Paris Translational Centre for Organ Transplantation
Paris, Île-de-France Region, 75015, France
NCT Number: NCT04918199
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).
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Notify Me18 year and older
All sexes
Observational
Paris, Île-de-France Region, 75015, France
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.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
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.
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,
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.
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.
Time frame: 7 years
Fleiss kappa will be used to measure inter-rater agreement between each physician's ranking
Paris Translational Research Center for Organ Transplantation
Other
Computer Based, vs Human Based Assessment of Kidney Allograft Failure Prediction and Stratification
Acronym: iBox vs Human
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