At any given time, about 100,000 people in the U.S. are waiting to become kidney transplant recipients. Roughly one-fifth of those get a new kidney each year, but others die while waiting. In short, the demand for kidneys makes it important to think about how we use the limited supply.
A study co-authored by an MIT economist brings new data to this issue, providing nuanced estimates of the lifespan-lengthening effect of kidney transplants. That can be hard to measure well, but the study is the first to account for some of the complexities involved, including the decisions patients make when accepting kidney transplants, and some of their pre-existing health factors.
The research concludes the system in use produces an additional 9.29 life-years from transplantation (LYFT) for kidney recipients. (LYFT is the difference in median survival for those with and without transplants.) If the organs were assigned randomly to patients, the study finds, that LYFT average would only be 7.54 overall. From that perspective, the current transplant system is a net positive for patients. However, the study also finds that the LYFT figure could potentially be raised as high as 14.08, depending on how the matching system is structured.
In any case, more precise estimates about the benefits of kidney transplants can help inform policymakers about the dynamics of the matching system in use.
"There's always this question about how to take the scarce number of organs being donated and place them efficiently, and place them well," says MIT economist Nikhil Agarwal, co-author of a newly published paper detailing the study's results. As he emphasizes, the point of the paper is to inform the ongoing refinement of the matching system, rather than advocate one viewpoint or another.
The paper, "Choices and Outcomes in Assignment Mechanisms: The Allocation of Deceased Donor Kidneys," is published in the latest issue of Econometrica. The authors are Agarwal, who is a professor in MIT's Department of Economics; Charles Hodgson, an assistant professor of economics at Yale University; and Paulo Somaini, an associate professor of economics in Stanford University's Graduate School of Business.
After people die, there is a period lasting up to 48 hours when they could be viable organ donors. Potential kidney recipients are prioritized by time spent on wait-lists as well as tissue-type similarity, and can accept or reject any given transplant offer.
Over the last decade-plus, Agarwal has conducted significant empirical research on matching systems for organ donations, especially kidney transplants. To conduct this study, the researchers used comprehensive data about patients on the kidney wait-list from 2000-2010, made available by the Organ Procurement and Transplantation Network, the national U.S. registry. This allowed the scholars to analyze both the matching system and the health effects of transplants; they track patient survival until February 2020.
The work is the first quasiexperimental study of kidney transplants; by carefully examining the decision-making tendencies of kidney recipients, along with many other health factors, the scholars are able to evaluate the effects of a transplant, other things being equal. Recipients are more likely to select kidney offers from donors who are younger, lacked hypertension, died of head trauma (suggesting their internal organs were healthy), and with whom they have perfect tissue-type matches.
"The [previous] methodology of estimating what are the life-years benefits was not incorporating this selection issue," Agarwal says.
Additionally, overall, a key empirical feature of kidney transplants is that recipients who are healthier overall tend to have the largest realized life-years benefits from a transplant, meaning that the greatest increase in LYFT is not found in the set of patients with the worst health.
"You might think people who are the sickest and who are most likely to die without an organ are going to benefit the most from it [in added life-years]," Agarwal says. "But there might be some other comorbidity or factor that made them sick, and their body's going to take a toll on the new organ, so the benefits might not be as large."
With this in mind, the maximal LYFT number of 14.08 in the study comes from, broadly, a hypothetical scenario in which an increased number of otherwise healthy people receive transplants. Again, the current system tends to prioritize time spent on a wait-list. And some observers might advocate for a system that prioritizes those who are sickest. With all that in mind, the policymaking process for kidney transplants may still involve recognition that the biggest gains in patient life-years are not necessarily aligned with other prioritization factors.
"Our results indicate … a dilemma rooted in the tension between these two goals," the authors write in the paper.
To be clear, Agarwal is not advocating for any one system over another, but conducting data-driven research so that policy officials can make more fully informed decisions in the ongoing, long-term process of trying to refine valuable transplant networks.
"I don't necessarily think it's my comparative advantage to make the ethical decisions, but we can at least think about and quantify what some of the tradeoffs are," Agarwal adds.
Support for the research was provided in part by the National Science Foundation and by the Alfred P. Sloan Foundation.
