From the American Medical Association:
A MATHEMATICAL MODEL SUGGESTS THAT A NATIONAL KIDNEY PAIRED DONATION PROGRAM WOULD PROVIDE MORE MATCHES FOR PREVIOUSLY INCOMPATIBLE RECIPIENTS AND DONORS
CHICAGO—A mathematical simulation model suggests that implementation of a national kidney paired donation program would provide a greater number and quality of matches for recipients and donors that were incompatible, according to a study in the April 20 issue of JAMA.
Kidney transplantation has emerged as the treatment of choice for medically suitable patients with end-stage kidney disease, according to background information in the article. More than 60,000 patients await kidney transplantation and are listed on the United Network for Organ Sharing (UNOS) recipient registry. Live donor kidney transplantation represents the most promising solution for closing the gap between organ supply and demand. Unfortunately, about one-third of patients with willing live donors will be excluded from kidney transplantation because of blood type or tissue incompatibility.
Kidney paired donation (KPD) offers an incompatible donor/recipient pair the opportunity to match with another donor and recipient in a similar situation. In the United States, these exchanges are currently performed at few institutions, with matches identified through local or regional patient databases. UNOS has recently proposed a national live donor KPD program through the Organ Procurement and Transplantation Network, but regulatory obstacles to a national program still exist; therefore, no data exist regarding the impact of national vs. regional programs.
Dorry L. Segev, M.D., of the Johns Hopkins University School of Medicine, Baltimore, and colleagues developed a novel kidney donor matching algorithm using optimization, a mathematical technology used in various applications. They then created a mathematical model that uses simulated pools of incompatible donor/recipient pairs to determine if their new matching algorithm might improve matches that can be found in a small (regional) or large (national) pool. The researchers compared the optimized algorithm with the scheme currently used in some centers and regions. The model included simulated patients from the general community with characteristics drawn from distributions describing end-stage kidney disease patients eligible for kidney transplantation and their willing and eligible live donors.
The researchers found that a national optimized matching algorithm would result in more transplants (47.7 percent vs. 42.0 percent), better matches, and more grafts surviving at 5 years when compared with an extension of the currently used first-accept scheme to a national level. Highly sensitized patients, who are extremely difficult to match and typically wait almost 7 years for a deceased donor kidney, would benefit 6-fold from a national optimized algorithm (14.1 percent vs. 2.3 percent). Furthermore, to alleviate concerns that a national KPD program would require extensive travel to accommodate matches, the study shows how optimization would dramatically reduce the number of pairs required to travel (2.9 percent vs. 18.4 percent).
"Even if only 7 percent of patients awaiting kidney transplantation participated in an optimized national KPD program, the health care system could save as much as $750 million," the authors write. "Our simulations suggest that approximately 47 percent of incompatible pairs could be matched through an optimized national KPD program."
"Determining optimal allocation priorities and algorithms is absolutely crucial to the smart proliferation of KPD in the United States and the prevention of a haphazard system that diminishes the impact of this promising approach to the organ shortage," the researchers write. "We believe that KPD should be the preferred treatment for patients who have incompatibilities with their intended donors who wish to participate, as KPD is less expensive than desensitization and requires less immunosuppression." (JAMA. 2005;293:1883-1890. Available at jama.com)
Editor's Note: Dr. Segev is funded by an American Society of Transplant Surgeons Fellowship in transplantation. Co-author Ms. Gentry is funded by a U.S. Department of Energy Computational Science Graduate Fellowship.
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