Optimal Donor for African Americans with Hematologic Malignancy: HLA-Haploidentical Relative or Umbilical Cord Blood Transplant
Bibliographic record
Abstract
Although hematopoietic cell transplantation from an HLA-matched unrelated donor is potentially curative for hematologic malignancies, survival is lower for African Americans compared with Caucasians. Because only approximately 20% of African Americans will have an HLA-matched unrelated donor, many of these patients undergo HLA-haploidentical relative or umbilical cord blood transplantation. In this study, we analyzed outcomes after HLA-haploidentical related donor (n = 249) and umbilical cord blood (n = 118) transplantations in African American patients with hematologic malignancy between 2008 and 2016. The predominant disease was acute myelogenous leukemia for recipients of both types of donor grafts. The incidences of grade II-IV and III-IV acute graft-versus-host disease were higher after umbilical cord blood transplantation compared with HLA-haploidentical relative transplantation (56% and 29%, respectively, versus 33% and 11%, respectively; P < .0001). The 2-year incidence of transplantation-related mortality adjusted for age and conditioning regimen intensity was higher after umbilical cord blood transplantation compared with HLA-haploidentical related donor transplantation (31% versus 18%; P = .008); however, there were no between-group differences in the 2-year adjusted incidence of relapse (30% versus 34%; P = .51), overall survival (54% versus 57%; P = .66), or disease-free survival (43% versus 47%; P = .46). Our findings show that the use of HLA-haploidentical and umbilical cord blood transplants expands the access to transplantation with comparable leukemia-free and overall survival for African Americans with hematologic malignancies.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".