Hematopoietic stem cell transplantation (HSCT) is a medical procedure in the field of hematology and oncology, most often performed for patients with certain cancers of the blood or bone marrow. A lot of patients have no suitable HLA-matched donor within their family, so physicians must activate a “donor search process” by interacting with national and international donor registries who will search their databases for adult unrelated donors or cord blood units (CBU). Information and communication technologies play a key role in the donor search process in donor registries both nationally and internationaly. One of the major challenges for donor registry computer systems is the development of a reliable search algorithm. This work discusses the top-down design of such algorithms and current practice. Based on our experience with systems used by several stem cell donor registries, we highlight typical pitfalls in the implementation of an algorithm and underlying data structure. 1. Introduction Hematopoietic stem cell transplantation (HSCT) [1] (commonly referred to as bone marrow transplantation) is a medical procedure in the field of hematology and oncology, most often performed for patients with certaincancersof thebloodorbone marrow. HSCT is the treatment of choice for people with hematopoietic malignancies, bone marrow failure, and certain types of cancer (e.g., lymphoma) which results in a compromised immune system. The most important factor in the successful outcome of HSCT is that the patient and donor are matched for the Human Leukocyte Antigens (HLA). The level of the matching required varies with the source of stem cells used for HSCT. A lot of patients have no suitable HLA-matched donor within their family, so physicians must activate a “donor search process” by interacting with national and international donor registries who will search their databases for adult unrelated donors (AUD) or cord blood units (CBU). Information and communication technologies play a key role in the donor search process in donor registries both nationally and internationaly. One of the major challenges for donor registry computer systems is the development of a reliable search algorithm. This work discusses the top-down design of such algorithms and current practice. Based on our experience with systems used by several stem cell donor registries, we will highlight typical pitfalls in the implementation of an algorithm and underlying data structure. 2. Search Algorithm The purpose of the donor search algorithm is to find and present a selected list of potential donors
W. Bochtler, M. Maiers, J. N. A. Bakker et al., “World Marrow Donor Association framework for the implementation of HLA matching programs in hematopoietic stem cell donor registries and cord blood banks,” Bone Marrow Transplantation, vol. 46, no. 3, pp. 338–343, 2011.
[3]
M. Prestegaard, Unrelated Hematopoietic Stem Cell Donor Search and Facilitation Information Systems Principles, 2012.
[4]
W. Bochtler, M. Maiers, M. Oudshoorn et al., “World Marrow Donor Association guidelines for use of HLA nomenclature and its validation in the data exchange among hematopoietic stem cell donor registries and cord blood banks,” Bone Marrow Transplantation, vol. 39, no. 12, pp. 737–741, 2007.
[5]
S. G. Marsh, “Nomenclature of HLA alleles,” http://hla.alleles.org/wmda/index.html.
[6]
A. Timm and H. Eberhard, “The semantics of EMDIS messages Version 1.28,” 2011.
E. B. I. EMBL, “IMGT/HLA Database—Search Determinants,” http://www.ebi.ac.uk/imgt/hla/searchdet.html.
[9]
C. K. Hurley, M. Maiers, S. G. E. Marsh, and M. Oudshoorn, “Overview of registries, HLA typing and diversity, and search algorithms,” Tissue Antigens, vol. 69, no. 1, supplement, pp. S3–S5, 2007.
[10]
C. K. Hurley, M. Setterholm, M. Lau et al., “Hematopoietic stem cell donor registry strategies for assigning search determinants and matching relationships,” Bone Marrow Transplantation, vol. 33, no. 4, pp. 443–450, 2004.
C. Malmberg, “Search Strategy and HapLogic: Case Studies,” NMDP, http://marrow.org/News/Events/Council_Meeting/HapLogic_III_Search_Strategy_With_Answers.aspx.
[14]
D. Steiner, M. Korhonen, M. Kurikova, et al., “Prometheus probability matching: community technology preview,” in Proceedings of the 9th International Donor Registry Conference (IDRC '12), Sydney, Australia, 2012.
[15]
J. Pingel, J. Hofmann, D. Baier et al., “Hap-E search: haplotype-enhanced search,” in Proceedings of the 9th International Donor Registry Conference (IDRC '12), Sydney, Australia, 2012.
[16]
P. Gourraud, M. Balère, A. Dormoy, P. Loiseau, E. Marry, and F. Garnier, “Computer assisted search for unrelated donors using the easymatch—tool at France greffe de moelleprometheus probability matching: community technology preview,” in Proceedings of the 16th International HLA and Immunogenetics Workshop and Joint Conference, Kings Dock, Liverpool, 2012.
[17]
H. Eberhard, “Validation of the predictions of optiMatch,” in Proceedings of the 9th International Donor Registry Conference (IDRC '08), Berne, Switzerland, 2008.
[18]
J. Dehn, “HapLogic III,” NMDP, http://marrow.org/News/Events/Council_Meeting/2011_Presentations/A3_B3_Putting_HapLogic_to_Work_for_You.aspx.
[19]
H.-P. Eberhard, Sch?tzung von hochaufgel?sten HLA-Haplotypfrequenzen deutscher Blutstammzellspender und ihre Anwendung bei der Patientenversorgung, Institut für Transfusionsmedizin, Universit?t Ulm, 2010.
[20]
M. Maiers, J. N. A. Bakker, W. Bochtler et al., “Information technology and the role of WMDA in promoting standards for international exchange of hematopoietic stem cell donors and products,” Bone Marrow Transplantation, vol. 45, no. 5, pp. 839–842, 2010.