In the modern era, kidney transplantation is a safe and effective treatment for many patients with kidney failure. However, choosing the right patients for kidney transplantation is difficult, especially among older patients. Very few older patients are placed on the transplant waiting list, although those who do receive transplants survive longer than if they had stayed on dialysis. Furthermore, older adults who are referred and counseled for transplantation can receive organs from live donors or from expanded criteria deceased donors that are not typically suitable for younger patients due to their shortened allograft life spans. As such, increasing referral of older adults for transplantation might expand the use of this modality for older adults without worsening the organ shortage for younger patients. The central problem is that selecting the appropriate older patients for transplantation is difficult. Even the best transplant risk prediction models currently available are based on all patients who undergo transplants, of whom only a small fraction are older adults. As such, these prediction models can miss effects specific to older patients. We hypothesize that the inability to quantify the complexities of physiology and multi-morbidity specific to older patients, combined with a historic perception of poor outcomes for older patients, causes clinical decision-making by these patients and their providers to be subjective and possibly overly restrictive, resulting in decreased access in a population that likely stands to benefit greatly from transplantation. In an effort to improve clinical decision-making and access to transplantation in older patients, we propose to build novel prediction models for identifying older patients who are appropriate candidates for transplantation. We will then explore patterns in access to transplantation for older adults by level of appropriateness as determined using these prediction models, with the hopes of identifying subgroups of appropriate older candidates who currently lack access to transplantation. Finally, we will estimate potential Medicare savings that might result from referral of appropriate older candidates who currently lack access to transplantation. Understanding risk prediction and access to kidney transplantation in older patients will allow for the development of educational programs, interventions, and policy modifications to increase access for those older adults to stand to benefit from it.
Although kidney transplantation is safe, effective, and life-extending for many patients, older adults (65 or over) have significantly less access to transplantation than their younger counterparts. We suspect that this occurs because deciding which older adults are appropriate candidates is difficult, and no good tools exist to help with this decision. Since over 50% of dialysis patients are 65 or older, equal access to transplantation for this subgroup is important. The goal of this project is to better understand transplant risk specific to older adults and how this relates to access disparities, so that interventions and education can be designed.
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