TY - JOUR
T1 - Accelerating Kidney Allocation: Simultaneously Expiring Offers
AU - Mankowski, Michal A
AU - Kosztowski, Martin
AU - Raghavan, Subramanian
AU - Garonzik-Wang, Jacqueline M
AU - Axelrod, David
AU - Segev, Dorry L
AU - Gentry, Sommer E
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported by grant number R01DK111233 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Michal A. Mankowski was supported by King Abdullah University of Science and Technology (KAUST). Martin Kosztowski was supported by National Institute of Diabetes, Digestive, and Kidney Diseases (T32DK007732). The data reported here have been supplied by the Hennepin Healthcare Research Institute (HHRI) as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy of or interpretation by the SRTR, UNOS/OPTN, or the US Government.
PY - 2019/5/28
Y1 - 2019/5/28
N2 - Placing non-ideal kidneys quickly might reduce discard. We studied changing kidney allocation to eliminate sequential offers, instead making offers to multiple centers for all non-locally allocated kidneys, so that multiple centers must accept or decline within the same one hour. If more than one center accepted an offer, the kidney would go to the highest-priority accepting candidate. Using 2010 KPSAM-SRTR data, we simulated the allocation of 12,933 kidneys, excluding locally allocated and zero-mismatch kidneys. We assumed that each hour of delay decreased the probability of acceptance by 5%, and that kidneys would be discarded after 20 hours of offers beyond the local level. We simulated offering kidneys simultaneously to small, medium, and large batches of centers. Increasing the batch size increased the percentage of kidneys accepted and shortened allocation times. Going from small to large batches increased the number of kidneys accepted from 10,085 (92%) to 10,802 (98%) for low-KDPI, and from 1,257 (65%) to 1,737 (89%) for high-KDPI kidneys. The average number of offers a center received each week was 10.1 for small batches and 16.8 for large batches. Simultaneously expiring offers might allow faster allocation and decrease the number of discards, while still maintaining an acceptable screening burden. This article is protected by copyright. All rights reserved.
AB - Placing non-ideal kidneys quickly might reduce discard. We studied changing kidney allocation to eliminate sequential offers, instead making offers to multiple centers for all non-locally allocated kidneys, so that multiple centers must accept or decline within the same one hour. If more than one center accepted an offer, the kidney would go to the highest-priority accepting candidate. Using 2010 KPSAM-SRTR data, we simulated the allocation of 12,933 kidneys, excluding locally allocated and zero-mismatch kidneys. We assumed that each hour of delay decreased the probability of acceptance by 5%, and that kidneys would be discarded after 20 hours of offers beyond the local level. We simulated offering kidneys simultaneously to small, medium, and large batches of centers. Increasing the batch size increased the percentage of kidneys accepted and shortened allocation times. Going from small to large batches increased the number of kidneys accepted from 10,085 (92%) to 10,802 (98%) for low-KDPI, and from 1,257 (65%) to 1,737 (89%) for high-KDPI kidneys. The average number of offers a center received each week was 10.1 for small batches and 16.8 for large batches. Simultaneously expiring offers might allow faster allocation and decrease the number of discards, while still maintaining an acceptable screening burden. This article is protected by copyright. All rights reserved.
UR - http://hdl.handle.net/10754/631994
UR - https://onlinelibrary.wiley.com/doi/abs/10.1111/ajt.15396
U2 - 10.1111/ajt.15396
DO - 10.1111/ajt.15396
M3 - Article
C2 - 31012528
SN - 1600-6135
VL - 19
SP - 3071
EP - 3078
JO - American Journal of Transplantation
JF - American Journal of Transplantation
IS - 11
ER -