The econometrics of deceased kidney donation

Two papers have made me think about the power of econometric methods applied to studies of medical issues related to matching deceased donor kidneys to patients.

I recently heard Chuck Manski give a seminar on this paper published last year in PNAS:

One thing I took away from it is that proportional hazard (Cox) models are very popular in the medical literature, but they assume that effects (e.g. rejection of a graft) are proportional to time, and there are immunological processes that don't in fact have a constant hazard rate, but build up over time, so that isn't a good model for those things.

Predicting kidney transplant outcomes with partial knowledge of HLA mismatch

Charles F. Manski,  Anat R. Tambur, and Michael Gmeiner, PNAS October 8, 2019 116 (41) 20339-20345

"Abstract: We consider prediction of graft survival when a kidney from a deceased donor is transplanted into a recipient, with a focus on the variation of survival with degree of human leukocyte antigen (HLA) mismatch. Previous studies have used data from the Scientific Registry of Transplant Recipients (SRTR) to predict survival conditional on partial characterization of HLA mismatch. Whereas earlier studies assumed proportional hazards models, we used nonparametric regression methods. These do not make the unrealistic assumption that relative risks are invariant as a function of time since transplant, and hence should be more accurate. To refine the predictions possible with partial knowledge of HLA mismatch, it has been suggested that HaploStats statistics on the frequencies of haplotypes within specified ethnic/national populations be used to impute complete HLA types. We counsel against this, showing that it cannot improve predictions on average and sometimes yields suboptimal transplant decisions. We show that the HaploStats frequency statistics are nevertheless useful when combined appropriately with the SRTR data. Analysis of the ecological inference problem shows that informative bounds on graft survival probabilities conditional on refined HLA typing are achievable by combining SRTR and HaploStats data with immunological knowledge of the relative effects of mismatch at different HLA loci."

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And here's a recent working paper that says that if we want to maximize life years added by transplant, more organs should go more quickly to healthier patients:

Choices and Outcomes in Assignment Mechanisms: The Allocation of Deceased Donor Kidneys

Nikhil Agarwal, Charles Hodgson, Paulo Somaini, August 17, 2020

"Abstract: While the mechanism design paradigm emphasizes notions of efficiency based on agent preferences, policymakers often focus on alternative objectives. School districts emphasize educational achievement; and transplantation communities focus on patient survival. However, it is unclear whether choice-based mechanisms perform well when assessed using these outcomes. This paper evaluates the assignment mechanism for allocating deceased donor kidneys on the basis of the additional patient life-years from transplantion (LYFT). We examine the role of choice in increasing LYFT and compare equilibrium assignments to benchmarks that remove choice. Our approach combines a model of choice and outcomes in order to study how selection induced in the mechanism produces the outcome of

interest, LYFT. We show how to identify and estimate the model using quasi-experimental variation resulting from the mechanism. The estimates suggest that the design in use selects patients with better survival prospects after a transplant and matches them well. It results in an average LYFT of 7.97, which is 0.88 years higher than a random assignment. However, there is scope for increasing the aggregate LYFT to 12.07. While some of this increase can be achieved by assigning transplanted patients to different donors, realizing the majority requires transplanting relatively healthy patients, who would have longer life-expectancy even without a transplant. Therefore, a policymaker faces a dilemma between transplanting patients that are sicker and those for whom life will be extended the longest."