1. Maximizing utility of nondirected living liver donor grafts using machine learning.
- Author
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Bambha K, Kim NJ, Sturdevant M, Perkins JD, Kling C, Bakthavatsalam R, Healey P, Dick A, Reyes JD, and Biggins SW
- Subjects
- Humans, Living Donors, Retrospective Studies, Liver Transplantation adverse effects, Liver Failure
- Abstract
Objective: There is an unmet need for optimizing hepatic allograft allocation from nondirected living liver donors (ND-LLD)., Materials and Method: Using OPTN living donor liver transplant (LDLT) data (1/1/2000-12/31/2019), we identified 6328 LDLTs (4621 right, 644 left, 1063 left-lateral grafts). Random forest survival models were constructed to predict 10-year graft survival for each of the 3 graft types., Results: Donor-to-recipient body surface area ratio was an important predictor in all 3 models. Other predictors in all 3 models were: malignant diagnosis, medical location at LDLT (inpatient/ICU), and moderate ascites. Biliary atresia was important in left and left-lateral graft models. Re-transplant was important in right graft models. C-index for 10-year graft survival predictions for the 3 models were: 0.70 (left-lateral); 0.63 (left); 0.61 (right). Similar C-indices were found for 1-, 3-, and 5-year graft survivals. Comparison of model predictions to actual 10-year graft survivals demonstrated that the predicted upper quartile survival group in each model had significantly better actual 10-year graft survival compared to the lower quartiles (p<0.005)., Conclusion: When applied in clinical context, our models assist with the identification and stratification of potential recipients for hepatic grafts from ND-LLD based on predicted graft survivals, while accounting for complex donor-recipient interactions. These analyses highlight the unmet need for granular data collection and machine learning modeling to identify potential recipients who have the best predicted transplant outcomes with ND-LLD grafts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Bambha, Kim, Sturdevant, Perkins, Kling, Bakthavatsalam, Healey, Dick, Reyes and Biggins.)
- Published
- 2023
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