Utilizing List Exchange and Nondirected Donation through ‘Chain’ Paired Kidney Donations

Roth, Alvin E.; Sönmez, Tayfun; Ünver, M. Utku; Delmonico, Francis L.; Saidman, Susan L.

doi:10.1111/j.1600-6143.2006.01515.x

Cited by 171 publications

(127 citation statements)

References 22 publications

Supporting

Mentioning

125

Contrasting

Unclassified

Order By: Relevance

“…A use of the calculator that first motivated our investigations arises in the context of allocations in a KPD program where algorithms are developed to optimize the number of transplants or some other measure of utility (31)(32)(33)(34). An alternative approach defines the value of a potential transplant from a given donor to a given recipient as the estimated probability that the graft would survive for 5 (or 10) years.…”

Section: Discussionmentioning

confidence: 99%

A Kidney Graft Survival Calculator that Accounts for Mismatches in Age, Sex, HLA, and Body Size

Ashby

Leichtman

Rees

et al. 2017

CJASN

View full text Add to dashboard Cite

Background and objectives Outcomes for transplants from living unrelated donors are of particular interest in kidney paired donation (KPD) programs where exchanges can be arranged between incompatible donor-recipient pairs or chains created from nondirected/altruistic donors.Design, setting, participants, & measurements Using Scientific Registry of Transplant Recipients data, we analyzed 232,705 recipients of kidney-alone transplants from 1998 to 2012. Graft failure rates were estimated using Cox models for recipients of kidney transplants from living unrelated, living related, and deceased donors. Models were adjusted for year of transplant and donor and recipient characteristics, with particular attention to mismatches in age, sex, human leukocyte antigens (HLA), body size, and weight.Results The dependence of graft failure on increasing donor age was less pronounced for living-donor than for deceased-donor transplants. Male donor-to-male recipient transplants had lower graft failure, particularly better than female to male (5%-13% lower risk). HLA mismatch was important in all donor types. Obesity of both the recipient (8%-18% higher risk) and donor (5%-11% higher risk) was associated with higher graft loss, as were donor-recipient weight ratios of ,75%, compared with transplants where both parties were of similar weight (9%-12% higher risk). These models are used to create a calculator of estimated graft survival for living donors.Conclusions This calculator provides useful information to donors, candidates, and physicians of estimated outcomes and potentially in allowing candidates to choose among several living donors. It may also help inform candidates with compatible donors on the advisability of joining a KPD program.

show abstract

Section: Discussionmentioning

confidence: 99%

A Kidney Graft Survival Calculator that Accounts for Mismatches in Age, Sex, HLA, and Body Size

Ashby

Leichtman

Rees

et al. 2017

CJASN

View full text Add to dashboard Cite

show abstract

“…Fielded kidney exchanges also gain great utility through the use of chains (see, e.g., [4,14,16,17,21,22,23,28]). Chains start with an altruistic donor donating his kidney to a patient, whose paired donor donates her kidney to another patient, and so on.…”

Section: Kidney Exchange Modelmentioning

confidence: 99%

Price of Fairness in Kidney Exchange.

2014

View full text Add to dashboard Cite

Kidney exchange provides a life-saving alternative to long waiting lists for patients in need of a new kidney. Fielded exchanges typically match under utilitarian or near-utilitarian rules; this approach marginalizes certain classes of patients. In this paper, we focus on improving access to kidneys for highly-sensitized, or hard-tomatch, patients. Toward this end, we formally adapt a recently introduced measure of the tradeoff between fairness and efficiencythe price of fairness-to the standard kidney exchange model. We show that the price of fairness in the standard theoretical model is small. We then introduce two natural definitions of fairness and empirically explore the tradeoff between matching more hard-tomatch patients and the overall utility of a utilitarian matching, on real data from the UNOS nationwide kidney exchange and simulated data from each of the standard kidney exchange distributions.

show abstract

“…These pairs may have incentives to participate in PKE programs since the patient could obtain a kidney that results in higher life-expectancy than that of her donor's kidney. The participation of compatible pairs can dramatically increase the chances of finding compatible swaps for incompatible pairs, and boost the transplantation rate [11,30,32,33].…”

Section: Introductionmentioning

confidence: 99%

Age-based preferences in paired kidney exchange

Nicolò

Álvarez

2017

Games and Economic Behavior

View full text Add to dashboard Cite

We consider a model of Paired Kidney Exchange (PKE) with feasibility constraints on the number of patient-donor pairs involved in exchanges. Patients' preferences are restricted so that patients prefer kidneys from compatible younger donors to kidneys from older donors. In this framework, patients with compatible donors may enroll on PKE programs to receive an organ with higher expected graft survival than that of their intended donor. PKE rules that satisfy individual rationality, efficiency, and strategy-proofness necessarily select pairwise exchanges.Such rules maximize the number of transplantations among pairs with the youngest donors, and sequentially among pairs with donors of different age groups. JEL: C78; D02; D78; I10.

show abstract

Utilizing List Exchange and Nondirected Donation through ‘Chain’ Paired Kidney Donations

Cited by 171 publications

References 22 publications

A Kidney Graft Survival Calculator that Accounts for Mismatches in Age, Sex, HLA, and Body Size

A Kidney Graft Survival Calculator that Accounts for Mismatches in Age, Sex, HLA, and Body Size

Price of Fairness in Kidney Exchange.

Age-based preferences in paired kidney exchange

Contact Info

Product

Resources

About