Planning for Uncertainty and Fallbacks Can Increase the Number of Transplants

[Clark]

http://onlinelibrary.wiley.com/doi/10.1111/ajt.13413/abstract

Planning for Uncertainty and Fallbacks Can Increase the Number of Transplants in a Kidney-Paired Donation Program
M. Bray, W. Wang, P. X.-K. Song, A. B. Leichtman, M. A. Rees, V. B. Ashby, R. Eikstadt, A. Goulding, J. D. Kalbfleisch

DOI: 10.1111/ajt.13413

A kidney-paired donation (KPD) pool consists of transplant candidates and their incompatible donors, along with nondirected donors (NDDs). In a match run, exchanges are arranged among pairs in the pool via cycles, as well as chains created from NDDs. A problem of importance is how to arrange cycles and chains to optimize the number of transplants. We outline and examine, through example and by simulation, four schemes for selecting potential matches in a realistic model of a KPD system; proposed schemes take account of probabilities that chosen transplants may not be completed as well as allowing for contingency plans when the optimal solution fails. Using data on candidate/donor pairs and NDDs from the Alliance for Paired Donation, the simulations extend over 8 match runs, with 30 pairs and 1 NDD added between each run. Schemes that incorporate uncertainties and fallbacks into the selection process yield substantially more transplants on average, increasing the number of transplants by as much as 40% compared to a standard selection scheme. The gain depends on the degree of uncertainty in the system. The proposed approaches can be easily implemented and provide substantial advantages over current KPD matching algorithms.

[Clark]

http://onlinelibrary.wiley.com/doi/10.1111/ajt.13414/full

Editorial
The Best-Laid Schemes of Mice and Men Often Go Awry; How Should We Repair Them?
S. E. Gentry, D. L. Segev

DOI: 10.1111/ajt.13414
American Journal of Transplantation
Optimization algorithms have played a central role in matching for kidney paired donation to achieve the greatest benefit [1]. In practice in the United States, matches selected using optimization are frequently scuttled, either because one or more of the pairs has already matched in a different registry, or because a donor turns out to be unacceptable to, or has a positive crossmatch with, a matched recipient [2]. These failed matches pose a challenge for matching systems: what should then be done with the pairs involved?

...the regrettable consequence of having multiple competing KPD registries in the United States, with many pairs listed in more than one registry, is that the registries drive each other to perform match runs very frequently. The more frequent the match runs, the less static optimization can contribute to increasing transplant opportunities. If a registry performs a match run every time a new pair joins, then all of the static optimization methods that have ever been described in the transplantation literature are rendered useless. There has been a race to the bottom in that registries forced by competition to perform match runs very frequently cannot take advantage of mathematical optimization, and likely fewer transplants are accomplished nationwide as a result. A different approach, dynamic optimization, could conceivably allow frequent match runs without compromising the number of transplants performed, but dynamic methods have not taken hold in practice.