Finding long chains in kidney exchange using the traveling salesman problem

A Systematic Review of Kidney Transplantation Decision Modelling Studies

BACKGROUND

Genome-based precision medicine strategies promise to minimize premature graft loss after renal transplantation, through precision approaches to immune compatibility matching between kidney donors and recipients. The potential adoption of this technology calls for important changes to clinical management processes and allocation policy. Such potential policy change decisions may be supported by decision models from health economics, comparative effectiveness research and operations management.

OBJECTIVE

We used a systematic approach to identify and extract information about models published in the kidney transplantation literature and provide an overview of the status of our collective model-based knowledge about the kidney transplant process.

METHODS

Database searches were conducted in MEDLINE, Embase, Web of Science and other sources, for reviews and primary studies. We reviewed all English-language papers that presented a model that could be a tool to support decision making in kidney transplantation. Data were extracted on the clinical context and modelling methods used.

RESULTS

A total of 144 studies were included, most of which focused on a single component of the transplantation process, such as immunosuppressive therapy or donor-recipient matching and organ allocation policies. Pre- and post-transplant processes have rarely been modelled together.

CONCLUSION

A whole-disease modelling approach is preferred to inform precision medicine policy, given its potential upstream implementation in the treatment pathway. This requires consideration of pre- and post-transplant natural history, risk factors for allograft dysfunction and failure, and other post-transplant outcomes. Our call is for greater collaboration across disciplines and whole-disease modelling approaches to more accurately simulate complex policy decisions about the integration of precision medicine tools in kidney transplantation.

Equity or Equality? Which Approach Brings More Satisfaction in a Kidney-Exchange Chain?

In United States (U.S.), government-funded organizations, such as NLDAC, reimburse travel and subsistence expenses incurred during living-organ donation process. However, in Iran, there is a non-governmental organization called Iranian Kidney Foundation (IKF) that funds the direct and indirect costs of donors through charitable donations and contributions from participants in the exchange program. In this article, for countries outside the U.S. that currently use an equality approach, we propose a potential new compensation-apportionment approach (equitable approach) for kidney-exchange chains and compare it with the currently available system (equality approach) in terms of the apportionment of compensation in a kidney-exchange chain to cover the expenses incurred by the initiating living donor of the chain in the act of donation. To this end, we propose a mechanism to apportion compensation among all participating pairs based on the equity approach by utilizing a prediction model to calculate the probability of graft survival in each transplant operation. These probabilities are then used to define the utility of any transplantation, considering the quality of each pair’s donated and received kidney in the chain. Afterward, the corresponding cost is apportioned by a mechanism based on the normalized differences between the utility of donated and received kidneys for each incompatible pair of the chain. In summary, we demonstrate that by utilizing the equitable approach, there is more fairness and equity in the allocation of resources in organ-procurement systems, which results in more satisfaction among incompatible pairs. Additional future prospective studies are needed to assess this proposed equitable approach for kidney-exchange chains in countries outside the U.S., such as Iran, that currently use an equality approach.

Global kidney chains

Kidney failure is among the leading causes of death worldwide, and the best treatment is transplantation. However, transplants are in short supply because of shortfalls of transplantable organs and of finances. In the United States and some other countries, kidney exchange chains have emerged as a way to increase the number of transplants; patients who have a willing donor but cannot receive that donor’s kidney can each receive a compatible kidney from another patient’s intended donor. Such programs are much better developed within the borders of wealthy countries, which is of little help to patients in countries with limited kidney transplantation or exchange. This paper proposes and analyzes a way to extend kidney exchange chains to share the benefits globally.

Kidney failure is a worldwide scourge, made more lethal by the shortage of transplants. We propose a way to organize kidney exchange chains internationally between middle-income countries with financial barriers to transplantation and high-income countries with many hard to match patients and patient–donor pairs facing lengthy dialysis. The proposal involves chains of exchange that begin in the middle-income country and end in the high-income country. We also propose a way of financing such chains using savings to US health care payers.

The Stochastic Matching Problem with (Very) Few Queries

Motivated by an application in kidney exchange , we study the following stochastic matching problem: We are given a graph G ( V, E ) (not necessarily bipartite), where each edge in E is realized with some constant probability p > 0, and the goal is to find a maximum matching in the realized graph. An algorithm in this setting is allowed to make queries to edges in E to determine whether or not they are realized.

We design an adaptive algorithm for this problem that, for any graph G , computes a (1−ε)-approximate maximum matching in the realized graph G p with high probability, while making O (log (1/ε p )/ε p ) queries per vertex, where the edges to query are chosen adaptively in O (log (1/ε p )/ε p ) rounds. We further present a non-adaptive algorithm that makes O (log (1/ε p )/ε p ) queries per vertex and computes a (1/2−ε)-approximate maximum matching in G p with high probability.

Both our adaptive and non-adaptive algorithms achieve the same approximation factor as the previous best algorithms of Blum et al. (EC 2015) for this problem, while requiring an exponentially smaller number of per-vertex queries (and rounds of adaptive queries for the adaptive algorithm). Our results settle an open problem raised by Blum et al. by achieving only a polynomial dependency on both ε and p . Moreover, the approximation guarantee of our algorithms is instance-wise as opposed to only being competitive in expectation as is the case for Blum et al. This is of particular relevance to the key application of stochastic matching in kidney exchange. We obtain our results via two main techniques—namely, matching-covers and vertex sparsification —that may be of independent interest.

Recent advances in kidney transplantation: a viewpoint from the Descartes advisory board

Transplantation medicine is a rapidly evolving field. Keeping afloat of the published literature to offer the best clinical care to our patients is a daunting task. As part of its educational mission, the Descartes advisory board identified seven topics in kidney transplantation where there has been substantial progresses over the last years: kidney allocation within Eurotransplant; kidney exchange strategies; kidney machine perfusion strategies; the changing landscape of anti-human leukocyte antigen (HLA) antibodies; the new immunosuppressive drugs in the pipeline; strategies for immunosuppression minimization; and the continuous enigma of focal segmental glomerular sclerosis recurrence after transplantation. Here, we have summarized the main knowledge and the main challenges of these seven topics with the aim to provide transplant professionals at large with key bullet points to successfully understand these new concepts.

Ant Lion Optimization algorithm for kidney exchanges

The kidney exchange programs bring new insights in the field of organ transplantation. They make the previously not allowed surgery of incompatible patient-donor pairs easier to be performed on a large scale. Mathematically, the kidney exchange is an optimization problem for the number of possible exchanges among the incompatible pairs in a given pool. Also, the optimization modeling should consider the expected quality-adjusted life of transplant candidates and the shortage of computational and operational hospital resources. In this article, we introduce a bio-inspired stochastic-based Ant Lion Optimization, ALO, algorithm to the kidney exchange space to maximize the number of feasible cycles and chains among the pool pairs. Ant Lion Optimizer-based program achieves comparable kidney exchange results to the deterministic-based approaches like integer programming. Also, ALO outperforms other stochastic-based methods such as Genetic Algorithm in terms of the efficient usage of computational resources and the quantity of resulting exchanges. Ant Lion Optimization algorithm can be adopted easily for on-line exchanges and the integration of weights for hard-to-match patients, which will improve the future decisions of kidney exchange programs. A reference implementation for ALO algorithm for kidney exchanges is written in MATLAB and is GPL licensed. It is available as free open-source software from: https://github.com/SaraEl-Metwally/ALO_algorithm_for_Kidney_Exchanges.

Ethical and Logistical Issues Raised by the Advanced Donation Program "Pay It Forward" Scheme

The advanced donation program was proposed in 2014 to allow an individual to donate a kidney in order to provide a voucher for a kidney in the future for a particular loved one. In this article, we explore the logistical and ethical issues that such a program raises. We argue that such a program is ethical in principle but there are many logistical issues that need to be addressed to ensure that the actual program is fair to both those who do and do not participate in this program.

The promise of organ and tissue preservation to transform medicine

The ability to replace organs and tissues on demand could save or improve millions of lives each year globally and create public health benefits on par with curing cancer. Unmet needs for organ and tissue preservation place enormous logistical limitations on transplantation, regenerative medicine, drug discovery, and a variety of rapidly advancing areas spanning biomedicine. A growing coalition of researchers, clinicians, advocacy organizations, academic institutions, and other stakeholders has assembled to address the unmet need for preservation advances, outlining remaining challenges and identifying areas of underinvestment and untapped opportunities. Meanwhile, recent discoveries provide proofs of principle for breakthroughs in a family of research areas surrounding biopreservation. These developments indicate that a new paradigm, integrating multiple existing preservation approaches and new technologies that have flourished in the past 10 years, could transform preservation research. Capitalizing on these opportunities will require engagement across many research areas and stakeholder groups. A coordinated effort is needed to expedite preservation advances that can transform several areas of medicine and medical science.

Strategies for long-term preservation of kidney graft function

Kidney transplantation has become a routine procedure in the treatment of patients with kidney failure, and requires collaboration of experts from different disciplines, such as nephrology, surgery, immunology, pathology, infectious disease medicine, cardiology, and oncology. Grafts can be obtained from deceased or living donors, with different logistical requirements and implications for long-term graft patency. 1-year graft survival rates are greater than 95% in many centres but improvement of long-term function remains a challenge. New developments in molecular immunology and computational biology have increased precision of donor and recipient matching of HLA and non-HLA compatibility. Individual omics-wide molecular diagnostics, extracorporeal therapies, and drug developments allow for precise individual decision making and treatment. Tolerance induction by mixed chimerism without toxic conditioning and with a low risk of graft versus host disease is a visionary but realistic goal. Some of these innovations are already used in modern transplant centres and will allow advancement in long-term allograft preservation.

Incentivizing Organ Donor Registrations with Organ Allocation Priority

How donor organs are allocated for transplant can affect their scarcity. In 2008, Israel's Parliament passed an Organ Transplantation Law granting priority on organ donor waiting lists to individuals who had previously registered as organ donors. Beginning in November 2010, public awareness campaigns advertised the priority policy to the public. Since April 2012, priority has been added to the routine medical criteria in organ allocation decisions. We evaluate the introduction of priority for registered organ donors using Israeli data on organ donor registration from 1992 to 2013. We find that registrations increased when information about the priority law was made widely available. We find an even larger increase in registration rates in the 2 months leading up to a program deadline, after which priority would only be granted with a 3-year delay. We also find that the registration rate responds positively to public awareness campaigns, to the ease of registration (i.e. allowing for registering online and by phone) and to an election drive that included placing registration opportunities in central voting locations. Copyright © 2016 John Wiley & Sons, Ltd.

Incentivizing Authorization for Deceased Organ Donation With Organ Allocation Priority: The First 5 Years

The allocation system of donor organs for transplantation may affect their scarcity. In 2008, Israel's Parliament passed the Organ Transplantation Law, which grants priority on waiting lists for transplants to candidates who are first-degree relatives of deceased organ donors or who previously registered as organ donors themselves. Several public campaigns have advertised the existence of the law since November 2010. We evaluated the effect of the law using all deceased donation requests made in Israel during the period 1998-2015. We use logistic regression to compare the authorization rates of the donors' next of kin in the periods before (1998-2010) and after (2011-2015) the public was made aware of the law. The authorization rate for donation in the period after awareness was substantially higher (55.1% vs. 45.0%, odds ratio [OR] 1.43, p = 0.0003) and reached an all-time high rate of 60.2% in 2015. This increase was mainly due to an increase in the authorization rate of next of kin of unregistered donors (51.1% vs. 42.2%). We also found that the likelihood of next-of-kin authorization for donation was approximately twice as high when the deceased relative was a registered donor rather than unregistered (89.4% vs. 44.6%, OR 14.27, p < 0.0001). We concluded that the priority law is associated with an increased authorization rate for organ donation.