Unrelated donor choices for allogeneic hematopoietic cell transplantation in Canada: an evaluation of factors influencing donor selection
Bibliographic record
Abstract
BACKGROUND: Utilization of unrelated donors and cord blood units (CBUs) for allogeneic hematopoietic cell transplantation continues to increase. Understanding the practices of donor selection by transplant centers is critical for unrelated donor registries and cord blood banks to optimize registry composition and inventory to meet patient need. STUDY DESIGN AND METHODS: Unrelated donor and CBU selection practices of Canadian transplant centers served by Canadian Blood Services' OneMatch Stem Cell & Marrow Network (OM) were reviewed, including HLA match level, locus of disparity, age, sex, and product choice (donor vs. CBU). RESULTS: HLA-matched donors within OM and/or international (INT) registries were preferentially investigated, underscoring the primary importance of HLA matching. In the case of HLA-mismatched donors, HLA-A disparities were most common while DRB1 mismatches were least common. Advanced age, sex, and lack of donor availability were the most frequent reasons that high-probability OM donors were overlooked in favor of INT donors. High-probability 10 of 10 HLA-matched female donors from OM were often avoided in favor of INT male donors. Use of female donors, however, increased in cases restricted to more HLA-disparate donor options. Caucasian patients were more likely to find 10 of 10 matched donors, whereas use of mismatched donors and CBUs were more prevalent among non-Caucasian patients. CONCLUSIONS: Recruitment and retention of young, male donors from diverse ethnic backgrounds may increase the usage of histocompatible OM donors for patients in need.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".