Race and Ethnicity Influences Collection of Granulocyte Colony–Stimulating Factor–Mobilized Peripheral Blood Progenitor Cells from Unrelated Donors, a Center for International Blood and Marrow Transplant Research Analysis
Bibliographic record
Abstract
Little information exists on the effect of race and ethnicity on collection of peripheral blood stem cells (PBSC) for allogeneic transplantation. We studied 10,776 donors from the National Marrow Donor Program who underwent PBSC collection from 2006 to 2012. Self-reported donor race/ethnic information included Caucasian, Hispanic, Black/African American (AA), Asian/Pacific Islander (API), and Native American (NA). All donors were mobilized with subcutaneous filgrastim at an approximate dose of 10 μg/kg/day for 5 days. Overall, AA donors had the highest median yields of mononuclear cells per liter and CD34(+) cells per liter of blood processed (3.1 × 10(9) and 44 × 10(6), respectively), whereas Caucasians had the lowest median yields at 2.8 × 10(9) and 33.7 × 10(6), respectively. Multivariate analysis of CD34(+) per liter mobilization yields using Caucasians as the comparator and controlling for age, gender, body mass index, and year of apheresis revealed increased yields in overweight and obese AA and API donors. In Hispanic donors, only male obese donors had higher CD34(+) per liter mobilization yields compared with Caucasian donors. No differences in CD34(+) per liter yields were seen between Caucasian and NA donors. Characterization of these differences may allow optimization of mobilization regimens to allow enhancement of mobilization yields without compromising donor safety.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".