individual assessment. However, this task remains difficult and uncertain due to the integration of complex and numerous parameters. We aim to evaluate and compare the ability of transplant physicians to predict long term allograft survival compared with a computer-based survival prediction algorithm (iBox system). | ||||||||
| Detailed Description | 400 kidney transplant recipients among the cohort of 4,000 patients from the Paris Transplant Group prospective kidney transplant cohort (NCT03474003) were randomly selected. We generated an anonymized electronic health record for each included patient including a total of 60 classical kidney transplant prognostic parameters comprising baseline transplant and recipient characteristics, together with post-transplant parameters including allograft function, proteinuria, histology, diagnoses, and immunological profile collected during the first-year post-transplant. The time of risk evaluation for the human and the iBox system were at 1-year post transplant and the death censored allograft survival predictions made at 7 years after risk assessment. We enrolled transplant physicians at various stages of their careers (residents, fellows and seniors) to assign death censored graft survival probabilities at 7 years post risk assessment. The physicians were blinded to the actual patient outcome (allograft failure) and the iBox predictions. The physicians-based predictions will then be compared with the iBox system, a validated computer-based kidney survival prediction system. | ||||||||
| Study Type | Observational | ||||||||
| Study Design | Observational Model: Cohort Time Perspective: Retrospective |
||||||||
| Target Follow-Up Duration | Not Provided | ||||||||
| Biospecimen | Not Provided | ||||||||
| Sampling Method | Probability Sample | ||||||||
| Study Population | 400 (10%) of the patients were randomly selected with an evaluation available at one-year post-transplant from the Paris Transplant Group cohort, which gathers 4,000 consecutive patients over 18 years of age prospectively enrolled at the time of kidney transplantation from a living or deceased donor at Necker Hospital, Saint-Louis Hospital, Foch Hospital, and Toulouse Hospital between January 1, 2005, and January 1, 2014, in France. | ||||||||
| Condition | Kidney Transplant Failure | ||||||||
| Intervention |
|
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| Study Groups/Cohorts | Paris Transplant Group cohort
400 (10%) of the patients were randomly selected from 4,000 consecutive patients over 18 years of age prospectively enrolled at the time of kidney transplantation from a living or deceased donor at Necker Hospital, Saint-Louis Hospital, Foch Hospital, and Toulouse Hospital between January 1, 2005, and January 1, 2014, in France.
Interventions:
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| Publications * | Loupy A, Aubert O, Orandi BJ, Naesens M, Bouatou Y, Raynaud M, Divard G, Jackson AM, Viglietti D, Giral M, Kamar N, Thaunat O, Morelon E, Delahousse M, Kuypers D, Hertig A, Rondeau E, Bailly E, Eskandary F, Böhmig G, Gupta G, Glotz D, Legendre C, Montgomery RA, Stegall MD, Empana JP, Jouven X, Segev DL, Lefaucheur C. Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study. BMJ. 2019 Sep 17;366:l4923. doi: 10.1136/bmj.l4923. | ||||||||
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* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline. |
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| Recruitment Information | |||||||||
| Recruitment Status | Recruiting | ||||||||
| Estimated Enrollment |
400 | ||||||||
| Original Estimated Enrollment | Same as current | ||||||||
| Estimated Study Completion Date | December 31, 2021 | ||||||||
| Estimated Primary Completion Date | December 31, 2021 (Final data collection date for primary outcome measure) | ||||||||
| Eligibility Criteria |
Inclusion Criteria:
Exclusion Criteria:
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| Sex/Gender |
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| Ages | 18 Years and older (Adult, Older Adult) | ||||||||
| Accepts Healthy Volunteers | No | ||||||||
| Contacts |
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| Listed Location Countries | France | ||||||||
| Removed Location Countries | |||||||||
| Administrative Information | |||||||||
| NCT Number | NCT04918199 | ||||||||
| Other Study ID Numbers | iBoxvsHuman | ||||||||
| Has Data Monitoring Committee | No | ||||||||
| U.S. FDA-regulated Product |
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| IPD Sharing Statement |
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| Responsible Party | Paris Translational Research Center for Organ Transplantation | ||||||||
| Study Sponsor | Paris Translational Research Center for Organ Transplantation | ||||||||
| Collaborators | Not Provided | ||||||||
| Investigators | Not Provided | ||||||||
| PRS Account | Paris Translational Research Center for Organ Transplantation | ||||||||
| Verification Date | June 2021 | ||||||||