Reducing ethnic disparity in access to high‐quality HLA‐matched cord blood units for transplantation: analysis of the Canadian Blood Services' Cord Blood Bank inventory
Bibliographic record
Abstract
BACKGROUND: Launched in 2013, Canadian Blood Services' Cord Blood Bank (CBS' CBB) has built a high-quality, ethnically diverse cord blood repository that aims to reduce ethnic disparity in accessing suitable units for transplantation. METHODS AND RESULTS: As of December 2016, 2000 units have been banked. The self-reported maternal ethnicity was 58% non-Caucasian. Overall, 26% of units were classified as multi-ethnicity with Caucasian (84%) most frequently observed in combination with Asian, First Nations (predominant indigenous peoples in Canada south of the Arctic Circle), or African ethnicity. Utilization scores that incorporate total nucleated and CD34+ cell counts in the CBS' CBB were associated with greater likelihood of utilization compared with the international inventory of units (p < 0.05). The distribution of utilization scores was similar for Caucasians compared with non-Caucasians (p < 0.05). Using HLA genotypes of cord blood units and their mothers, we determined probable ethnic assignments for each haplotype using HaploStats (National Marrow Donor Program). Significant increases in HLA-match likelihoods are predicted for all ethnicities as the inventory grows to its target of 10,000 units and the gap in HLA-match likelihoods for Caucasian and non-Caucasian patients progressively declines. CONCLUSIONS: The CBS' CBB inventory is predicted to have high HLA-matching likelihoods across a broad spectrum of ethnic groups, improving access to high-quality stem cell products for all patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".