PROJECT SUMMARY / ABSTRACT: Survival with end-stage kidney disease (ESKD) has improved in the last
decade alongside the trend of an aging population with greater risks, including cancer. Therefore, optimal
management for patients with both ESKD and cancer (affecting at least 7% of the > 130,000 annual incident
ESKD patients) is of increasing public health importance. Kidney transplantation confers substantial survival
benefit over dialysis for patients with ESKD, but the immunosuppression doubles the risk of cancer compared
to the general population. Nephrologists face a dilemma to when evaluating transplant candidates who have a
previous history of cancer, because while most active malignancies are considered a contraindication to
transplantation due to high mortality risk, the recommended waiting time to transplant for patients in remission
is based largely on expert opinion and low-grade evidence. The resulting uncertainty in the context of the
current organ shortage makes providers reluctant to transplant kidney patients with a history of cancer. Yet, for
many of these patients, the risk of dying while on dialysis likely exceeds the risk conferred by their cancer
recurrence. There are little data available to transplant centers to guide decisions about listing patients with
kidney failure in remission from cancer, and nephrologists face a critical need to better serve patients with
ESKD by improving predictions of pre- and post-transplant outcomes. This proposal will provide personalized
risk estimates to nephrologists in a clinically useful, publicly available format. Models will estimate the “tipping
point” for an individual, when the risk of waiting longer for surveillance exceeds the risk of immunosuppression.
These estimates will be communicated in a free, user-friendly, online tool for use by transplant programs to
precisely guide decisions about listing kidney transplant candidates with a history of cancer. Multiple data
sources with be used to address potential bias: The United States Renal Data System (USRDS), Transplant
Cancer Match (TCM) Study, and US cancer registries. Aim 1 will estimate mortality risk in waitlisted kidney
transplant candidates with a history of cancer, comparing those who are transplanted vs. not yet transplanted
using data from the TCM Study. Aim 2 will estimate mortality risk in ESKD patients with a history of cancer who
are not yet listed for transplant, compared to patients in the TCM Study who were transplanted, using a novel
linkage between the USRDS database and US cancer registries. Aim 3 will develop a Clinician Decision
Support website that incorporates the mortality estimates developed in Aims 1 and 2 into a free user-friendly,
online interface for nephrologists to use in transplant candidate waitlisting decisions. This proposal fills an
immediate need to inform decisions that balance the risk of death on dialysis with the risk of cancer recurrence
after transplant. The novel database linkage also creates wide-ranging potential for future investigations into
the association between ESKD and cancer. Thus, this proposal aligns well with the NIDDK mission to improve
the lives of patients with chronic kidney disease, and will extend the scientific reach of the USRDS.
