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Assessing survival post-kidney transplantation in Australia: A multivariable prediction model
Lachlan C McMichael1,2,3,4, Aarti Gulyani1,5, Philip A Clayton1,2,4
1Transplant Research Epidemiology Group (TrEG), Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia.
Nephrology (Carlton, Vic.)
|November 28, 2023
Summary
A new model predicts kidney transplant survival, improving comparisons of access to this life-saving procedure for kidney failure patients. This tool aids in assessing transplant suitability and promoting equitable organ access.
Area of Science:
- Nephrology
- Transplant Surgery
- Biostatistics
Background:
- Kidney transplantation is the optimal treatment for kidney failure.
- Access to kidney transplantation varies significantly among eligible patients.
- Accurate methods are needed to compare transplantation access and outcomes.
Purpose of the Study:
- To develop and validate a predictive model for post-kidney transplant survival.
- To inform comparisons of access to kidney transplantation.
- To enhance the assessment of suitability for kidney transplantation.
Main Methods:
- Utilized demographic and clinical data from the Australia and New Zealand Dialysis and Transplant Registry (2000-2020).
- Included adult deceased donor kidney-only transplant recipients.
- Employed Cox proportional hazards regression, evaluated using Harrell's C-statistic and calibration plots.
Main Results:
- The final model incorporated recipient, donor, and transplant-related variables.
- The model demonstrated good discrimination (C-statistic 0.70-0.72) and calibration.
- Included 11,302 participants, with 62.8% male and 45.6% with glomerulonephritis as the cause of kidney disease.
Conclusions:
- A robust statistical model for predicting post-kidney transplant survival in Australian patients was developed.
- The model facilitates improved assessment of transplant suitability.
- Survival estimates derived from the model can enhance equity in organ transplantation access assessments.
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