educational topic 19 alloimmunization

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• v.47(2); 2020 Apr

Pathophysiology of Alloimmunization

Rubiraida molina-aguilar.

a Morphology Department, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Mexico City, Mexico

b Hematology Department, UMAE, Hospital de Especialidades Centro Médico Nacional La Raza, Instituto Mexicano del Seguro Social, Mexico City, Mexico

c Translational Medicine Research Unit in Hemato-Oncological Diseases, UMAE, Hospital de Especialidades Centro Médico Nacional La Raza, Instituto Mexicano del Seguro Social, Mexico City, Mexico

Soledad Gómez-Ruiz

Jorge vela-ojeda, laura arcelia montiel-cervantes, elba reyes-maldonado, introduction.

Alloimmunization is caused by exposure to erythrocytes from a donor that expresses blood group antigens other than those of the recipient and is related to processes that alter the balance of the immune system. Knowing the pathophysiology of alloimmunization process is essential to understand clinical complications associated with this process.

Patients and Methods

From October 2016 to April 2017, irregular antibody screening was performed in 1,434 polytransfused (compatible with the ABO and D system) patients by means of agglutination techniques using erythrocytes of a known phenotype of 44 patients with a positive alloantibody screening. Non-alloimmunized (control) subjects were matched for age, gender, pathology, and treatment group with alloimmunized patients. The subsets of B, T, and Treg lymphocytes were determined by flow cytometry.

The results of screening for alloantibodies in patients by specificity of antibodies were as follows: nonspecific (30%), followed by anti-Di^a (13%), anti-e (9%), anti-S (9%), anti-I (7%), anti-K (7%), and anti-P (7%). A lower percentage of CD4+ T lymphocytes and an increase of CD8+ T lymphocytes were observed in alloimmunized patients, as well as a low CD4/CD8 ratio (0.7 vs. 1.6, p = 0.003), a higher percentage of B lymphocytes versus the control group (30 vs. 20%, p = 0.003), and a decrease of Treg CD4+ lymphocytes versus the control group (3 vs. 12 cells/μL, p = 0.043). These observations suggest that alloimmunized patients have important alterations in the number of some lymphocyte subsets that can be translated into clinical immune dysregulation.

A decreased CD4/CD8 ratio, increased B lymphocytes, and Treg lymphocyte deficiency are the most significant changes observed in alloimmunized patients.

According to the Mexican guide for the clinical use of blood, transfusion therapy is applied to patients with symptomatic anemia, when their hemoglobin concentration ranges between 5 and 10 g/dL and does not show response to other therapies such as iron, folic acid, vitamin B 12 , or erythropoietin [ 1 ]. Each unit of blood is enough to raise the patient's hemoglobin by 1 g/dL; however, most patients require repeated transfusions to improve their symptoms [ 2 ].

Red blood cell (RBC) transfusions are administered routinely, exclusively with a match compatibility of the “ABO” and RhD phenotype between the recipient and the donor; but other erythrocyte antigens have been associated with the formation of alloantibodies, the so-called alloimmunization process [ 3 , 4 , 5 ]. The main requirement for the development of alloimmunization is exposure to the donor erythrocyte antigens that are absent in the recipient; these antigens have the ability to initiate the formation of antibodies against erythrocytes resulting in transfusion reactions that are potentially serious [ 6 , 7 , 8 ]. This process represents an important complication in patients with repeated transfusions, since the levels of alloantibodies can be reduced over time (evanescence) and overlooked in future determinations, although this does not preclude the probability of suffering severe transfusion reactions [ 9 ].

Studies suggest that alloimmunization is related to onco-hematological disease and organ transplantation, because these events alter the equilibrium of the immune system [ 10 ]. The analysis of subpopulations of CD4+ and CD8+ lymphocytes in murine models concluded that alloimmunization requires depletion of CD4+ lymphocytes, but not of CD8+ lymphocytes [ 11 ].

In murine models with neonatal alloimmunization, an increase in CD8+ CD25+ regulatory T lymphocytes has been described, with an increase in the production of IL-10 and IFN-α [ 12 ]. In patients with thalassemia alloimmunized after repeated transfusions, an increase in memory B lymphocytes (CD19+, CD38+) has been observed in comparison with non-alloimmunized patients, suggesting an important alteration of the immune system induced by erythrocyte antigens [ 13 ].

As far as the authors know, there are no reports in humans that describe the immunological changes associated with the process of alloimmunization to erythrocyte antigens. Therefore, in the present study we determined T and B lymphocyte subpopulations, as well as regulatory T lymphocytes (Treg) in patients with different hematological disorders exposed to multiple transfusions of erythrocyte concentrates (EC) and who developed alloantibodies against RBC of the donor; lymphocyte subsets were compared with patients in the same conditions (hematological disorder, age, sex, polytransfusion) who did not develop anti-erythrocyte alloantibody.

Material and Methods

The present study included adult patients with different hematological disorders. All patients were tested for alloantibody determinations and T, B, and Treg lymphocytes characterization from samples obtained for routine studies.

Patients and Donors

A cross-sectional cohort study was performed with recurrently transfused patients at the hematology service of the “Hospital de Alta Especialidad Dr. Antonio Fraga Mouret, Centro Médico Nacional La Raza, Instituto Mexicano del Seguro Social.” The study included all patients attended at this center from October 2016 to April 2017. Patients with hemolytic anemia (HA), myelodysplastic syndrome (MDS), multiple myeloma (MM), immune thrombocytopenic purpura (ITP), chronic myeloid leukemia (CML), and acute leukemia (AL) were included; each group consisted of 239 patients (total 1,434 patients). Patients with HIV and other viral infections were excluded from the study.

Patients with a previous report in the medical record of alloantibodies and patients with positive screening for alloantibodies according to agglutination techniques during at least two separate determinations were included. Patients who did not report a previous test in the medical record of alloantibodies and with negative screening for alloantibodies by agglutination techniques during at least two separate determinations were selected as negative controls. The control group was paired with positive patients by age, gender, pathology, and treatment group. Determinations of alloantibodies and lymphocyte subsets were performed simultaneously, immediately after the collection of samples. Clinical information was obtained from the transfusion medical records of the study center.

RBCs Alloantibody Screened

Samples were analyzed to identify the detected alloantibodies using the 10-cell panel of the “Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social.” The institutional code panels used were as follows: VI-2016 (03/09/16–14/10/16); VII-2016 (15/10/16–25/11/16); VIII (26/11/16–06/01/17); I-2017 (07/01/17–17/02/17), and II-2017 (18/02/17–05/05/17).

These cells constitute a standard panel with known phenotype provided by the Instituto Mexicano del Seguro Social and are used for alloantibody screening. Agglutination tests were done at three temperatures: room temperature, incubation at 7°C, incubation at 37°C, and in Coombs serum. The criteria for antibody specificity were based on the recommendations of AABB. Plasma of each patient was analyzed in duplicate and confirmed 1 month later for patients with positive screening.

Flow Cytometry Acquisition and Analysis of Lymphocyte Subsets

Optimal concentrations of directly conjugated (FITC, PE, PerCP, or APC) monoclonal antibodies were added to 100 µL of whole blood. The mixture was incubated for 20 min at room temperature (20–25°C) in the dark. RBC lysis was performed using FACS Lysing Solution (Becton-Dickinson, San Jose, CA, USA), according to manufacturer's instructions. Stained cells were washed twice and resuspended in phosphate-buffered saline (PBS). The following monoclonal antibodies were used, conjugated to one of the four fluorochromes fluorescein isothiocyanate (FITC), phycoerythrin (PE), peridinin chlorophyll protein reagent (PerCP), and allophycocyanin (APC). Anti-CD45 APC, anti-CD4 FITC, and anti-CD3 PerCP were used to stain CD4+ T cells. To identify CD8+ T cells, the antibodies anti-CD45 APC, anti-CD3 PerCP, and anti-CD8 PE were used. Anti-CD19 PE was used to stain B lymphocytes. Anti-CD4 FITC, anti-Fox P3 PE, and anti-CD25 APC were used for identification of regulatory CD4+ lymphocytes (Treg CD4) or anti-CD8 PerCP, anti-Fox P3 PE, and anti-CD25 APC were used for identification of regulatory CD8+ lymphocytes (Treg CD8). The samples of patients were acquired by BD FACS Calibur flow cytometry (BD Biosciences, San Diego, CA, USA) and analyzed by CellQuest Pro software.

Statistical Analysis

The Kolmogorov-Smirnov tests were used to evaluate the normality of the distributions. The Mann-Whitney U test was used to analyze the differences between the two groups of patients. Statistical analysis was performed using GraphPad Prism 6.0 (GraphPad Software, San Diego, CA, USA) and SPSS for Windows (SPSS Inc., Chicago, IL, USA). Statistical significance was considered at p ≤ 0.05.

Alloantibody screening was performed in 1,434 patients from October 2016 to April 2017. The results of 44 hematologic patients (3.1%) with positive alloantibody screening were analyzed and compared with the control group that included 44 patients matched for age, gender, pathology, and treatment group (patients with negative alloantibody screening, verified by self-labeling and negative direct Coombs).

Distribution of patients according to hematological diagnosis, specificity of alloantibodies, and other clinical data are presented in Table ​ Table1. 1 . The patients had a median age of 55 years (24–83 years), HA (membranopathy and autoimmune) (50%) was the most common pathology for which patients presented alloimmunization, followed by MDS (27%), MM (11%), ITP (7%), and CML (5%). According to medical records, patients had a stable and controlled state of their hematologic disease. Previous to determination of alloantibodies and lymphocyte subsets, the group of alloimmunized patients received between 1 and 78 (median, 12) transfusions of EC (compatible with the ABO and D system), while the control group received between 1 and 38 (median, 21) transfusions of EC. Antibody tests were performed at 11–127 weeks after transfusion. The antibodies most frequently identified were nonspecific (30%), followed by anti-Di a (13%), anti-e (9%), anti-S (9%), anti-I (7%), anti-K (7%), and anti-P (7%).

Characteristics of alloimmunized and non-alloimmunized patients by hematological disease, specificity of alloantibody, and CD4/CD8 ratio

Ranges are given in square brackets. HA, hemolytic anemia; MDS, myelodysplastic syndrome; MM, multiple myeloma; ITP, immune thrombocytopenia; CML, chronic myeloid leukemia; EC, erythrocyte concentrates.

No differences were observed between alloimmunized versus non-alloimmunized patients in terms of routine hematological parameters such as white blood cell counts 5,490 cells/μL (3,770–6,570) versus 6,610 cells/μL (3,850–8,625), respectively; total lymphocytes counts 1,410 cells/μL (840–1,850) versus 1,835 cells/μL (1,140–2,525), respectively; hemoglobin 11.8 g/dL (9.2–13.6) versus 13.8 g/dL (11.3–14.9), respectively; and platelets count 166 10 3 /μL (98–247) versus 194 10 3 /μL (68–248), respectively.

Lymphocyte Subsets

In alloimmunized patients, the median and 25–75 percentile (median [25–75 percentile]) values of CD3+, CD4+, CD8+, and B cells in peripheral blood were expressed as percentage, whereas CD4+ and CD8+ Treg cells were expressed as cells/μL and CD4/CD8 ratio cells. Figure ​ Figure1 1 shows dot plots of the acquisition of each lymphocyte subset. Alloimmunized patients had no statistical difference in the percentages of CD3+ T lymphocytes compared with the control group (62% [46–71] vs. 60% [50–74], p = 0.893); but the alloimmunized patients had a lower percentage of CD4+ T lymphocytes compared to the control group (22% [14–27] vs. 34%] 29–42], p = 0.0001) (Fig. ​ (Fig.2A) 2A ) and a higher percentage of CD8+ T lymphocytes compared to the controls (30% [20–40] vs. 20% [18–29], p = 0.003) (Fig. ​ (Fig.2B). 2B ). Inversion in the proportion of CD4+ and CD8+ T lymphocytes (CD4/CD8 ratio) was observed compared to the control group (0.7 [0.5–1.1] vs. 1.6 [1.2–2.1], p = 0.0001) (Fig. ​ (Fig.2C). 2C ). In the alloimmunized patients, a significant increase in the percentage of B lymphocytes (CD19+) was observed compared with the control group (11% [9–14] vs. 5% [3–6], p = 0.0053) (Fig. ​ (Fig.2D). 2D ). In alloimmunized patients, a significant decrease of regulatory CD4+ T lymphocytes (Treg CD4) was observed in comparison with the control group (3 cells/μL [1–12] vs. 12 cells/μL [5–17], p = 0.0031) (Fig. ​ (Fig.2E), 2E ), while a nonsignificant increase was observed in regulatory CD8+ T lymphocytes (Treg CD8) compared with the control group (3 cells/μL [1–20] vs. 5 cells/μL [2–9], p = 0.554) (Fig. ​ (Fig.2F 2F ).

Dot plots showing strategy of acquisition for lymphocyte subsets. a Selection of lymphocyte region for analysis of coexpression patterns of antigens characteristic of lymphocyte subtypes. The populations of classified lymphocytes are shown in the following dot plots: b B lymphocytes (CD19+); c CD8+ T lymphocytes; d CD4+ T lymphocytes. e Region selection of total CD8+ T lymphocytes for coexpression analysis of antigen characteristic of Treg lymphocytes (CD8+) ( f ). g Region selection of total CD4+ T lymphocytes for coexpression analysis of antigen characteristic of Treg lymphocytes (CD4+) ( h ).

Comparison between lymphocyte subsets in patients with and without anti-erythrocyte alloantibodies. Percentage comparison of: A CD4+ lymphocytes in patients with and without alloantibodies (22 vs. 34%, p = 0.0001*). B CD8+ lymphocytes in patients with and without alloantibodies (30 vs. 20%, p = 0.0030*). C Proportion of CD4+/CD8+ lymphocytes (ratio) in patients with and without alloantibodies (0.7 vs. 1.6, p = 0.0001*). D CD19+ lymphocytes in patients with and without alloantibodies (11 vs. 5%, p = 0.0030*). E CD4+/CD25+/FoxP3+ lymphocytes (TregCD4+) in patients with and without alloantibodies (3 vs.12 cells/μL, p = 0.0430*). F CD8+/CD25+/FoxP3+ lymphocytes (TregCD8+) in patients with and without alloantibodies (3 vs. 5 cells/μL, p = 0.5540). Mann-Whitney U test statistics, * p = ≤0.05.

The objective of this study was to obtain, as far as possible, a general view of the immunological changes in the alloimmunization process. In this study, the presence and specificity of alloantibodies was determined in patients with transfusion-dependent hematological diseases, as well as the number of B cells, Treg, CD3+, CD4+, CD8+ lymphocytes, and the CD4/CD8 ratio. In alloimmunized patients, a low number of CD4+ lymphocytes, Treg CD4+ cells, and higher number of B and CD8+ lymphocytes was observed in our study, as well as a decrease in the CD4/CD8 ratio.

We determined the presence and specificity of anti-erythrocytic alloantibodies in 1,434 transfused hematologic patients, of which only 3.1% presented positive alloantibodies.

The frequency of antibodies identified in this group of hematological patients is higher than the frequency reported by the Chilean group where they reported that 1.02% of their study population developed alloantibodies [ 14 ]. While another study conducted in Brazilian patients reported a higher frequency (7.5%) [ 15 ]. However, in this study, the results were obtained through a retrospective study performed over more than 6 years, and with a different population sample. Other authors have reported an alloimmunization rate similar to our results, in the range of 3–10% of recipients in the general population [ 16 ].

The prevalence of antibodies reported in studies conducted in Latino population differs according to the country; in this study, we found a higher frequency of nonspecific antibodies (auto anti-IgG), followed by anti-Di a antibodies; whereas in the Chilean and Brazilian population, the prevalence of anti-E antibodies was higher.

Different to the European population, the Latin-American population is more predisposed to alloimmunization with antigens of the Diego system. Even though, in our population, the presence of this erythrocyte antigen was lower. Di a is found mainly in populations of Mongolian descent. It is found in 36% of South American Indians, 12% of Japanese, and 12% of Chinese, whereas it is rare in Caucasians and Blacks (0.01%) [ 17 ]. The greater frequency of erythrocyte phenotype in this population is associated with a lower frequency of alloimmunization in this population. Regarding the specificity of antibodies identified by disease, in patients with HA, the predominance of warm IgG autoantibodies and the anti-Rh system is observed, which is consistent with previous reports [ 18 ].

MDS, characterized by cytopenias and ineffective hematopoiesis, is usually treated with disease-modifying therapies and supportive care, such as transfusion. In this disease, IgG-specific alloantibodies against RBC antigens were predominantly identified [ 19 ].

The processing of antigens is complex, ranging from antigen recognition to development of polyclonal antibodies. In this process, different cell lines intervene; when an erythrocytic alloantigen comes in contact with an antigen-presenting cell (APC-which may be: dendritic cells, macrophages, or B lymphocytes), it must be able to recognize it by using the MHC II molecule; subsequently, it must phagocytose and excise it in small linear peptides that are presented and recognized by a helper CD4+ T lymphocyte or directly by the receptor of B lymphocytes, the latter proliferate and differentiate into plasma cells capable of producing antibodies that will recognize the three-dimensional structure of the presented epitope [ 20 ]. In this process, there are several cellular subsets with the ability to develop or inhibit this immunological activity, such as helper T lymphocytes (T CD4+), with co-stimulatory function, promoting the presentation of linear peptide antigens to B lymphocytes. Regulatory T CD4+ lymphocytes produce IL-10 (anti-inflammatory cytokine) that inhibits cellular activation, mainly helper T lymphocytes [ 21 ].

The decrease of these regulatory subpopulations has been associated with the development of autoimmune diseases, such as AHAI, in which there is a predominance of autoreactive CD4+ T lymphocytes and production of IgG autoantibodies, which recognize erythrocytic antigens, constituting the pathophysiology of disease. In our study, we observed that in general, all alloimmunized patients had a lower number of CD4+ Treg lymphocytes, even in patients with AHAI, which can be associated with the increased activity of T CD4+ lymphocytes, and with it the greater presentation of erythrocytic alloantigens [ 22 ].

Another important aspect to consider in the process of presentation of alloantigens and alloimmunization is the variability in the MHC II molecules, since the polymorphisms of HLA-DR have been proposed as a relevant factor alloimmunization, because they depend on the primary recognition capacity of a linear epitope that will culminate with the development of an alloantibody that will recognize the same epitope but three-dimensionally [ 23 , 24 , 25 ]. One weakness of our study is that this variable was not evaluated, but it is important to emphasize that this is one of the first studies conducted in a Latin population where main lymphoid subsets are evaluated and their number is associated with the alloimmunization process.

In vitro studies report that the main cellular effects of alloimmunization are a decrease in Th1 cytokines and an increase in Th2, as well as an increase in CD8+ T lymphocytes, and a decrease in CD4+ T lymphocytes [ 26 ], which is in accordance with our results. It has also been reported that at the beginning of alloimmunization, an increase in the number of CD4+ T lymphocytes is observed due to an exacerbated antigenic presentation in this period. In patients evaluated in this study, we observed that the group of alloimmunized patients presented a significant decrease in the number of helper CD4+ T lymphocytes, while CD8+ T lymphocytes were significantly increased; although the values of leukocytes and total lymphocytes are not different between both groups.

The decrease of CD4+ T lymphocytes has been reported under immunological depletion conditions, as in patients infected with HIV [ 27 ], where the antigenic stimulus is constant and for prolonged periods, similar to the immune status of alloimmunized patients. This decrease of CD4+ T lymphocytes is possibly mediated by PD-1/PDL-1; therefore, inversion of the CD4+/CD8+ proportion and decrease of the CD4/CD8 ratio are observed.

Two groups of researchers determined separately but simultaneously that the proportion of CD4/CD8 lymphocytes was associated with viral load in patients with HIV, concluding that there is an inverse relation between the CD4/CD8 ratio and viral load, that is, a decrease in viral load and better prognosis. They considered that a CD4/CD8 ratio of less than 1.0 is an indicator of exhaustion of lymphopoiesis and immunosenescence. Therefore, they proposed that a proportion of CD4/CD8 lymphocytes greater than 1.0 is a favorable prognostic factor for evolution and response to treatment in patients with HIV [ 28 , 29 ]. In our study, we observed that the non-alloimmunized group had a CD4/CD8 index of 1.6 (percentile 25–75 [1.2–2.1]), while in the group of alloimmunized patients, the index was 0.7 (percentile 25–75 [0.5–1.1]).

Based on the cutoff value referred to in the previously mentioned studies, we consider that a ratio of CD4/CD8 lymphocytes of less than 1.0 could suggest an alloimmunization process, even in cases of evanescence of alloantibodies; although it is necessary to conduct more studies to establish it.

In our study, we observed that patients “previously alloimmunized” have a lower media of the CD4/CD8 ratio than patients “not previously alloimmunized” (0.8 vs. 1.0, respectively), possibly due to a greater exposure to erythrocytic alloantigens, and a greater immunological exhaustion. Among the “previously alloimmunized” patients, we found a patient with two alloantibodies. The first anti-C+e specificity was observed at the time of study entry, and the second antibody with anti-Di a specificity was identified during follow-up. This patient has also a CD4/CD8 ratio greater than 1.1 (ratio = 2.2), suggesting that the number of CD4+ T lymphocytes is increased, which, according to the reports, is associated to antigenic processing activity and an early stage of the alloimmunization process.

A similar case occurred in the group of “not previously alloimmunized” patients, where we found a patient with a CD4/CD8 ratio equal to 3.3, in whom two alloantibodies with anti-e and anti-Fy a specificity were identified. It is known that these alloantibodies are highly immunogenic proteins.

Our group suggests that in the early stages of alloimmunization, the CD4/CD8 ratio is increased; and as the humoral immune response is established and immune exhaustion continues, this value decreases. This finding could be a marker of the occurrence of alloimmunization in transfused patients.

It has been reported that up to 40% of alloantibodies subsequently become undetectable, especially when patients do not receive transfusion therapy again. In these cases, the CD4/CD8 ratio can be a useful tool to identify this group of patients [ 30 ].

Finally, an important limitation of this study is the number of patients evaluated. Since it was a cross-sectional study, and although 1,434 patients were analyzed, the frequency of alloimmunization is similar to that reported by other studies.

Conclusions

The most significant immunological alterations observed in alloimmunized patients were the decreased CD4/CD8 ratio, increased B lymphocytes, and Treg lymphocyte deficiency.

Statement of Ethics

The experiments performed in the present paper complied with the current laws of Mexico and were approved by the Ethical Committee of the Hospital de Alta Especialidad Dr. Antonio Fraga Mouret, Centro Médico Nacional La Raza, Instituto Mexicano del Seguro Social.

Disclosure Statement

The authors have no potential conflicts of interest to disclose.

Acknowledgments

This work was supported in part by a grant from SIP-IPN 20160954. R.M.-A. is a fellow of CONACYT (No. 280269) and research fellow IMSS (No. 98366535). E.R.-M. is EDI and COFAA fellow. E.R.-M., L.A.M.-C., and J.V.-O. are SNI fellows.

Pathophysiology of Alloimmunization

Affiliations.

• 1 Morphology Department, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Mexico City, Mexico.
• 2 Hematology Department, UMAE, Hospital de Especialidades Centro Médico Nacional La Raza, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
• 3 Translational Medicine Research Unit in Hemato-Oncological Diseases, UMAE, Hospital de Especialidades Centro Médico Nacional La Raza, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
• PMID: 32355475
• PMCID: PMC7184833
• DOI: 10.1159/000501861

Introduction: Alloimmunization is caused by exposure to erythrocytes from a donor that expresses blood group antigens other than those of the recipient and is related to processes that alter the balance of the immune system. Knowing the pathophysiology of alloimmunization process is essential to understand clinical complications associated with this process.

Patients and methods: From October 2016 to April 2017, irregular antibody screening was performed in 1,434 polytransfused (compatible with the ABO and D system) patients by means of agglutination techniques using erythrocytes of a known phenotype of 44 patients with a positive alloantibody screening. Non-alloimmunized (control) subjects were matched for age, gender, pathology, and treatment group with alloimmunized patients. The subsets of B, T, and Treg lymphocytes were determined by flow cytometry.

Results: The results of screening for alloantibodies in patients by specificity of antibodies were as follows: nonspecific (30%), followed by anti-Di a (13%), anti-e (9%), anti-S (9%), anti-I (7%), anti-K (7%), and anti-P (7%). A lower percentage of CD4+ T lymphocytes and an increase of CD8+ T lymphocytes were observed in alloimmunized patients, as well as a low CD4/CD8 ratio (0.7 vs. 1.6, p = 0.003), a higher percentage of B lymphocytes versus the control group (30 vs. 20%, p = 0.003), and a decrease of Treg CD4+ lymphocytes versus the control group (3 vs. 12 cells/μL, p = 0.043). These observations suggest that alloimmunized patients have important alterations in the number of some lymphocyte subsets that can be translated into clinical immune dysregulation.

Conclusion: A decreased CD4/CD8 ratio, increased B lymphocytes, and Treg lymphocyte deficiency are the most significant changes observed in alloimmunized patients.

Keywords: Alloantibodies; Alloimmunization; B lymphocytes; Regulatory lymphocytes; Transfusion.

Copyright © 2019 by S. Karger AG, Basel.

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The question, my response, diagnosis and management of platelet alloimmunization.

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Karen Quillen; Diagnosis and Management of Platelet Alloimmunization. The Hematologist 2013; 10 (6): No Pagination Specified. doi: https://doi.org/10.1182/hem.V10.6.1023

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Platelet refractoriness remains a clinical challenge associated with an increased risk of bleeding, prolonged hospital stays, and decreased survival. Poor one-hour post-transfusion increments typically represent immune platelet refractoriness, whereas an adequate one-hour increment followed by a suboptimal 18- to 24-hour count suggests peripheral consumption or sequestration. In the absence of a direct prospective comparison of the three strategies commonly used to support patients who have platelet alloimmunization – human leukocyte antigen (HLA) matching, HLA antibody avoidance, and platelet cross-matching – two recent reviews have concluded there is no definitive evidence that any of these strategies improves hemorrhage control or mortality. 1 , 8    The provision of HLA-matched platelets can be very efficient in centralized transfusion systems as it has been in the United Kingdom. 2  

Apheresis platelets stored in additive solution, which contain 2/3 less donor plasma, have become available in the United States, with a longer track record in Europe. They are associated with lower platelet increments at one hour, but are less likely to cause allergic transfusion reactions or hemolysis, compared with standard platelets suspended in 100 percent donor plasma. 3    Platelets that have undergone psoralen- UVA treatment to inactivate bacteria (and other infectious agents) are also known to produce lower post-transfusion increments. These considerations need to be taken into account when evaluating patients who seem to be refractory to platelet transfusion.

A recent study in an animal model suggests that immune-mediated clearance of MHC mismatched platelets can occur in the absence of anti-platelet alloantibodies, in mice that are deficient in B cells. Allo-reactive CD8+ T cells appear to mediate antibodyindependent platelet clearance. 4 , 5    If this finding is corroborated in humans, immune platelet refractoriness may actually account for some refractory cases now presumed to be non-immune. A putative T-cell—mediated mechanism would also favor HLA matching over cross-matching as a management strategy.

Updated References

What is your approach to the diagnosis and management of platelet alloimmunization?

Platelet refractoriness occurs in 5 to 15 percent of patients who receive chronic platelet transfusions. 1    The patient’s size and the number of platelets transfused should be factored into the assessment of refractoriness. For example, one measure, the corrected count increment (CCI), is computed as follows: CCI = (platelet increment after transfusion/μl) x (body surface area in m2) ÷ (platelet dose x 1011). For the purposes of this calculation, assume that each single-donor apheresis unit contains 3 x 10 11  platelets or that each whole-blood-derived platelet concentrate contains 5.5 x 10 10  platelets. Using this formula, if the platelet count increased by 20,000/μL in a patient who had a body surface area of 2.0 m 2  and who received one apheresis unit of platelets, the CCI is 20,000/μL x 2 ÷ by 3 = 13,333/μL.

Refractoriness is defined as a CCI value below 2,500 platelets/μL at 18 to 24 hours post-transfusion or a value below 4,500 platelets/μL at 10 to 60 minutes post-transfusion 2    on two to three consecutive platelet transfusion episodes. A less rigorous approach is to assume that, for an average size, non-refractory adult, the platelet count increment will be at least 10,000/μl to 20,000/μL one hour after the transfusion of either one unit of apheresis platelets or an equivalent dose of pooled platelets (5-6 combined random-donor platelet concentrates are equivalent to 1 apheresis unit), recognizing that the number of platelets per component unit may vary widely.

Non-immune causes of platelet refractoriness predominate.

Non-immune factors are present in the majority (72-88%) of transfusion-refractory patients, and immune causes are present in a minority (25-39%). 2   Non-immune factors, most of which are prevalent in a high proportion of hematology-oncology patients requiring prolonged platelet transfusion support, include splenomegaly, fever, infection, DIC, bleeding, and drugs such as vancomycin and amphotericin, are associated with platelet refractoriness. 2 , 3    The mechanism for refractoriness associated with various drugs is partially mediated by drug-dependent platelet antibodies, although specific testing for such is not widely available and unlikely to be of practical help.

Use of fresh ABO-matched platelets can improve transfusion response.

Platelets express blood group A and B antigens, but they are often transfused without ABO matching. Major ABO incompatibility (such as group A platelets transfused into a group O recipient) can decrease post-transfusion increments. A trial of fresh ABO-matched platelets can be a valuable temporizing measure while investigation of the basis of platelet transfusion refractoriness is ongoing.

HLA alloimmunization is prevented by the transfusion of leuko-reduced red blood cells and platelets.

Antibodies to HLA antigens account for the overwhelming majority of cases of immune platelet refractoriness, with antibodies to platelet-specific antigens being much less common. HLA alloimmunization may occur in response to prior pregnancies or to transfusions, although only a subset of alloimmunized individuals demonstrates immune platelet refractoriness . The TRAP study 4    showed that filtration-removal of leukocytes and ultraviolet B irradiation to inactivate leukocytes were equally effective in preventing the development of platelet transfusion refractoriness, which occurred in 16 percent of control patients, compared with 7 to 10 percent of patients who received leuko-reduced or irradiated platelets. On the other hand, HLA antibodies developed in 45 percent of control patients compared with 17 to 21 percent of intervention patients. Outcomes were equivalent for filtered apheresis platelets and for filtered pooled platelets. In Canada, universal prestorage leuko-reduction of platelets has lessened the incidence of alloimmune platelet refractoriness from 14 to 4 percent. 5    Almost all apheresis platelet units and more than 80 percent of packed red blood cell units in the United States are leuko-reduced by filtration either at the time of collection or immediately prior to storage.

HLA typing and antibody testing are complementary approaches.

Platelets express only HLA Class I antigens. For patients who are candidates for allogeneic stem cell transplantation, HLA typing results may already be known. Most HLA laboratories have adopted high-throughput molecular methods for genotyping HLA Class I and II antigens. A sequence-specific oligonucleotide probe method requires only small amounts of DNA and therefore can be performed on samples from neutropenic patients. Low-resolution HLA-A and B typing (Class I antigens) is adequate for the management of platelet alloimmunization, while high-resolution typing, including sequencing, is reserved for HLA Class II typing to select stem cell donors.

HLA antibody detection can be performed using a variety of methods. 3   Multiplex flow cytometric bead assays are more sensitive than traditional ELISA. 6    In the former assay, patient serum or plasma is incubated with color-coded microbeads that are coated with HLA antigens. Flurochrome-labeled anti-human IgG is added, and a flow analyzer is used to determine the color code of the reactive beads with a computer algorithm determining the specific antigens to which the antibody is reactive. The panel-reactive antibody (PRA) represents the percent of HLA targets to which the patient has made antibodies. PRA can be determined by using the traditional lymphocytotoxic assay, by ELISA, or by fluorescence-based microbead method. Serial assays are useful in assessing candidates for organ transplantation, but less so for management of platelet-refractory patients because a numerical PRA result (the percentage of the population to which the patient has HLA antibodies) does not provide actionable information to guide platelet selection.

Strategies to select platelets for refractory patients include HLA-matching, avoidance of known HLA antibody specificities, and platelet cross-matching.

For the purpose of platelet donor selection, a grading system (with designated categories A, B1, B2 C, D) is employed. A perfect four-antigen match (2 loci each at HLA-A and HLA-B) is grade A. In a B1 match, all of the donor’s HLA antigens are present in the recipient, but the donor lacks one of the recipient’s HLA antigens; in a B2-match, all of the donor’s HLA antigens are present in the recipient, but the donor lacks two of the recipient’s HLA antigens; in a C-match, the donor has one HLA antigen that is not present in the recipient; in a D-match, the donor has more than one HLA antigen that is not present in the recipient. High-grade matched donors (grade A, B1, or B2) are specifically recruited to donate platelets for a particular patient, but transfusion with grade C or D “matched” units is unlikely to produce a clinically meaningful incremental increase in the platelet count. This grading approach to matching also allows for categorization of antigens into cross-reactive groups (CREG). For example, HLA-A1 and A36 are within the same CREG, so if a patient has the A36 antigen and no available donor platelet is A36 positive, then an A1 donor platelet – typically more prevalent in the Caucasian population – can be used in a grade B match. HLA Matchmaker is an epitope-based computer algorithm used in some centers to identify permissible donor platelets that are more likely to yield adequate platelet increment increases without being HLA matched. 7    Despite the resources invested in the management of patients who are refractory to platelet transfusion, a recent review of the literature identified no studies that were adequately powered to detect an effect of transfusion of HLA-matched platelets on mortality or hemorrhage. 8    Prospective studies utilizing current technology and examining clinical outcomes are needed to evaluate the effectiveness of HLA-matched platelet transfusion. 8  

For management of the transfusion-refractory patient, available data argue that selection of donors with HLA antigens against which the recipient does not have antibodies is a better strategy than HLA matching. In one observational study involving 29 refractory patients and a database of more than 7,000 HLA-typed donors, a mean of 39 donors were HLA grade A or B matched, but a mean of 1,426 donors were identified as permissible by antibody exclusion. 9    Post-transfusion platelet count increments were comparable for the two strategies. HLA antibody testing should be repeated at periodic intervals because antibody specificities may evolve over time.

Platelet cross-matching tests the patient’s serum against samples of available donor apheresis platelets using a solid-phase adherence assay or an ELISA. A recent study found a mean CCI of 7,000 at one hour in more than 400 cross-matched platelet doses transfused to 71 refractory patients. 10    Platelet cross-matching can be done within a few hours compared with several days for HLA testing, but it does involve frequent repeat testing because the shelf-life of platelets is five days. Automated platforms are invaluable in making this approach efficient and practical. 1    A recent shortage of the commercial kits used for platelet cross-matching in the United States is expected to be resolved by early 2014.

A comparison of some of the advantages and disadvantages of the three strategies for dealing with refractoriness to platelet transfusion is contained in the table. Choice of method depends on local resources, and communication between the hematologist and the transfusion service is critical to ensure that donor selection is appropriate and that valuable resources are not wasted or used inappropriately.

Anti-fibrinolytic agents can be a useful adjunct for mucosal bleeding.

Other approaches to ameliorating the consequences of alloimmune platelet refractoriness include infusion of IVIgG, citric acid treatment of platelets to remove Class I HLA epitopes, and infusion of recombinant activated FVII in actively bleeding patients. Despite anecdotal reports of success, none of these approaches has been validated for clinical use. Use of family members as platelet donors for patients who are potential allogeneic SCT candidates is controversial, based on a theoretical concern for inducing alloimmunization that may jeopardize engraftment. Anti-fibrinolytic agents such as epsilon-aminocaproic acid and tranexamic acid, however, can be useful in platelet-refractory patients with oral mucosal bleeding.

Author notes

The update/commentary section was added in 2016 when this article was included in the Ask the Hematologist Compendium .

Competing Interests

Dr. Quillen indicated no relevant conflicts of interest.

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• Volume 2, Issue 3
• Risk Factors for Alloimmunisation after red blood Cell Transfusions (R-FACT): a case cohort study
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• Saurabh Zalpuri 1 ,
• Jaap Jan Zwaginga 1 , 2 ,
• J G van der Bom 1 , 3
• 1 Sanquin-LUMC Jon J van Rood Center for Clinical Transfusion Research, Leiden, the Netherlands
• 2 Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, the Netherlands
• 3 Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
• Correspondence to Saurabh Zalpuri; s.zalpuri{at}lumc.nl

Introduction Individuals exposed to red blood cell alloantigens through transfusion, pregnancy or transplantation may produce antibodies against the alloantigens. Alloantibodies can pose serious clinical problems such as delayed haemolytic reactions and logistic problems, for example, to obtain timely and properly matched transfusion blood for patients in which new alloantibodies are detected.

Objective The authors hypothesise that the particular clinical conditions (eg, used medication, concomitant infection, cellular immunity) during which transfusions are given may contribute to the risk of immunisation. The aim of this research was to examine the association between clinical, environmental and genetic characteristics of the recipient of erythrocyte transfusions and the risk against erythrocyte alloimmunisation during that transfusion episode.

Methods and analysis Study design Incident case–cohort study.

Setting Secondary care, nationwide study (within the Netherlands) including seven hospitals, from January 2005 to December 2011.

Study population Consecutive red cell transfused patients at the study centres.

Inclusion The study cohort comprises of consecutive red blood cell transfused patients at the study centre.

Exclusion Patients with transfusions before the study period and/or pre-existing alloantibodies.Cases defined as first time alloantibody formers; Controls defined as transfused individuals matched (on number of transfusions) to cases and have not formed an alloantibody.

Statistical analysis Logistic regression models will be used to assess the association between the risk to develop antibodies and potential risk factors, adjusted for other risk factors.

Ethics and dissemination Approval at each local ethics regulatory committee will be obtained. Data will be coded for privacy reasons. Patients will be sent a letter and an information brochure explaining the purpose of the study. A consent form in presence of the study coordinator will be signed before the blood taking commences. Investigators will submit progress summary of the study to study sponsor regularly. Investigators will notify the accredited ethics board of the end of the study within a period of 8 weeks.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode .

https://doi.org/10.1136/bmjopen-2012-001150

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Article summary

Article focus.

Identifying transfusion-related risk factors of alloimmunisation against red blood cell (RBC) antigens.

Identifying clinical risk factors of alloimmunisation against RBC antigens.

Identifying environmental and genetic risk factors of alloimmunisation against RBC antigens.

Key messages

Alloimmunisation against RBC transfusion is a clinically relevant problem faced by transfusion specialists.

Identifying a high-risk group of responders who form allantibodies against transfused RBCs would be the next step towards transfusion of complete phenotyped matched RBC.

In synergy with other ongoing studies, cost-effectiveness of a phenotyped matched RBC approach will be assessed.

Strengths and limitations of this study

Multicentre, matched case–cohort design.

Good representative sample of controls from large base cohort of general population.

Cases and controls matched on the number of RBC transfusions.

Possibility that patients entering cohort have had transfusions prior to start of study period in other hospitals/non-study centres.

Previous pregnancies in women could play a role in alloimmunisation. Retrospective data will not allow for a comprehensive check on previous pregnancies.

There could be a few cases selected who are booster/secondary alloimmune responders, instead of first time ever alloantibody formers.

Introduction

Individuals exposed to red blood cell (RBC) alloantigens through transfusion, pregnancy or transplantation may produce antibodies against the alloantigens expressed by RBCs. Although the incidence of these events is debated and ranges between the percentages of 1%–6% in single transfused and up to 30% in polytransfused patients (eg, sickle cell disease, thalassaemia and myelodysplasia), 1 they can pose serious clinical problems such as delayed haemolytic reactions as well as logistic problems, for example, to obtain timely and properly matched transfusion blood for patients in which new alloantibodies are detected. Of course, prevention of alloimmunisation by extended matching between donors and all transfused patients (ie, on the basis of typing patients for the most relevant RBC antigens) would be an ultimate but complicated and costly solution. However, matching of donors only for patients who are defined to have a high alloimmunisation risk would be a more feasible step forward. This strategy would be especially valuable because as soon as immunisation for one antigen develops, additional immunisations tend to develop more frequently. 2 3

Characterisation of patients and clinical conditions with high immunisation risk can be derived from studying the possible correlations between the actual immunisation and patient-related factors (both genetic and acquired) and/or transfusion-associated situations.

Such a study comparing immunised and non-immunised patients with a similar transfusion history will generate RR or relative protective factors.

We expect a twofold impact from our study: (1) to identify a set of transfusion recipients who need to be extensively matched and (2) to help understand the mechanisms underlying the development of alloantibodies to erythrocyte transfusion.

Rationale/background

Alloantibodies can lead to serious clinical consequences and logistic problems like obtaining properly and timely matched blood for the patients who do develop these antibodies. Prevention of such serious events is possible by extended matching and typing of donor's blood against the patient's for all the possible antigens, but this process is cumbersome and costly. Identifying a high-risk group will be a feasible first target and advanced matching a big step forward, and the aim of our study.

It is known that the recipient's formation of antibodies depends not only on dose and route of administration and the immunogenicity of the antigen but probably also on genetic or acquired patient-related factors. It has been shown that the number of transfusions also plays an important role in alloimmunisation against RBC, with the risk increasing with the increasing number of transfusions. 4 It is generally recognised that immunocompromised patients have a lower risk to develop such antibodies. 5 Relatively little is known, however, about other patient-related risk factors. 2 3 6–9

A recent study examined such patient-related risk factors in a case–control study among 101 cases developing erythrocyte alloantibodies and 87 controls. 10 In this two-centre study, patients with first time detected antibodies and at least one transfusion in the past were compared with controls with a negative antibody screening in the same centre. After adjustment for a limited number of confounders, this study confirmed known risk factors for antibody formation, such as female sex (increased risk, since women are more susceptible to exposure of alloantigens during pregnancy, miscarriages, abortions and childbirth 11 ), lymphoproliferative disease and leukaemia (lower risk attributed to lymphocyte dysfunction by concomitant chemotherapy and suppression of the immune response 12 ). Also new and partly unexpected risk factors were found, such as diabetes and solid tumours (both increased risk). Although the latter patients do undergo chemotherapy as well, in this group, antibodies might develop more easily because of their chronic inflammatory state. 13 The limitations of this case–control study, 10 however, were (1) the selection method for controls favoured controls that had received more transfusions with also smaller transfusion time intervals compared with the cases, (2) the relatively small number of patients reducing the detection of smaller RRs and (3) a relatively crude assessment of only a limited number of potential risk factors. Additionally, the study design did not allow investigating the association with the actual factors at the time of the likely primary immunisation/causal transfusion. We will not only try to confirm the observed potential risk factors in a larger cohort, but we aim to find other clinical, environmental as well as genetic factors. There is well-documented evidence that certain human leukocyte antigen (HLA) types are associated with enhanced response to RBC antigens like Kell, Duffy and Kidd. 14–16 HLA genes in this respect are particularly interesting because along with their polymorphisms, they have been shown to play an active role in autoimmune disorders and diseases, which develop via T cell-mediated immunity. 17 Moreover, several of these genes have been identified in human studies to be associated with susceptibility and resistance to mycobacterial infection. Another strong correlation was shown between immunodeficient genotype (interferon γ receptor 1 deficiency) and responsiveness to mycobacterium antigen. 18 Finally, specific single nucleotide polymorphism (SNP) associations have been identified to play a role in viral immunity and variations in both humeral and cellular immunity following measles vaccination. 19 20 Although many genes are involved in the immune system, SNP's in genes (eg, coding for HLA types) that modulate specific and innate immune responses will be of the first targets in our analyses. We hypothesise that this will yield genetic modulators on the patients' humoural response to particular erythrocyte-expressed antigens but maybe even more broadly to other antigens as well.

By our questionnaire, we will query environmental, lifestyle factors and socioeconomic status as those have been suggested to modulate the immune response. Environmental factors such as exposure to helminthic, fungal and parasitic infections do play a role in modulating the general set point of the immune response at young age. 21 The same is true for living in unsanitary conditions and for unhygienic occupations throughout life. 22 Additional information on ‘immune modulating’ conditions during childhood and youth will be collected from the vaccination status, completion of the vaccination programme, presence of pet animals, place of residence (urban/rural) and visits to day care centres during childhood. The questionnaire will add to the knowledge to these possible confounders in cases and controls.

Research objective

The aim of the project was to examine the association between clinical, environmental and genetic characteristics of the recipient of erythrocyte transfusions and the risk of immunisation against erythrocyte alloantigens that he/she was exposed to during that transfusion episode.

Methodology

Study design and study population.

We will perform a retrospective matched case–cohort study at hospitals nationwide from a period January 2005 to December 2011. Large RBC using hospitals will be selected as study bases. The study cohort will comprise of consecutive RBC transfused patients at the study centre.

Cases are defined as first time ever irregular RBC antibody formers, with no history of RBC transfusions and alloimmunisation before the study period.

Controls will be all consecutive transfused patients who had received their first and subsequent red blood transfusions at the study centre with no history of RBC transfusions and alloimmunisation.

Observational studies, if well conducted, are equipped to examine interesting transfusion research questions. With that in mind, we chose a case–cohort study design for our study. With the help of such a design, we can compare the cases occurring in a RBC transfused cohort with a randomly selected sample of the cohort. Using such an approach, for any one given case, we will select two controls that have had at least the same number or more transfusions than the case itself. This approach has following advantages:

This ensures that all the patients in the transfusion cohort with same or higher number of transfusions have an equal chance of being picked as controls. In essence, any member of the cohort who has been at a similar transfusion risk (of alloimmunisation) at some point in their transfusion history can be selected as a control.

Cases also have an equal chance of getting selected as controls for other cases.

This study design minimises the selection bias, if any. Such a study design allows us to include a number of patients, which is sufficient to detect smaller effects and to adjust for other risk factors, as well as to document potential risk factors extensively.

We will take into account the number of transfusions a particular case received until the antibody-forming episode and match the two cases (selected per control) on the same number of transfusions.

To account for interhospital differences nationwide, we will also match the cases and controls on the site/study centre ( figure 1 ).

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Flowchart of study design for the matched control group.

Implicated period

To examine the immunomodulating clinical risk factors surrounding the transfusions preceding the date of alloantibody formation, we will define a clinical risk period or an implicated period of alloimmunisation during which the case would have formed an irregular RBC antibody. This period would be the time (in days) between the date of a first ever positive screen for alloantibody to a calendar date 30 days before that positive screen. We will also introduce a lag period of minimum 7 days between that first ever positive screen and the last ever transfusion ( implicating transfusion ) before that positive screen ( figure 2 ). This is to ensure that a patient's immune system has adequate time to respond to the transfusion exposure.

Implicating period of clinical data collection.

We will define a similar implicated period in the matched controls as well, retrospectively from the implicating transfusion to 30 calendar days back ( figure 2 ).

First time formed alloantibody

Our endpoint for cases, or first time formed irregular RBC antibodies is defined as clinically significant antibodies as screened by a three-cell serology panel at 37°C. All patients were routinely screened for alloantibodies, which is repeated at least every 72 h, if further transfusions as required. The antibodies are screened for by a three-cell panel, including an indirect antiglobulin test (LISS Diamed ID gel system, DiaMed-ID system, DiaMed, Murten, Switzerland) and subsequently identifies by a standard 11 cell panels in the same gel system.

Data acquirement, measurements and handling

Transfusion cohort data will be acquired from the hospital blood transfusion services and on-site patient records. Second, we will use data from a patient questionnaire. Third, we will determine the patients' racial background from blood of the included and consenting patients.

Patient medical history and records

Potential clinical risk factors include haematological, oncological, surgical and medicinal data as well as autoimmune diseases and related conditions at the time of the implicated (likely causal) transfusion. Factors and conditions that will be actively scored are: infections (including the causal microorganisms) and active/chronic allergies (including the if known antigens), fever, cytopenia(s), systemic inflammatory response (a clinical response to a (non)-specific insult of either infectious or non-infectious origin), peripheral blood progenitor cells transplantation (autologous or allogenous), multitrauma, splenectomy, solid malignancies, autoimmune disorders (rheumatoid arthritis, diabetes mellitus type 1, etc), chemotherapy, immunosuppressive drugs, cytostatics and antibiotics will be studied.

Questionnaire

Participants will be asked to fill out a printed questionnaire. The participants have also the option to fill in a web-based questionnaire, which will be accessible via a link provided in the information letter. After identification of control patients, a similar mailing will be sent to these controls.

Environmental and lifestyle factors like vaccination status, previous pregnancies in case of females, level of education and current professions (as a proxy for socioeconomic status) will be obtained via the patient information questionnaire. The questionnaire will add to the knowledge to these possible confounders in cases and controls.

In general, many questions will involve ‘life-time’ risk factors and information and are not particularly targeted at the time of implicated episode.

Racial confounder

Based on the knowledge that different ethnicities have varying frequencies of erythrocyte antigens, a so-called mismatch between a donor from one particular ethnicity and the recipient of another ethnicity does play a role in developing immune response to donor erythrocytes. Therefore, we will also attempt to document racial mismatch leading to RBC alloimmunisation. This is attempted by one question in the questionnaire but will foremost rely on the blood group typing, which usually determines the ethnicity.

Blood research and sampling

To investigate the effect of genetic factors on the risk of the development of alloantibodies, we will collect blood samples from all participants for extensively typing the blood to get an antigen profile and to look at genetic markers, which influence immune system and vaccination efficiency. SNP's in candidate genes (eg, coding for HLA types) modulating specific and innate immune responses will be assessed. Biomarkers typical for the activity of the immune response: cytokines and titres of antibodies against common (vaccinated) antigens can later be determined in the plasma and serum that are stored as well.

Statistical analysis

We expect to include a total of 500 case patients and 1000 controls.

Logistic regression models will be used to assess the association between the risk to develop antibodies and potential risk factors, adjusted for other risk factors and for the number of exposures to the antigen.

We will examine the association between the risk factor and alloimmunisation using logistic regression.

We will also make a selection of all cases and controls on the most frequently found antibodies and if the relative impact of risk factors and immune modulators on the risk of all the antibody types (in separate analysis) is in the same direction, we will make a generalised observation.

With 1500 patients, and the conventional 80% power and a p value of 0.05, we will be able to detect effects (OR) of dichotomised risk factors of 1.35 or higher.

An additional analysis will be performed along the lines of a ‘case-crossover’ design within the case patients. The ‘Hazard Period’ (time period right before the detection of a positive antibody) will be compared to a ‘Control Component’ (a specified time period other than the Hazard Period) in the case patient's medical history and the RR for the transient effect risk factors will be calculated.

Ethical considerations

Regulation statement.

The study will have a multicentre design subjecting patients to a questionnaire and additional blood sampling. After approval by the central Medical Ethical Committee (MEC) of the Leiden University Medical Center (LUMC), the study clearly requires a local Medical Ethical Committee approval for each site that detects a probable transfusion-mediated alloimmunisation. Help of local investigators, usually the local haematologist or clinical chemist in charge of the transfusion laboratory, will be recruited to substantiate implementation of the study at the various sites. Each local investigator will in fact be responsible for ensuring that the study will be conducted in his centre in accordance with the protocol, the ethical principal of the Declaration of Helsinki, current International Conference on Harmonization (ICH) guidelines on Good Clinical Practice and applicable regulatory requirements.

Recruitment and consent

Data will be collected at each hospital site, Sanquin and from medical records and files. All data will be coded for privacy reasons. As said, after identification of cases and controls, patients will be sent a short and concise letter and an information brochure explaining the purpose of the study. This letter will be combined with the questionnaire and foremost—an answer card expressing willingness or refusal to participate in the study to fill in and return to the study's contact address. Participants, moreover, will have an option of filling in the questionnaire via the study's website. The web link access will be explained in the patient information. After receiving a patient's positive response to our request to participate, a follow-up call will be made by the investigator to answer any additional queries and if applicable to make an appointment for the blood taking. The patients would be invited to LUMC or the participating centres for blood taking. Additionally to the signed answer card for blood taking, patients would be informed about the study once again at the blood taking appointment, and a final consent form in presence of the study coordinator and data manager will be signed before the blood taking commences. Proper tubing and transfer material will be provided to the non-LUMC sites.

The patient burden

The reading of the information and completing the questionnaire (estimated to take about 10 min) will be of minimal patient burden or stress and is absolutely voluntary. Apart from the questionnaire, the protocol involves a single blood sampling of 25 ml as main discomfort for cases and controls. However, the blood taking will preferably be combined with a regular control and if possible a blood sampling.

The blood taking will be organised centrally at the LUMC upon invitations. There are no further interventions within the study protocol. The study has absolute minimum invasive risk for the patients.

Medical information, data and sample handling and reports

Per patient an electronic Case Record Form (CRF) with a unique study number (identifier) will be made. The CRFs will be subjected to independent data management. The principal investigators, Anske van der Bom and J J Zwaginga, will be responsible for the CRF and data management.

Patient-identifying parameters such as name, the hospital patient number and the full birth date will not be entered and found in the electronic CRF. The key between these identifying data and the unique study number will be only available to the data management at the Department of Epidemiology. These patient-identifying parameters are only needed for sending the questionnaire and making an appointment for blood taking, which will be done by the data management. The blood taking and further sampling will involve relabelling of the tubes to the specific study number.

There will be a provision to keep the patient personal details for the entire duration of storage of blood samples, with a possibility to track back and identify the patients with their blood samples. Coding measure will ensure that this information is not available to a third party and is only accessible via an encoding key to the principal investigators of the R-FACT study. Individual medical and investigational information obtained during the study is considered confidential and disclosure to third parties is prohibited. The described strategy will guarantee effective study of data together with maintaining optimal patient privacy.

The blood samples will be stored in state-of-the-art storage facilities at the LUMC, with storage management software for 20 years.

The research, patient information, blood sampling and storage will be conducted in accordance with LUMC's Good Research Practice guidelines.

Withdrawal of individuals

Subjects can decide to have their samples removed from the serum, plasma, DNA and RNA bank and thus from further research in the future at any time and for any reason, that is, meaning without consequences for their further clinical treatment.

Independent physician

Before consenting, patients can gather information or advice from the investigator and also from an independent physician. This name will be provided in the patient information.

Objection by minors or incapacitated subjects

Not applicable.

Group-related risk assessment and benefits

Administrative aspects and publication, handling and storage of data and documents.

Data handling will comply with the Dutch Personal Data Protection Act.

A data manager (employed on the project) and the PhD fellow will extract data from the study sites and recode patients and locations to unique study codes under which non-patient identifying data are filed in a CRF per patient.

There will be no specific physical CRFs because of the massive patient/control numbers and electronic data sets can be often automatically extracted from the patient information systems present in most hospitals.

All amendments will be notified to the MEC that gave a favourable opinion.

Annual progress report

The investigators will submit a progress summary of the study to Sanquin as sponsor of the study regularly. Information on inclusion of cases and controls, other problems and amendments will be provided as required by the regional and local MEC's.

End of the study report

The investigator will notify the accredited MECs of the end of the study within a period of 8 weeks. The end of the study is defined as the last data collected from medical records and case–control questionnaires.

Public disclosure and publication policy

The final publication of the study results will be written by the study coordinator(s) on the basis of the statistical analysis performed. A draft manuscript will be submitted to all co-authors for review. After revision, the manuscript will be sent to a peer-reviewed scientific journal.

Any publication, abstract or presentation based on patients included in the study must be approved by the study investigators and collaborators.

Expected results

Our case–cohort study will quantify and characterise risks of patients and conditions for transfusion-associated alloimmunisation, although a prospective serology study involving a first transfused cohort would be most preferable to add to the insight in primary immunisation (risk). However, 50% of first transfused patients never need new blood again and escape follow-up if not recalled. Moreover, the occurrence for the other 50% of the following transfusion period is quite variable. Therefore, a prospective study is viewed as cumbersome. On the more practical side for a case–control study, 50% of the transfused patients have been transfused before and these in principle are eligible as case or control patients. Indeed, in accordance by the rules for inclusion, these patients are already transfused at two different periods at least. Therefore, if we can define risk factors for alloimmunisation, then advanced matching of blood donors for this group should be regarded as valuable. Finally, strong synergy will be obtained between our study and the MATCH study by Schonewille et al . In the latter study, logistical/cost/and benefit aspects of advanced matching after formation of a first antibody will be determined.

Our study will contribute to classifying patients who could benefit from additional or extended typing and donor matching to prevent alloimmunisation. We envision to contribute to a matching policy based on a prognostic risk score for immunisation in general transfused patients.

• Nadjahi J ,
• Schonewille H ,
• van Zijl AM
• Drenthe-Schonk AM
• Zalpuri S ,
• Zwaginga J ,
• Narvios A ,
• Lichtiger B
• Cornell FW ,
• Shukla JS ,
• Chaudhary RK
• Reisner EG ,
• Kostyu DD ,
• Phillips G ,
• Wiersum-Osselton J ,
• Schipperus M ,
• Hoeltge GA ,
• Rybicki LA ,
• Seyfried H ,
• Hendrickson JE ,
• Desmarets M ,
• Deshpande SS ,
• Reviron D ,
• Dettori I ,
• Ferrera V ,
• Chiaroni J ,
• Noizat-Pirenne F ,
• Tournamille C ,
• Bierling P ,
• Dorman SE ,
• Ovsyannikova IG ,
• Vierkant RA ,
• Cunningham JM ,
• Larcombe L ,
• Rempel JD ,
• Dembinski I ,
• McDade TW ,
• Rutherford JN ,

Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Files in this Data Supplement:

• Data supplement 1 - Online Funding Statement

To cite: Zalpuri S, Zwaginga JJ, van der Bom JG, et al . Risk Factors for Alloimmunisation after red blood Cell Transfusions (R-FACT): a case cohort study. BMJ Open 2012; 2 :e001150. doi: 10.1136/bmjopen-2012-001150

Collaborators (1) Dr H Schonewille, Sanquin-LUMC Jon J van Rood Center for Clinical Transfusion research, Leiden, the Netherlands; (2) Professor JP Vandenbroucke, Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands; (3) Professor A Brand, Sanquin-LUMC Jon J van Rood Center for Clinical Transfusion research, Leiden, the Netherlands; (4) Professor E Briët Former Director, Sanquin Blood Bank, the Netherlands.

Contributors All the above-mentioned authors fulfil the ICMJE guidelines criteria for authorship. All the authors have equally made: (1) substantial contributions to conception and design, acquisition of data or analysis and interpretation of data; (2) drafting the article or revising it critically for important intellectual content and (3) final approval of the version to be published.

Funding This ongoing clinical study is funded by not-for-profit organisation—Sanquin Blood Supply, the Netherlands, grant number PPOC-08-006.

Competing interests None.

Ethics approval Ethics approval was provided by the Medical Ethical Committee, Leiden University Medical Center.

Provenance and peer review Not commissioned; internally peer reviewed.

Data sharing statement No additional data are available.

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Abbreviation key.

Instructional Methods AL = Active Learning (case-based learning, team-based learning, problem-based learning) CE = Clinical Experience DT = Didactic Teaching IL = Independent Learning S = Simulation, Role Play

Assessment Methods CDR = Clinical Documentation Review CP = Clinical Performance Ratings/Checklist DO = Direct Observation MCQ = Exam (institutionally developed or nationally normed/standardized, subject) 2 OSAT = Exam (institutionally developed, technical skill) 3 OE = Exam (institutionally developed, oral) OSCE = Exam (institutionally developed, clinical performance; standardized patients can be used here) 4

Emerging Topics BSR = Basic Science Related E = Ethics GE = Genetics GH = Global Health N = Nutrition OUD = Opioid User Disorder PM = Pain Management RX = Pharmacology SS = Surgical Skills

Competence Level 1 K = Knows (Knowledge) KH = Knows How (Competence) SH = Shows How (Performance) D = Does (Action)

APGO Electronic Resources BCS = Basic Clinical Skills Curriculum BSV = Basic Science Videos EP = Effective Preceptor Series ES = Educational Services M1 = Milestone 1 Cases OTC = Online Teaching Cases and Videos uW = uWISE and PrepforRes

ACGME Competency PC = Patient Care MK = Medical Knowledge PBLI = Practice-Based Learning and Improvement ICS = Interpersonal and Communication Skills P = Professionalism SBP = Systems-Based Practice

HSS HP = Health Policy and Advocacy IP = Interprofessional Teamwork L = Leadership PH = Population Health PS = Patient Safety QI = Quality Improvement SD = Social Determinant VBC = Value-Based Case

1   As defined by Miller, GE in The assessment of clinical skills/competence/performance. Acad Med 1990;65:S63-7. 2   Multiple Choice Question Examination 3   Objective Structured Assessment of Technical Skills 4   Objective Structured Clinical Examination

Using the filters below, select criteria for your search and build a customized list of Intended Learning Objectives for your curriculum. View the Abbreviation Key to determine section criteria.

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