Predicting One-year Kidney Graft Failure and Death with Cardiovascular and Immunological Factors

Cardiovascular and immunological factors increase the levels of uncertainty and risk associated with transplantation. Kidney transplant programs are reluctant to risk performing transplant surgery on high risk candidates because of poor outcomes. Patients with high risk have limited access to kidney transplantation in spite of possible survival benefits of kidney transplantation. We developed four predictive models according to donor types (living donor- and deceased donor-) and transplant outcomes (graft failure and patient death) using national transplant registry data (Scientific Registry Transplant Recipients, n = 218,657) which have different probabilities of one-year kidney graft failure and death compared to the currently used models. We showed that by including two more risk factors in the analyses that current models underestimate predicted risks. The two factors were cardiovascular comorbidities and immunological barriers. The predictive models showed risk of high risk candidates were underestimated by current predictive models. If transplant community used our models, they would find that predicted risk of failure is higher and more generous. Then, more high risk patients could have access to kidney transplantation without the transplant programs’ jeopardizing theirs status as high quality programs. The predictive models were shown to be valid and reliable.These models will help (1) quantify risks of transplant outcomes in high-risk candidates, (2) screen the most appropriate candidates and eventually, (3) improve accessibility of kidney transplantation and (4) better utilize the most limited and scarce resources, donated kidneys.