Goey, Steven R. De

Abstract Background: Platelet transfusions are important for supporting patients with hematologic disorders. Refractoriness to platelet transfusions may lead to serious complications and pose a challenge to clinical management. A variety of laboratory strategies to optimize transfusion support in this population are being used; however, data on clinical correlation and success of these interventions is limited. We report the laboratory testing, transfusion yield, and clinical correlation in a cohort of patients receiving cross-matched platelet units. Methods: All consecutive adult patients refractory to platelet transfusions (failure to increment platelet count by 10 x 10(9) times two) with platelet crossmatch performed between June 2014 and April 2016 at our institution were included. Detailed clinical information, laboratory data of the crossmatch results, and Single Antigen Bead (SAB; Luminex) for each platelet unit cross-matched was retrospectively collected. Mean fluorescence intensity (MFI) of antibodies directed towards donor platelet HLA antigens identified through SAB were grouped into zones according to previously validated laboratory data: green zone (<4,000 MFI), yellow zone (4000-10000) and red zone (>10,000). Adequate transfusion yield was defined as an absolute increase of at least 10 x 10((9)/L platelets on a post-transfusion (i.e., within 1 hour) sample. Patients with major bleeding per International Society on Thrombosis and Haemostasis (ISTH) criteria, palpable splenomegaly, fever during transfusion, DIC, active sepsis, or antibodies directed against human platelet antigens were excluded from the final analysis. Importantly, the Hematologist and Pathologist were blinded to the other's data until collection was completed. Data analysis correlating adequate transfusion yield and laboratory parameters was performed. Results: 22 patients (72% female) met our study criteria. All patients had a hematologic malignancy with prolonged pancytopenia after chemotherapy, 4 (18%) had undergone allogeneic bone marrow transplantation. A total of 422 platelet cross-matches were performed, with 17 patients ultimately receiving 46 cross-matched units. The indication for transfusion was: prophylactic 35 (76%), bleeding 4 (9%) and peri-procedural 7 (15%). Ten (22%) transfusion events were excluded: splenomegaly 3, fever 4 and active severe bleeding 2. In one case a post transfusion platelet count was not performed. The overall success rate of transfusion was 64% (23/36). All transfusions leading to an adequate yield had a negative crossmatch. Of the 13 ineffective transfusions, 2 had a positive crossmatch. Based on single antigen MFI assignment, 26 (74%) donor units were classified as green zone, 8 (23%) yellow and 1 (3%) red. The success rates according to the single MFI zone assignment are presented in Table 1. These MFI-defined assignments were predictive of clinically successful transfusions. Conclusion: Selection of appropriate donor platelet units in refractory patients is a challenge that is managed in a variety of ways. While crossmatching is sometimes necessary, a strategy of antigen-avoidance can dramatically increase the identification of potentially effective platelet units for many patients. Understanding of how to navigate HLA antibody data is essential for identifying which HLA antigens should be avoided. Based on these data, in general, our practice is to avoid transfusing a platelet when there is a donor specific antibody of 8,000 MFI or greater. Furthermore, in our dataset there were two patients with both successful and unsuccessful transfusions after receiving crossmatch-negative units with green zone assignment. This finding highlights the limitations of laboratory testing and emphasizes the importance of post-transfusion platelet counts for continuously improving the platelet support of each immune-refractory patient. Disclosures No relevant conflicts of interest to declare.

BACKGROUND Platelet transfusion–refractoriness is a challenging and expensive clinical scenario seen most often in patients with hematologic malignancies. Although the majority of platelet transfusion–refractory cases are due to nonimmune causes, a significant minority are caused by alloimmunization against Class I human leukocyte antigens (HLAs) or human platelet antigens (HPAs). Such platelet transfusion–refractory patients can be effectively managed with appropriate antigen‐negative products. STUDY DESIGN AND METHODS Our institution has developed a diagnostic and management algorithm for the platelet transfusion–refractory patient with an early focus on identifying those cases caused by immune‐mediated factors. Using physical platelet cross‐matches to initially classify platelet transfusion–refractory patients as immune‐mediated or not, cross‐match–compatible inventory is then provided to immune‐mediated patients, whereas subsequent HLA (with or without HPA) testing is performed. RESULTS Our blood donor program performs Class I HLA typing of all repeat platelet donors to facilitate the identification of antigen‐negative platelet units (virtual cross‐matching) as well as the recruitment of HLA‐matched donors. The platelet transfusion–refractoriness algorithm realizes an initial net cost savings once two apheresis platelets are saved from use for each newly identified, immune‐mediated platelet transfusion–refractory patient. CONCLUSION An algorithm utilizing physical platelet cross‐matches, Class I HLA and HPA antibody testing, and upfront Class I HLA typing of platelet donors leads to overall resource savings and improved clinical management for platelet transfusion–refractory patients.

AbstractObjectiveHLA‐DPB1 matching may impact allogeneic hematopoietic stem cell transplantation (ASCT) outcomes; however, this locus is not in linkage disequilibrium with the remainder of the HLA genes. After classifying HLA‐DPB1 mismatches based on T‐cell epitope, avoiding non‐permissive mismatches may impact survival. We tested this hypothesis at a single academic institution.MethodsRetrospective HLA‐DPB1 genotyping was performed on 153 adult patients who underwent ASCT and unrelated donors matched for HLA‐A, B, C, DRB1, and DQB1 loci (10/10). Using the ImMunoGeneTics/HLA T‐cell epitope matching algorithm, mismatch status was classified as permissive or non‐permissive.ResultsOf 153 donor‐recipient pairs, 22 (14.4%) were HLA‐DPB1 matches, 64 (42.8%) permissive mismatches, and 67 (43.8%) non‐permissive mismatches. DPB1 mismatch increased risk of chronic graft‐versus‐host disease (cGVHD; RR 2.89 [1.19‐9.53], P=.016) compared with DPB1‐matched transplants, but there were no differences in overall mortality, risk of relapse, or acute GVHD (aGVHD). Combining matches and permissive mismatches and comparing to non‐permissive mismatches, there was no significant difference in overall survival or relapse; however, patients receiving non‐permissive mismatched transplants experienced greater risk of aGVHD overall and severe aGVHD (RR 1.66 [1.13‐2.44], P=.010 and RR 1.97 [1.10‐3.59], P=.024, respectively).ConclusionIn this single‐center study, HLA‐DPB1 matching influenced outcomes of patients undergoing ASCT for hematologic malignancy.

BackgroundIdentifying antibodies to HLA (anti‐HLA) by solid‐phase assays is used to screen blood donors to mitigate transfusion‐related acute lung injury risk. Various cutoffs for detection assays have been proposed in the literature; however, these do not take into consideration lot‐to‐lot variability of commercially available assays.Study Design and MethodsSamples from 93 nontransfused males were tested using five different lots of a multiplex bead‐based anti‐HLA detection kit. A subset of 17 samples was tested on 5 days using a single lot. An additional 96 samples from donations with varied anti‐HLA levels were tested using kits from two different lots. Results were reported as a normalized background (NBG) ratio.ResultsFor the 93 nontransfused donors, NBG values generated using the reference lot were significantly higher than those obtained with three of the four comparator lots. However, for the 96 samples with low‐, moderate‐, and higher‐level anti‐HLA, Class I (CL‐I) values were 1.4 times lower and Class II (CL‐II) values were 1.2 times lower using the reference versus comparator lot. For CL‐I antibodies the between‐lot standard deviation (SD) was 1.36 (95% confidence interval [CI], 1.19‐1.60), while the between‐day SD was 1.27 (95% CI, 1.08‐1.52). Similarly, for CL‐II antibodies the between‐lot SD was 0.81 (95% CI, 0.70‐0.95), while the between‐day SD was 0.50 (95% CI, 0.43‐0.60).ConclusionsThere is interlot variability in the tested HLA detection assay as well as significant bias between lots. It may be reasonable to develop a new cutoff when a new lot is obtained.