Unrelated Donor Hematopoietic Cell Transplantation: Factors Associated with a Better HLA Match
Bibliographic record
Abstract
The impact of non-HLA patient factors on the match of the selected unrelated donor (URD) for hematopoietic cell transplantation (HCT) has not been fully evaluated. National Marrow Donor Program (NMDP) data for 7486 transplants using peripheral blood stem cells (PBSCs) or bone marrow from years 2000 to 2005 were evaluated using multivariate logistic regression to identify independent non-HLA patient factors associated with completing a more closely matched URD transplant. Advanced (intermediate- and late-stage) disease was significantly associated with an increased likelihood of transplant using a less-matched (partially matched or mismatched) donor. Additionally, Black patients were 2.83 times, Asian patients 2.05 times, and Hispanic patients 1.73 times more likely to have a less-matched HCT donor than Caucasian patients. Younger patients, HCT at lower volume centers, and in earlier years had significantly higher likelihood of having a less HLA matched URD transplant. Our analysis provides encouraging evidence of HLA matching improvement in recent years. Initiating a patient's URD search early in the disease process, especially for patients from non-Caucasian racial and ethnic groups, will provide the best likelihood for identifying the best available donor and making informed transplant decisions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".