Multi-criteria decision analysis model for choosing the best hematopoietic stem cell donor

Authors

DOI:

https://doi.org/10.33448/rsd-v13i1.44678

Keywords:

Hematopoietic stem cell transplantation; Donor; Multi-criteria decision; DEXi Software.

Abstract

Allogeneic hematopoietic stem cell transplantation is employed in the treatment of hematologic and non-hematologic diseases, transferring stem cells from a healthy donor to the patient. Donor selection requires compatibility of the human leukocyte antigen, considering factors such as age, gender match, blood type, and cytomegalovirus serology, being an essential strategy for transplant success. This article proposes integrating two tools: REDCap (Research Electronic Data Capture) for electronic forms and DEXi for multi-criteria decision analysis. The goal is to address a complex decision-making process in choosing the best donor, considering multiple qualitative parameters. Relevant criteria were selected, and REDCap forms were constructed for data collection. A DEX model based on a hierarchized decision tree was developed, with values inserted by the author following predefined rules. The analysis involved four hypothetical donors. Results highlighted donor 1 for its strong HLA match with the recipient, assigning it higher hierarchical weight. The model indicated donor 1 as the preferred choice. The DEX methodology answered the decision question with visually accessible graphical results. The promising use of the REDCap platform and the positive evaluation of the DEXi model suggest it is a thriving technology for optimizing medical practice in transplantation.

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Published

07/01/2024

How to Cite

BENEVIDES, T. .; GURJÃO, E. .; BRITO, L. . Multi-criteria decision analysis model for choosing the best hematopoietic stem cell donor. Research, Society and Development, [S. l.], v. 13, n. 1, p. e3313144678, 2024. DOI: 10.33448/rsd-v13i1.44678. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/44678. Acesso em: 27 may. 2024.

Issue

Section

Health Sciences