Faculty Bibliography

BACKGROUND AND AIMS:Scores from the Model for End-Stage Liver Disease (MELD), which are used to prioritize candidates for deceased donor livers, are widely acknowledged to be negatively correlated with the 90-day survival rate without a liver transplant. However, inconsistent and outdated estimates of survival probabilities by MELD preclude useful applications of the MELD score. APPROACH AND RESULTS:Using data from all prevalent liver waitlist candidates from 2016 to 2019, we estimated 3-day, 7-day, 14-day, 30-day, and 90-day without-transplant survival probabilities (with confidence intervals) for each MELD score and status 1A. We used an adjusted Kaplan-Meier model to avoid unrealistic assumptions and multiple observations per person instead of just the observation at listing. We found that 90-day without-transplant survival has improved over the last decade, with survival rates increasing >10% (in absolute terms) for some MELD scores. We demonstrated that MELD correctly prioritizes candidates in terms of without-transplant survival probability but that status 1A candidates' short-term without-transplant survival is higher than that of MELD 40 candidates and lower than that of MELD 39 candidates. Our primary result is the updated survival functions themselves. CONCLUSIONS:We calculated without-transplant survival probabilities for each MELD score (and status 1A). The survival function is an invaluable tool for many applications in liver transplantation: awarding of exception points, calculating the relative demand for deceased donor livers in different geographic areas, calibrating the pediatric end-stage liver disease score, and deciding whether to accept an offered liver.

BACKGROUND AND AIMS:In February 2020, the Organ Procurement and Transplantation Network replaced donor service area-based allocation of livers with acuity circles, a system based on three homogeneous circles around each donor hospital. This system has been criticized for neglecting to consider varying population density and proximity to coast and national borders. APPROACH AND RESULTS:Using Scientific Registry of Transplant Recipients data from July 2013 to June 2017, we designed heterogeneous circles to reduce both circle size and variation in liver supply/demand ratios across transplant centers. We weighted liver demand by Model for End-Stage Liver Disease (MELD)/Pediatric End-Stage Liver Disease (PELD) because higher MELD/PELD candidates are more likely to be transplanted. Transplant centers in the West had the largest circles; transplant centers in the Midwest and South had the smallest circles. Supply/demand ratios ranged from 0.471 to 0.655 livers per MELD-weighted incident candidate. Our heterogeneous circles had lower variation in supply/demand ratios than homogeneous circles of any radius between 150 and 1,000 nautical miles (nm). Homogeneous circles of 500 nm, the largest circle used in the acuity circles allocation system, had a variance in supply/demand ratios 16 times higher than our heterogeneous circles (0.0156 vs. 0.0009) and a range of supply/demand ratios 2.3 times higher than our heterogeneous circles (0.421 vs. 0.184). Our heterogeneous circles had a median (interquartile range) radius of only 326 (275-470) nm but reduced disparities in supply/demand ratios significantly by accounting for population density, national borders, and geographic variation of supply and demand. CONCLUSIONS:Large homogeneous circles create logistical burdens on transplant centers that do not need them, whereas small homogeneous circles increase geographic disparity. Using carefully designed heterogeneous circles can reduce geographic disparity in liver supply/demand ratios compared with homogeneous circles of radius ranging from 150 to 1,000 nm.

Recently, the Organ Procurement and Transplant Network approved a plan to allocate kidneys within 250-nm circles around donor hospitals. These homogeneous circles might not substantially reduce geographic differences in transplant rates because deceased donor kidney supply and demand differ across the country. Using Scientific Registry of Transplant Recipients data from 2016-2019, we used an integer program to design unique, heterogeneous circles with sizes between 100 and 500 nm that reduced supply/demand ratio variation across transplant centers. We weighted demand according to wait time because candidates who have waited longer have higher priority. We compared supply/demand ratios and average travel distance of kidneys, using heterogeneous circles and 250 and 500-nm fixed-distance homogeneous circles. We found that 40% of circles could be 250 nm or smaller, while reducing supply/demand ratio variation more than homogeneous circles. Supply/demand ratios across centers for heterogeneous circles ranged from 0.06 to 0.13 kidneys per wait-year, compared to 0.04 to 0.47 and 0.05 to 0.15 kidneys per wait-year for 250-nm and 500-nm homogeneous circles, respectively. The average travel distance for kidneys using heterogeneous, and 250-nm and 500-nm fixed-distance circles was 173 nm, 134 nm, and 269 nm, respectively. Heterogeneous circles reduce geographic disparity compared to homogeneous circles, while maintaining reasonable travel distances.

BACKGROUND:In December 2018, United Network for Organ Sharing approved an allocation scheme based on recipients' geographic distance from a deceased donor (acuity circles [ACs]). Previous analyses suggested that ACs would reduce waitlist mortality overall, but their impact on pediatric subgroups was not considered. METHODS:We applied Scientific Registry of Transplant Recipients data from 2011 to 2016 toward the Liver Simulated Allocation Model to compare outcomes by age and illness severity for the United Network for Organ Sharing-approved AC and the existing donor service area-/region-based allocation schemes. Means from each allocation scheme were compared using matched-pairs t tests. RESULTS:During a 3-year period, AC allocation is projected to decrease waitlist deaths in infants (39 versus 55; P < 0.001), children (32 versus 50; P < 0.001), and teenagers (15 versus 25; P < 0.001). AC allocation would increase the number of transplants in infants (707 versus 560; P < 0.001), children (677 versus 547; P < 0.001), and teenagers (404 versus 248; P < 0.001). AC allocation led to decreased median pediatric end-stage liver disease/model for end-stage liver disease at transplant for infants (29 versus 30; P = 0.01), children (26 versus 29; P < 0.001), and teenagers (26 versus 31; P < 0.001). Additionally, AC allocation would lead to fewer transplants in status 1B in children (97 versus 103; P = 0.006) but not infants or teenagers. With AC allocation, 77% of pediatric donor organs would be allocated to pediatric candidates, compared to only 46% in donor service area-/region-based allocation (P < 0.001). CONCLUSIONS:AC allocation will likely address disparities for pediatric liver transplant candidates and recipients by increasing transplants and decreasing waitlist mortality. It is more consistent with federally mandated requirements for organ allocation.

OBJECTIVE:To describe how overly simple conceptualisations of how research is translated into public health policy impact impair effective translation. To suggest how alternative approaches to conceptualising impact, which incorporate recent developments in social and political sciences, can help stakeholders improve translation of high-quality public health research into policy impact. STUDY DESIGN/METHODS:Researchers often describe generating impact in terms of linear or cyclical models, in which the production of scientific findings alone compels action and leads to impact. However, such conceptualisations do not appear to have supported improved translation of research into policy and practice. Improving understanding of how research impact is achieved may identify areas stakeholders seeking to achieve impact could target. METHODS:Overview of theoretical and practical approaches to achieving public health policy impact from research. RESULTS:Despite much evidence that translating research into public health policy is more complex than linear and cyclical models suggest, stakeholders often revert to these heuristics, that is shorthand ways of thinking that allow simple but inaccurate answers to complex problems. This leads to potentially missing opportunities for impact, such as conducting research in collaboration with local policy makers and contributing ideas to the wider narrative through the media and public engagement. CONCLUSION/CONCLUSIONS:The process of translating research into impact appears more complex than that suggested by linear and cyclical models. Success involves a planned approach targeting multiple routes to impact, sustained over time.