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- W2937434668 abstract "Abstract Introduction: Human leukocyte antigen (HLA)-matched unrelated donor (MUD) is the source of MUD transplantation (MUDT) for about 70% of patients who do not have matched related donor. To facilitate MUD search globally, there are 75 stem cell registries with more than 28 million donors registered (as of January 2017). Out of these donors, India has an insignificant representation of approximately 0.23 million. Further, Indians express high genetic variations, making it difficult to find MUD for an Indian patient. Aims and Objectives: The aim of this study is to analyze the MUD search for hematological disorder patients requiring transplant. An attempt was made to observe the MUD scenario for Indian patients requiring MUDT from accessible stem cell registries. Methods: A total of 558 patients approached Genebandhu registry and Chimera Transplant Research Foundation for MUD search over a period of 4 years requiring MUDT were included in this study. High resolution of HLA-A, -B, -C, -DRB1, and -DQB1 was used to perform MUD search through proprietary software called Prometheus and Bone Marrow Donors Worldwide (BMDW) search tool. Results: Out of 558 patients, MUD was located only for 135 (24.19%) patients. Out of these 135 patients, 91 (16.30%) patients found an MUD in global database and only 44 (7.88%) patients within India. Conclusion: This study demonstrates that building a large Indian database will not only help in increasing the chances of finding an MUD for maximum number of patients within India but also provide cost-effective treatment, in a society where cost is a vital factor." @default.
- W2937434668 created "2019-04-25" @default.
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- W2937434668 date "2019-01-01" @default.
- W2937434668 modified "2023-10-11" @default.
- W2937434668 title "Human leukocyte antigen-matched unrelated donor search experience for hematological disorder patients requiring transplant: scenario for Indian patients" @default.
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- W2937434668 doi "https://doi.org/10.4103/ijmpo.ijmpo_3_18" @default.
- W2937434668 hasPublicationYear "2019" @default.
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