title: Scripts for TRUMP data analyses. Part II (HLA-related data): statistical analyses specific for hematopoietic stem cell transplantation.
abstract: The Transplant Registry Unified Management Program (TRUMP) made it possible for members of the Japan Society for Hematopoietic Cell Transplantation (JSHCT) to analyze large sets of national registry data on autologous and allogeneic hematopoietic stem cell transplantation. However, as the processes used to collect transplantation information are complex and differed over time, the background of these processes should be understood when using TRUMP data. Previously, information on the HLA locus of patients and donors had been collected using a questionnaire-based free-description method, resulting in some input errors. To correct minor but significant errors and provide accurate HLA matching data, the use of a Stata or EZR/R script offered by the JSHCT is strongly recommended when analyzing HLA data in the TRUMP dataset. The HLA mismatch direction, mismatch counting method, and different impacts of HLA mismatches by stem cell source are other important factors in the analysis of HLA data. Additionally, researchers should understand the statistical analyses specific for hematopoietic stem cell transplantation, such as competing risk, landmark analysis, and time-dependent analysis, to correctly analyze transplant data. The data center of the JSHCT can be contacted if statistical assistance is required.
authors.affiliation: Division of Hematology, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-cho, Omiya-ku, Saitama City, Saitama, 330-8503, Japan. jkandajp@gmail.com.
authors.forename: Junya
authors.initials: J
authors.lastname: Kanda
mesh_terms: D066264:Datasets as Topic; D005060:Europe; D006680:HLA Antigens / Q000032:analysis*; D018380:Hematopoietic Stem Cell Transplantation; D006648:Histocompatibility; D006801:Humans; D007564:Japan; D012042:Registries; D013223:Statistics as Topic; D014481:United States
chemical_list: D006680:HLA Antigens
keywords: Competing risk; HLA mismatch; Landmark analysis; Mismatch direction; Time-dependent analysis