Sex disparity in liver allocation within Eurotransplant.

In Eurotransplant, relatively more females than males die while waiting for liver transplantation, and relatively fewer females undergo transplantation. With adult liver transplantation candidates listed between 2007 and 2019 (n = 21 170), we study whether sex disparity is inherent to the model for end-stage liver disease (MELD) scoring system, or the indirect result of a small candidate body size limiting access to transplantation. Cox proportional hazard models are used to quantify the direct effect of sex on waitlist mortality, independent of the effect of sex through MELD scores, and the direct effect of sex on the transplantation rate, independent of the effect of sex through MELD and candidate body size. Adjusted waitlist mortality hazard ratios (HRs) for female sex are insignificant (HR: 1.03, 95% CI: 0.88-1.20). We thus lack evidence that MELD systematically underestimates waitlist mortality rates for females. Transplantation rates are 25% lower for females than males in unadjusted analyses (HR: 0.74, 95% CI: 0.71-0.77), but HRs become insignificant with adjustment for mediators (HR: 0.98, 95% CI: 0.93-1.04), most importantly candidate body size. Sex disparity in Eurotransplant thus appears to be largely a consequence of lower transplantation rates for females, which are explained by sex differences in body size.

Immunized Patients Face Reduced Access to Transplantation in the Eurotransplant Kidney Allocation System.

BACKGROUND: The presence of donor-specific HLA antibodies before transplantation is associated with poor transplantation outcomes. Unacceptable antigens can be assigned for Eurotransplant kidney transplant candidates to prevent kidney offers against which the candidate has developed clinically relevant HLA antibodies. This retrospective cohort study aimed to assess to what degree unacceptable antigens affect access to transplantation in the Eurotransplant Kidney Allocation System (ETKAS). METHODS: Candidates who underwent kidney-only transplantation between 2016 and 2020 were included (n = 19 240). Cox regression was used to quantify the relationship between the relative transplantation rate and virtual panel-reactive antibodies (vPRAs), which is the percentage of the donor pool with unacceptable antigens. Models used accrued dialysis time as the timescale; were stratified by country and blood group of patient and were adjusted for nontransplantable status, patient age, sex, history of kidney transplantations, and prevalence of 0 HLA-DR-mismatched donors. RESULTS: Transplantation rates were 23% lower for vPRA 0.1% to 50%, 51% lower for vPRA 75% to 85%, and decreased rapidly for vPRA of >85%. Prior studies showed significantly lower ETKAS transplantation rates only for highly sensitized patients (vPRA of >85%). The inverse relationship between transplantation rate and vPRA is independent of Eurotransplant country, listing time, and 0 HLA-DR-mismatched donor availability. Results were similar when quantifying the relationship between vPRA and attainment of a sufficiently high rank for an ETKAS offer, suggesting lower transplantation rates for immunized patients are due to current ETKAS allocation. CONCLUSIONS: Immunized patients face lower transplantation rates across Eurotransplant. The current ETKAS allocation mechanism inadequately compensates immunized patients for reduced access to transplantation.

Building Kidney Exchange Programmes in Europe-An Overview of Exchange Practice and Activities.

BACKGROUND: Considerable differences exist among the living donor Kidney Exchange Programmes (KEPs) that are in use and being built in Europe, contributing to a variation in the number of living donor transplants (Newsletter Transplant; International figures on donation and transplantation 2016). Efforts of European KEPs to exchange (best) practices and share approaches to address challenges have, however, been limited. METHODS: Experts from 23 European countries, collaborating on the European Network for Collaboration on Kidney Exchange Programmes Cooperation on Science and Technology Action, developed a questionnaire to collect detailed information on the functioning of all existing KEPs in Europe, as well as their opportunities and challenges. Following a comparative analysis, results were synthesized and interpreted by the same experts. RESULTS: The practices, opportunities and challenges reported by 17 European countries reveal that some of the 10 operating programs are mature, whereas others are in earlier stages of development. Over 1300 transplants were performed through existing KEPs up to the end of 2016, providing approximately 8% of their countries' living kidney donations in 2015. All countries report challenges to either initiating KEPs or increasing volumes. Some challenges are shared, whereas others differ because of differences in context (eg, country size, effectiveness of deceased donor program) and ethical and legal considerations (eg, regarding living donation as such, nonrelated donors, and altruistic donation). Transnational initiatives have started in Central Europe, Scandinavia, and Southern Europe. CONCLUSIONS: Exchange of best practices and shared advancement of national programs to address existing challenges, aided by transnational exchanges, may substantially improve access to the most (cost) effective treatment for the increasing number of patients suffering from kidney disease.

Testing Probabilistic Models of Choice using Column Generation.

In so-called random preference models of probabilistic choice, a decision maker chooses according to an unspecified probability distribution over preference states. The most prominent case arises when preference states are linear orders or weak orders of the choice alternatives. The literature has documented that actually evaluating whether decision makers' observed choices are consistent with such a probabilistic model of choice poses computational difficulties. This severely limits the possible scale of empirical work in behavioral economics and related disciplines. We propose a family of column generation based algorithms for performing such tests. We evaluate our algorithms on various sets of instances. We observe substantial improvements in computation time and conclude that we can efficiently test substantially larger data sets than previously possible.