Impact of Ethnicity on Donor Search Results for Children Requiring Stem Cell Transplantation
Bibliographic record
Abstract
Hematopoietic stem cell transplantation (HSCT) can be curative for children with various malignant and nonmalignant conditions. Access to suitable unrelated living donors (ULDs) or unrelated cord blood (UCB) may be limited for certain ethnic backgrounds. We therefore determined the impact of ethnicity upon donor availability in a pediatric cohort referred for allogeneic HSCT to a single Canadian transplant center. Among 252 eligible patients, 58 (23.0%) had suitable family donors. Of 161 patients with combined ULD and UCB searches, 78 (48.4%) had a suitable ULD, whereas 143 (88.8%) had suitable UCB. The probability of finding a suitable ULD differed significantly by ethnicity (P=0.007). Non-white patients were significantly less likely to have suitable ULDs (odds ratio [OR] 0.35; 95% confidence interval [CI], 0.17-0.69; P=0.003) compared with white patients but were equally likely to have suitable UCB (OR 1.02; 95% CI, 0.36-2.89; P=0.97). Although ethnic disparities exist in pediatric patients' access to ULD for HSCT, they are narrowed by the availability of international UCB registries. These findings, however, also highlight the importance of continued recruitment of individuals of non-white ethnicities to donor registries.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".