Predicting Liver Allograft Discard: The Discard Risk Index

Abbas Rana, Rohini R. Sigireddi, Karim J. Halazun, Aishwarya Kothare, Meng Fen Wu, Hao Liu, Michael L. Kueht, John M. Vierling, Norman L. Sussman, Ayse L. Mindikoglu, Tamir Miloh, N. Thao N. Galvan, Ronald T. Cotton, Christine A. O'Mahony, John A. Goss

Research output: Contribution to journalArticle

Abstract

Background An index that predicts liver allograft discard can effectively grade allografts and can be used to preferentially allocate marginal allografts to aggressive centers. The aim of this study is to devise an index to predict liver allograft discard using only risk factors available at the time of initial DonorNet offer. Methods Using univariate and multivariate analyses on a training set of 72 297 deceased donors, we identified independent risk factors for liver allograft discard. Multiple imputation was used to account for missing variables. Results We identified 15 factors as significant predictors of liver allograft discard; the most significant risk factors were: total bilirubin > 10 mg/dL (odds ratio [OR], 25.23; confidence interval [CI], 17.32-36.77), donation after circulatory death (OR, 14.13; CI, 13.30-15.01), and total bilirubin 5 to 10 mg/dL (OR, 7.57; 95% CI, 6.32-9.05). The resulting Discard Risk Index (DSRI) accurately predicted the risk of liver discard with a C statistic of 0.80. We internally validated the model with a validation set of 37 243 deceased donors and also achieved a 0.80 C statistic. At a DSRI at the 90th percentile, the discard rate was 50% (OR, 32.34; CI, 28.63-36.53), whereas at a DSRI at 10th percentile, only 3% of livers were discarded. Conclusions The use of the DSRI can help predict liver allograft discard. The DSRI can be used to effectively grade allografts and preferentially allocate marginal allografts to aggressive centers to maximize the donor yield and expedite allocation.

Original languageEnglish (US)
Pages (from-to)1520-1529
Number of pages10
JournalTransplantation
Volume102
Issue number9
DOIs
StatePublished - Sep 1 2018
Externally publishedYes

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Allografts
Liver
Odds Ratio
Confidence Intervals
Bilirubin
Multivariate Analysis

ASJC Scopus subject areas

  • Transplantation

Cite this

Rana, A., Sigireddi, R. R., Halazun, K. J., Kothare, A., Wu, M. F., Liu, H., ... Goss, J. A. (2018). Predicting Liver Allograft Discard: The Discard Risk Index. Transplantation, 102(9), 1520-1529. https://doi.org/10.1097/TP.0000000000002151

Predicting Liver Allograft Discard : The Discard Risk Index. / Rana, Abbas; Sigireddi, Rohini R.; Halazun, Karim J.; Kothare, Aishwarya; Wu, Meng Fen; Liu, Hao; Kueht, Michael L.; Vierling, John M.; Sussman, Norman L.; Mindikoglu, Ayse L.; Miloh, Tamir; Galvan, N. Thao N.; Cotton, Ronald T.; O'Mahony, Christine A.; Goss, John A.

In: Transplantation, Vol. 102, No. 9, 01.09.2018, p. 1520-1529.

Research output: Contribution to journalArticle

Rana, A, Sigireddi, RR, Halazun, KJ, Kothare, A, Wu, MF, Liu, H, Kueht, ML, Vierling, JM, Sussman, NL, Mindikoglu, AL, Miloh, T, Galvan, NTN, Cotton, RT, O'Mahony, CA & Goss, JA 2018, 'Predicting Liver Allograft Discard: The Discard Risk Index', Transplantation, vol. 102, no. 9, pp. 1520-1529. https://doi.org/10.1097/TP.0000000000002151
Rana A, Sigireddi RR, Halazun KJ, Kothare A, Wu MF, Liu H et al. Predicting Liver Allograft Discard: The Discard Risk Index. Transplantation. 2018 Sep 1;102(9):1520-1529. https://doi.org/10.1097/TP.0000000000002151
Rana, Abbas ; Sigireddi, Rohini R. ; Halazun, Karim J. ; Kothare, Aishwarya ; Wu, Meng Fen ; Liu, Hao ; Kueht, Michael L. ; Vierling, John M. ; Sussman, Norman L. ; Mindikoglu, Ayse L. ; Miloh, Tamir ; Galvan, N. Thao N. ; Cotton, Ronald T. ; O'Mahony, Christine A. ; Goss, John A. / Predicting Liver Allograft Discard : The Discard Risk Index. In: Transplantation. 2018 ; Vol. 102, No. 9. pp. 1520-1529.
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abstract = "Background An index that predicts liver allograft discard can effectively grade allografts and can be used to preferentially allocate marginal allografts to aggressive centers. The aim of this study is to devise an index to predict liver allograft discard using only risk factors available at the time of initial DonorNet offer. Methods Using univariate and multivariate analyses on a training set of 72 297 deceased donors, we identified independent risk factors for liver allograft discard. Multiple imputation was used to account for missing variables. Results We identified 15 factors as significant predictors of liver allograft discard; the most significant risk factors were: total bilirubin > 10 mg/dL (odds ratio [OR], 25.23; confidence interval [CI], 17.32-36.77), donation after circulatory death (OR, 14.13; CI, 13.30-15.01), and total bilirubin 5 to 10 mg/dL (OR, 7.57; 95{\%} CI, 6.32-9.05). The resulting Discard Risk Index (DSRI) accurately predicted the risk of liver discard with a C statistic of 0.80. We internally validated the model with a validation set of 37 243 deceased donors and also achieved a 0.80 C statistic. At a DSRI at the 90th percentile, the discard rate was 50{\%} (OR, 32.34; CI, 28.63-36.53), whereas at a DSRI at 10th percentile, only 3{\%} of livers were discarded. Conclusions The use of the DSRI can help predict liver allograft discard. The DSRI can be used to effectively grade allografts and preferentially allocate marginal allografts to aggressive centers to maximize the donor yield and expedite allocation.",
author = "Abbas Rana and Sigireddi, {Rohini R.} and Halazun, {Karim J.} and Aishwarya Kothare and Wu, {Meng Fen} and Hao Liu and Kueht, {Michael L.} and Vierling, {John M.} and Sussman, {Norman L.} and Mindikoglu, {Ayse L.} and Tamir Miloh and Galvan, {N. Thao N.} and Cotton, {Ronald T.} and O'Mahony, {Christine A.} and Goss, {John A.}",
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T1 - Predicting Liver Allograft Discard

T2 - The Discard Risk Index

AU - Rana, Abbas

AU - Sigireddi, Rohini R.

AU - Halazun, Karim J.

AU - Kothare, Aishwarya

AU - Wu, Meng Fen

AU - Liu, Hao

AU - Kueht, Michael L.

AU - Vierling, John M.

AU - Sussman, Norman L.

AU - Mindikoglu, Ayse L.

AU - Miloh, Tamir

AU - Galvan, N. Thao N.

AU - Cotton, Ronald T.

AU - O'Mahony, Christine A.

AU - Goss, John A.

PY - 2018/9/1

Y1 - 2018/9/1

N2 - Background An index that predicts liver allograft discard can effectively grade allografts and can be used to preferentially allocate marginal allografts to aggressive centers. The aim of this study is to devise an index to predict liver allograft discard using only risk factors available at the time of initial DonorNet offer. Methods Using univariate and multivariate analyses on a training set of 72 297 deceased donors, we identified independent risk factors for liver allograft discard. Multiple imputation was used to account for missing variables. Results We identified 15 factors as significant predictors of liver allograft discard; the most significant risk factors were: total bilirubin > 10 mg/dL (odds ratio [OR], 25.23; confidence interval [CI], 17.32-36.77), donation after circulatory death (OR, 14.13; CI, 13.30-15.01), and total bilirubin 5 to 10 mg/dL (OR, 7.57; 95% CI, 6.32-9.05). The resulting Discard Risk Index (DSRI) accurately predicted the risk of liver discard with a C statistic of 0.80. We internally validated the model with a validation set of 37 243 deceased donors and also achieved a 0.80 C statistic. At a DSRI at the 90th percentile, the discard rate was 50% (OR, 32.34; CI, 28.63-36.53), whereas at a DSRI at 10th percentile, only 3% of livers were discarded. Conclusions The use of the DSRI can help predict liver allograft discard. The DSRI can be used to effectively grade allografts and preferentially allocate marginal allografts to aggressive centers to maximize the donor yield and expedite allocation.

AB - Background An index that predicts liver allograft discard can effectively grade allografts and can be used to preferentially allocate marginal allografts to aggressive centers. The aim of this study is to devise an index to predict liver allograft discard using only risk factors available at the time of initial DonorNet offer. Methods Using univariate and multivariate analyses on a training set of 72 297 deceased donors, we identified independent risk factors for liver allograft discard. Multiple imputation was used to account for missing variables. Results We identified 15 factors as significant predictors of liver allograft discard; the most significant risk factors were: total bilirubin > 10 mg/dL (odds ratio [OR], 25.23; confidence interval [CI], 17.32-36.77), donation after circulatory death (OR, 14.13; CI, 13.30-15.01), and total bilirubin 5 to 10 mg/dL (OR, 7.57; 95% CI, 6.32-9.05). The resulting Discard Risk Index (DSRI) accurately predicted the risk of liver discard with a C statistic of 0.80. We internally validated the model with a validation set of 37 243 deceased donors and also achieved a 0.80 C statistic. At a DSRI at the 90th percentile, the discard rate was 50% (OR, 32.34; CI, 28.63-36.53), whereas at a DSRI at 10th percentile, only 3% of livers were discarded. Conclusions The use of the DSRI can help predict liver allograft discard. The DSRI can be used to effectively grade allografts and preferentially allocate marginal allografts to aggressive centers to maximize the donor yield and expedite allocation.

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