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Identification and utilization of donor and recipient genetic variants to predict survival after HCT: are we ready for primetime?

ABSTRACT: Overall survival following hematopoietic cell transplantation (HCT) has improved over the past two decades through better patient selection and advances in HLA typing, supportive care, and infection prophylaxis. Nonetheless, mortality rates are still unsatisfactory and transplant-related mortality remains a major cause of death after unrelated allogeneic HCT. Since there are no known pre-HCT, non-HLA biologic predictors of survival following transplant, for over a decade, scientists have been investigating the role of non-HLA germline genetic variation in survival and treatment-related mortality after HCT. Variation in single nucleotide polymorphisms (SNPs) has the potential to impact chemotherapy, radiation, and immune responses, leading to different post-HCT survival outcomes. In this paper, we address the current knowledge of the contribution of genetic variation to survival following HCT and discuss study design and methodology for investigating HCT survival on a genomic scale.

SUBMITTER: Sucheston-Campbell LE

PROVIDER: S-EPMC4352187 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Identification and utilization of donor and recipient genetic variants to predict survival after HCT: are we ready for primetime?

Sucheston-Campbell Lara E LE Clay Alyssa A McCarthy Philip L PL Zhu Qianqian Q Preus Leah L Pasquini Marcelo M Onel Kenan K Hahn Theresa T

Current hematologic malignancy reports 20150301 1

Overall survival following hematopoietic cell transplantation (HCT) has improved over the past two decades through better patient selection and advances in HLA typing, supportive care, and infection prophylaxis. Nonetheless, mortality rates are still unsatisfactory and transplant-related mortality remains a major cause of death after unrelated allogeneic HCT. Since there are no known pre-HCT, non-HLA biologic predictors of survival following transplant, for over a decade, scientists have been in ...[more]

PMID: 25700678

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Project description:Background and objectivesSmall donor and/or kidney sizes relative to recipient size are associated with a higher risk of kidney allograft failure. Donor and recipient ages are associated with graft survival and may modulate the relationship between size mismatch and the latter. The aim of this study was to determine whether the association between donor-recipient size mismatch and graft survival differs by donor and recipient age.Design, setting, participants, & measurementWe performed a retrospective cohort study of first adult deceased donor kidney transplantations performed between 2000 and 2018 recorded in the Scientific Registry of Transplant Recipients. We used multivariable Cox proportional hazards models to assess the association between donor-recipient body surface area ratio and death-censored graft survival, defined as return to dialysis or retransplantation. We considered interactions between donor-recipient body surface area ratio and each of recipient and donor age.ResultsAmong the 136,321 kidney transplant recipients included in this study, 23,614 (17%) experienced death-censored graft loss over a median follow-up of 4.3 years (interquartile range, 1.9-7.8 years). The three-way donor-recipient body surface area ratio by donor age by recipient age interaction was statistically significant (P=0.04). The magnitude of the association between severe size mismatch (donor-recipient body surface area ratio <0.80 versus ≥1.00) and death-censored graft survival was stronger with older donor age and recipient age. In all recipient age categories except the youngest (18-30 years), 5- and 10-year graft survival rates were similar or better with a size-mismatched donor aged <40 years than a nonsize-mismatched donor aged 40 years or older.ConclusionsThe association of donor-recipient size mismatch on long-term graft survival is modulated by recipient and donor age. Size-mismatched kidneys yield excellent graft survival when the donor is young. Donor age was more strongly associated with graft survival than size mismatch.

Project description:BackgroundThe "digital era" in the field of medicine is the new "here and now". Artificial intelligence has entered many fields of medicine and is recently emerging in the field of organ transplantation. Solid organs remain a scarce resource. Being able to predict the outcome after liver transplantation promises to solve one of the long-standing problems within organ transplantation. What is the perfect donor recipient match? Within this work we developed and validated a novel deep-learning-based donor-recipient allocation system for liver transplantation.MethodIn this study we used data collected from all liver transplant patients between 2004 and 2019 at the university transplantation centre in Munich. We aimed to design a transparent and interpretable deep learning framework to predict the outcome after liver transplantation. An individually designed neural network was developed to meet the unique requirements of transplantation data. The metrics used to determine the model quality and its level of performance are accuracy, cross-entropy loss, and F1 score as well as AUC score.ResultsA total of 529 transplantations with a total of 1058 matching donor and recipient observations were added into the database. The combined prediction of all outcome parameters was 95.8% accurate (cross-entropy loss of 0.042). The prediction of death within the hospital was 94.3% accurate (cross-entropy loss of 0.057). The overall F1 score was 0.899 on average, whereas the overall AUC score was 0.940.ConclusionWith the achieved results, the network serves as a reliable tool to predict survival. It adds new insight into the potential of deep learning to assist medical decisions. Especially in the field of transplantation, an AUC Score of 94% is very valuable. This neuronal network is unique as it utilizes transparent and easily interpretable data to predict the outcome after liver transplantation. Further validation must be performed prior to utilization in a clinical context.

Dataset Information

Identification and utilization of donor and recipient genetic variants to predict survival after HCT: are we ready for primetime?

Publications

Identification and utilization of donor and recipient genetic variants to predict survival after HCT: are we ready for primetime?

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