Database research in transfusion medicine: The power of large numbers

T he article by Edgren and colleagues in this issue of TRANSFUSION presents information about the expansion of a previously constructed linked blood donor–transfusion recipient database, the SCANdinavian Donations And Transfusions database (SCANDAT). The “original” SCANDAT consisted of computerized records of blood donation and transfusion activities dating back to the mid-1960s in Sweden and the early 1980s in Denmark with long-term follow-up data from national health registries extending through 2002. This database included data on more than one million blood donors linked to more than 1.3 million transfused recipients. Health outcomes were retrieved by record linkage to Swedish and Danish nationwide data health registries on cancer occurrence, hospital care, and mortality. This linkage was made possible by the use of a national registration number for all health-related activities, thereby providing thorough follow-up of donors and recipients for multiple (long-term) health outcomes. Previous SCANDAT accomplishments include determination of cancer risks in volunteer blood donors compared with general population data, evaluation of the potential transmissibility of cancer to transfusion recipients from donors who subsequently develop cancer, and evaluation of recipient posttransfusion survival stratified by a number of variables including red blood cell (RBC) storage age. The second version of SCANDAT has added another 8 to 10 years of data, thereby extending the original observations through 2010 to 2012. SCANDAT2 contains 25.5 million donation records, 21.3 million transfusion records, 3.7 million unique persons, and 40 million person-years of follow-up. Data quality is high as there is a more than 97% concordance with official annual statistics on blood donations and transfusions, and 96% of all transfusions in Sweden (94% in Denmark) are linkable to their respective donation(s). This robust linkage will enable investigators to study disease concordance between donors and recipients and to make inferences about disease transmissibility. This capability is enhanced by SCANDAT2’s impressive number of transfused components and unprecedented longterm follow-up morbidity and mortality data. As SCANDAT2 illustrates, the routine collection of massive amounts of clinical data in large multiinstitution databases has become increasingly common across multiple medical and surgical specialties. These databases come in two main flavors: 1) administrative databases whose primary purpose is for reimbursement and insurance purposes and 2) clinical registries that focus on collecting data on patients with a given disease or undergoing a specific procedure. As in other medical specialties, the use of complex databases that extract data from various sources are becoming more common in transfusion medicine (TM), where such databases can be used for hemovigilance and monitoring purposes and blood management evaluations or to address key research questions. SCANDAT and SCANDAT2 are excellent examples of how TM research questions can be approached using a large multicenter database. The remainder of this editorial will further review how TM research can benefit from such large database queries and will address some important considerations in this type of research. We have organized our discussion in order of the complexity of the efforts needed to compile the databases, although none of these efforts should be characterized as uncomplicated or straightforward!