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.

A kidney paired donation (KPD) pool consists of transplant candidates and their incompatible donors along with non-directed 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; our 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.

As proof of concept, we simulate a revised kidney allocation system that includes deceased donor (DD) kidneys as chain‐initiating kidneys (DD‐CIK) in a kidney paired donation pool (KPDP), and estimate potential increases in number of transplants. We consider chains of length 2 in which the DD‐CIK gives to a candidate in the KPDP, and that candidate's incompatible donor donates to theDD waitlist. In simulations, we vary initial pool size, arrival rates of candidate/donor pairs and (living) nondirected donors (NDDs), and delay time from entry to the KPDP until a candidate is eligible to receive a DD‐CIK. Using data on candidate/donor pairs and NDDs from the Alliance for Paired Kidney Donation, and the actual DDs from the Scientific Registry of Transplant Recipients (SRTR) data, simulations extend over 2 years. With an initial pool of 400, respective candidate and NDD arrival rates of 2 per day and 3 per month, and delay times for access to DD‐CIK of 6 months or less, including DD‐CIKs increases the number of transplants by at least 447 over 2 years, and greatly reduces waiting times of KPDP candidates. Potential effects on waitlist candidates are discussed as are policy and ethical issues.

While there is a growing need for kidney transplants to treat end stage kidney disease, the supply of transplantable kidneys is in serious shortage. Kidney paired donation (KPD) programs serve as platforms for candidates with willing but incompatible donors to assess the possibility of exchanging donors, thus opening up new transplant opportunities for these candidates. In recent years, non-directed (or altruistic) donors (NDDs) have been incorporated into KPD programs beginning chains of transplants that benefit many candidates. In such programs, making optimal decisions in transplant exchange selection is of critical importance. With the aim of improving the selection of chains beginning with an NDD, this paper introduces a look-ahead multiple decision strategy to select chains, that are easy to extend in the future. Simulation studies are adopted to assess performance of this strategy. Taking into account the extensibility of chains increases the number of realized transplants.

In kidney paired donation (KPD), incompatible donor-candidate pairs and non-directed (also known as altruistic) donors are pooled together with the aim of maximizing the total utility of transplants realized via donor exchanges. We consider a setting in which disjoint sets of potential transplants are selected at regular intervals, with fallback options available within each proposed set in the case of individual donor, candidate or match failure. We develop methods for calculating the expected utility for such sets under a realistic probability model for the KPD. Exact expected utility calculations for these sets are compared to estimates based on Monte Carlo samples of the underlying network. Models and methods are extended to include transplant candidates who join KPD with more than one incompatible donor. Microsimulations demonstrate the superiority of accounting for failure probability and fallback options, as well as candidates joining with additional donors, in terms of realized transplants and waiting time for candidates.

Kidney paired donation is a partial solution to overcoming biological incompatibility preventing kidney transplants. A kidney paired donation (KPD) program consists of altruistic or non-directed donors (NDDs) and pairs, each of which comprises a candidate in need of a kidney transplant and her/his willing but incompatible donor. Potential transplants from NDDs or donors in pairs to compatible candidates in other pairs are determined by computer assessment, though various situations involving either the donor, candidate, or proposed transplant may lead to a potential transplant failing to proceed. A KPD program can be viewed as a directed graph with NDDs and pairs as vertices and potential transplants as edges, where failure probabilities are associated with each vertex and edge. Transplants are carried out in the form of directed cycles among pairs and directed paths initiated by NDDs, which we refer to respectively as cycles and chains. Previous research shows that selecting disjoint subgraphs with a view to creating fallback options when failures occur generates more realized transplants than optimal selection of disjoint chains and cycles. In this paper, we define such subgraphs, which are called locally relevant (LR) subgraphs, and present an efficient algorithm to enumerate all LR subgraphs. Its computational efficiency is significantly better than the previous, more restrictive, algorithms.

Background: Multiple sclerosis (MS) is a lifelong neurological disorder requiring care in a variety of settings. The purpose of this study is to describe preferences of general practitioners (GPs) with regards to providing care for MS patients. Methods: A stratified sample of 900 GPs in the province of Quebec were sent a questionnaire, with 266 returning completed questionnaires. Respondents were surveyed about their preferences using four clinical scenarios describing hypothetical patients experiencing different stages of MS. Respondents were asked whether they would continue managing the patient themselves, formally refer the patient to a specialist, or seek specialist advice. Results: In two scenarios representing stable courses, 40.9% and 61.6% of GPs, respectively, intended to manage the patient themselves. GPs who reported having experience with MS patients were more likely to report an intention to continue management. In one scenario, GPs operating in rural areas were less likely to consider management than those in the Montreal metropolitan area (odds ratio = 0.422, 95% confidence interval 0.20-0.90). Conclusions: For MS patients with a stable disease course, an important proportion of GPs appear to be willing to manage long-term care for MS patients.RÉSUMÉ: Préférences des médecins généralistes concernant la prise en charge des patients atteints de sclérose en plaques. Contexte : La sclérose en plaques (SP) est une maladie neurologique qui nécessite des soins tout au long de la vie, dans plusieurs contextes. Le but de cette étude était de décrire les préférences des médecins généralistes (MG) concernant les soins à prodiguer aux patients atteints de SP. Méthode : Un questionnaire a été envoyé à un échantillon stratifié de 900 MG de la province de Québec. Deux cent soixante-six questionnaires complétés ont été retournés. Le questionnaire portait sur leurs préférences évaluées au moyen de quatre scénarios cliniques décrivant des patients hypothétiques à différents stades de la SP. On demandait aux répondants s'ils continueraient à traiter le patient eux-mêmes, s'ils référeraient le patient à un spécialiste ou s'ils demanderaient conseil auprès d'un spécialiste. Résultats : Dans deux scénarios où l'état du patient était stable, 40,9% et 61,6% des MG respectivement avaient l'intention de traiter euxmêmes le patient. Les MG qui rapportaient qu'ils avaient de l'expérience dans le traitement des patients atteints de SP étaient plus susceptibles de rapporter qu'ils avaient l'intention de continuer à traites le patient. Dans un scénario, les MG travaillant en milieu rural étaient moins susceptibles de considérer traiter le patient eux-mêmes que ceux qui travaillaient dans la région métropolitaine de Montréal (rapport de cotes = 0,422 ; intervalle de confiance de 0,20 à 0,90). Conclusions : Une importante proportion des MG semble disposée à suivre à long terme les patients atteints de SP dont la maladie est stable.

Background and objectives:The aim in kidney paired donation (KPD) is typically to maximize the number of transplants achieved through the exchange of donors in a pool comprising incompatible donor-candidate pairs and non-directed (or altruistic) donors. With many possible options in a KPD pool at any given time, the most appropriate set of exchanges cannot be determined by simple inspection. In practice, computer algorithms are used to determine the optimal set of exchanges to pursue. Here, we present our software application, KPDGUI (Kidney Paired Donation Graphical User Interface), for management and optimization of KPD programs.Methods: While proprietary software platforms for managing KPD programs exist to provide solutions to the standard KPD problem, our application implements newly investigated optimization criteria that account for uncertainty regarding the viability of selected transplants and arrange for fallback options in cases where potential exchanges cannot proceed, with intuitive resources for visualizing alternative optimization solutions. Results:We illustrate the advantage of accounting for uncertainty and arranging for fallback options in KPD using our application through a case study involving real data from a paired