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MHC Class I Chain-Related Gene A (MICA) Donor-Recipient Mismatches and MICA-129 Polymorphism in Unrelated Donor Hematopoietic Cell Transplantations Has No Impact on Outcomes in Acute Lymphoblastic Leukemia, Acute Myeloid Leukemia, or Myelodysplastic Syndrome: A Center for International Blood and Marrow Transplant Research Study.

ABSTRACT: Single-center studies have previously reported associations of MHC Class I Chain-Related Gene A (MICA) polymorphisms and donor-recipient MICA mismatching with graft-versus-host disease (GVHD) after unrelated donor hematopoietic cell transplantation (HCT). In this study, we investigated the association of MICA polymorphism (MICA-129, MM versus MV versus VV) and MICA mismatches after HCT with 10/10 HLA-matched (n?=?552) or 9/10 (n?=?161) unrelated donors. Included were adult patients with a first unrelated bone marrow or peripheral blood HCT for acute lymphoblastic leukemia, acute myeloid leukemia, or myelodysplastic syndrome that were reported to the Center for International Blood and Marrow Transplant Research between 1999 and 2011. Our results showed that neither MICA mismatch nor MICA-129 polymorphism were associated with any transplantation outcome (P?

SUBMITTER: Askar M

PROVIDER: S-EPMC5370205 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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MHC Class I Chain-Related Gene A (MICA) Donor-Recipient Mismatches and MICA-129 Polymorphism in Unrelated Donor Hematopoietic Cell Transplantations Has No Impact on Outcomes in Acute Lymphoblastic Leukemia, Acute Myeloid Leukemia, or Myelodysplastic Syndrome: A Center for International Blood and Marrow Transplant Research Study.

Askar Medhat M Sobecks Ronald R Wang Tao T Haagenson Mike M Majhail Navneet N Madbouly Abeer A Thomas Dawn D Zhang Aiwen A Fleischhauer Katharina K Hsu Katharine K Verneris Michael M Lee Stephanie J SJ Spellman Stephen R SR Fernández-Viña Marcelo M

Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation 20161214 3

Single-center studies have previously reported associations of MHC Class I Chain-Related Gene A (MICA) polymorphisms and donor-recipient MICA mismatching with graft-versus-host disease (GVHD) after unrelated donor hematopoietic cell transplantation (HCT). In this study, we investigated the association of MICA polymorphism (MICA-129, MM versus MV versus VV) and MICA mismatches after HCT with 10/10 HLA-matched (n = 552) or 9/10 (n = 161) unrelated donors. Included were adult patients with a first ...[more]

PMID: 27987385

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Project description:ObjectiveOne of the main problems of lung transplantation is the shortage of organs as well as reduced survival rates. In the absence of an international standardized model for lung donor-recipient allocation, we set out to develop such a model based on the characteristics of past experiences with lung donors and recipients with the aim of improving the outcomes of the entire transplantation process.MethodsThis was a retrospective analysis of 404 lung transplants carried out at the Reina Sofía University Hospital (Córdoba, Spain) over 23 years. We analyzed various clinical variables obtained via our experience of clinical practice in the donation and transplantation process. These were used to create various classification models, including classical statistical methods and also incorporating newer machine-learning approaches.ResultsThe proposed model represents a powerful tool for donor-recipient matching, which in this current work, exceeded the capacity of classical statistical methods. The variables that predicted an increase in the probability of survival were: higher pre-transplant and post-transplant functional vital capacity (FVC), lower pre-transplant carbon dioxide (PCO2) pressure, lower donor mechanical ventilation, and shorter ischemia time. The variables that negatively influenced transplant survival were low forced expiratory volume in the first second (FEV1) pre-transplant, lower arterial oxygen pressure (PaO2)/fraction of inspired oxygen (FiO2) ratio, bilobar transplant, elderly recipient and donor, donor-recipient graft disproportion requiring a surgical reduction (Tailor), type of combined transplant, need for cardiopulmonary bypass during the surgery, death of the donor due to head trauma, hospitalization status before surgery, and female and male recipient donor sex.ConclusionsThese results show the difficulty of the problem which required the introduction of other variables into the analysis. The combination of classical statistical methods and machine learning can support decision-making about the compatibility between donors and recipients. This helps to facilitate reliable prediction and to optimize the grafts for transplantation, thereby improving the transplanted patient survival rate.

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