DJ GOODMAN1, S ULLAH2,3, SP MCDONALD2,3,
1 Department of Nephrology St Vincent’s Hospital Melbourne, Fitzroy, Victoria, 2 ANZDATA Registry, Adelaide, South Australia, 3 Adelaide Medical School, University of Adelaide, Adelaide, South Australia.
Aims: To identify risk factors at the time of transplantation that predict graft and patient survival (G/PS) for recipients with T2DM to generate a “risk calculator”.
Background: TSANZ guidelines recommend 5-year PS of ≥80% before listing for deceased donor kidney transplantation but no Australian and New Zealand based tool is available to assist in risk calculation.
Methods: Data for all adult first transplants recipients between 2005-2014 was extracted from ANZDATA registry. Age, gender, BMI, smoking, history of coronary artery disease (CAD), cerebrovascular disease (CVD) and peripheral vascular disease (PVD), indigenous status, dialysis duration, donor source and HLA matching. A multivariate Cox model was used to predict G/PS.
Results: We developed 3 models to predict G/PS of increasing complexity. Model 1 (4 variables) included recipient age and gender, donor age and indigenous status. Model 2 (9 variables) added smoking, CAD, CVD, PVD and biopsy proven diabetic nephropathy. Model 3 (13 variables) added donor source, dialysis time, cold ischaemia time and HLA mismatch. The inclusion of more variables improved the predictive ability for 5y G/PS from C statistics of 0.61 for model 1 to 0.66 for model 3.
Conclusions: The risk factors that influence G/PS vary between T2DM and non-T2DM recipients. We have generated a simple tool with good predictive ability to assist clinicians in determining suitability for transplantation. The models with variables apparent only at the time of transplant listing (model 1 & 2) have limited predictive ability. We plan to validate model 3 using data from overseas data registries and produce an “app” to make the model user friendly.