Availability of Multiple HLA-Matched Unrelated Donors for Allogeneic HCT Recipients
Bibliographic record
Abstract
Introduction Success of allogeneic hematopoietic cell transplantation (HCT) is marred by adverse outcomes that include relapse of underlying malignancy, graft versus host disease (GVHD), and post-transplant viral infections. An ideal approach to minimize these adverse outcomes is to select an immunogentically ideal donor for each HCT recipient that not only has minimum allogeneic disparity with the recipient but also possesses an immunogenetic predisposition for strong anti-leukemic and anti-viral immune responses. In addition to human leukocyte antigen (HLA) compatibility, several other immunogenetic systems like killer Immunoglobulin-like receptors (KIRs) and variants in cytokine genes have shown promise in reducing HCT adverse outcomes. Their clinical utility in improving donor selection can only be assessed if for every patient there are more than one HLA matched donors available. Objectives In this study, a retrospective analysis of World Marrow Donor Association (WMDA) Search & Match Service search reports were performed for potential HCT recipients from a single center to assess how many allele level HLA matched donors were available for each recipient. Methods A retrospective, manual review of WMDA (formerly Bone Marrow Donors Worldwide) search reports for recipients seeking unrelated allogeneic HCT at Alberta Blood and Marrow Transplant Program in 2017 was performed (n=110). Patients were predominantly Caucasians. Allele-level match at HLA-A, HLA-B, HLA-C, and HLA-DRB1 was considered in determination of match level (n/8). The number of potential 8/8 and 7/8 matched unrelated donors were recorded. Donor prospects were categorized as ‘potential donor': total number of donors presented in WMDA search report; ‘high-probability donors': subset of donors known or highly-favored to match the patient; and ‘optimal donors': subset of high probability donors who were male and age ≤ 35. Results When 8/8 HLA matching was considered, more than one ‘potential', ‘high-probability' and ‘optimal' unrelated donors were available for 93%, 67% and 57% recipients respectively. When 7/8 HLA matching was considered, more than one ‘potential', ‘high-probability' and ‘optimal' unrelated donors were available for 100%, 98% and 94% recipients respectively. Conclusions Multiple HLA-matched unrelated donors are available for majority of HCT recipient of Caucasian ethnicity in BMDW search. These findings provide an ideal platform for prospective studies/clinical trials on unrelated HLA-matched HCTs to assess other non-HLA immunogenetic systems for finding an immunogenetically ideal donor (e.g., HLA matched and possessing favorable KIR or cytokine variants) for every HCT recipient.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".