TY - JOUR
T1 - Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic
T2 - A stochastic simulation and machine learning study
AU - Massie, Allan B.
AU - Boyarsky, Brian J.
AU - Werbel, William A.
AU - Bae, Sunjae
AU - Chow, Eric K.H.
AU - Avery, Robin K.
AU - Durand, Christine M.
AU - Desai, Niraj
AU - Brennan, Daniel
AU - Garonzik-Wang, Jacqueline M.
AU - Segev, Dorry L.
N1 - Funding Information:
This work was supported by grant number K01KD101677 (Massie), K23DK115908 (Garonzik‐Wang), and K24DK101828 (Segev) from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The analyses described here are the responsibility of the authors alone and do not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. 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 author(s) and in no way should be seen as an official policy of or interpretation by the SRTR or the US Government.
Funding Information:
This work was supported by grant number K01KD101677 (Massie), K23DK115908 (Garonzik-Wang), and K24DK101828 (Segev) from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The analyses described here are the responsibility of the authors alone and do not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. 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 author(s) and in no way should be seen as an official policy of or interpretation by the SRTR or the US Government.
Publisher Copyright:
© 2020 The American Society of Transplantation and the American Society of Transplant Surgeons
PY - 2020/11/1
Y1 - 2020/11/1
N2 - Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our poor understanding of these risks, many centers have paused or reduced KT activity, yet data to inform such decisions are lacking. To quantify the benefit/harm of KT in this context, we conducted a simulation study of immediate-KT vs delay-until-after-pandemic for different patient phenotypes under a variety of potential COVID-19 scenarios. A calculator was implemented (http://www.transplantmodels.com/covid_sim), and machine learning approaches were used to evaluate the important aspects of our modeling. Characteristics of the pandemic (acquisition risk, CFR) and length of delay (length of pandemic, waitlist priority when modeling deceased donor KT) had greatest influence on benefit/harm. In most scenarios of COVID-19 dynamics and patient characteristics, immediate KT provided survival benefit; KT only began showing evidence of harm in scenarios where CFRs were substantially higher for KT recipients (eg, ≥50% fatality) than for waitlist registrants. Our simulations suggest that KT could be beneficial in many centers if local resources allow, and our calculator can help identify patients who would benefit most. Furthermore, as the pandemic evolves, our calculator can update these predictions.
AB - Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our poor understanding of these risks, many centers have paused or reduced KT activity, yet data to inform such decisions are lacking. To quantify the benefit/harm of KT in this context, we conducted a simulation study of immediate-KT vs delay-until-after-pandemic for different patient phenotypes under a variety of potential COVID-19 scenarios. A calculator was implemented (http://www.transplantmodels.com/covid_sim), and machine learning approaches were used to evaluate the important aspects of our modeling. Characteristics of the pandemic (acquisition risk, CFR) and length of delay (length of pandemic, waitlist priority when modeling deceased donor KT) had greatest influence on benefit/harm. In most scenarios of COVID-19 dynamics and patient characteristics, immediate KT provided survival benefit; KT only began showing evidence of harm in scenarios where CFRs were substantially higher for KT recipients (eg, ≥50% fatality) than for waitlist registrants. Our simulations suggest that KT could be beneficial in many centers if local resources allow, and our calculator can help identify patients who would benefit most. Furthermore, as the pandemic evolves, our calculator can update these predictions.
KW - Scientific Registry for Transplant Recipients (SRTR)
KW - clinical research/practice
KW - infection and infectious agents
KW - kidney transplantation/nephrology
UR - http://www.scopus.com/inward/record.url?scp=85087878197&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087878197&partnerID=8YFLogxK
U2 - 10.1111/ajt.16117
DO - 10.1111/ajt.16117
M3 - Article
C2 - 32515544
AN - SCOPUS:85087878197
VL - 20
SP - 2997
EP - 3007
JO - American Journal of Transplantation
JF - American Journal of Transplantation
SN - 1600-6135
IS - 11
ER -