Racial, ethnic, and socioeconomic diversity and outcomes of patients with graft-versus-host disease: a CIBMTR analysis
Bibliographic record
Abstract
ABSTRACT: Socioeconomic status (SES) and race/ethnicity have been associated with the outcomes of allogeneic hematopoietic stem cell transplantation (allo-HCT). Certain aspects of graft-versus-host disease (GVHD) management, such as the need for long-term care, prolonged immunosuppressive treatment, and close follow-up for complications, may exacerbate disparities. Adults (≥18 years) reported to the Center for International Blood and Marrow Transplant Research who underwent a first allo-HCT for acute leukemia, myelodysplastic syndrome, or myeloproliferative neoplasm between 2008 and 2018 were included. End points for those developing GVHD included overall survival (OS), transplant-related mortality (TRM), and disease relapse. Models were adjusted for patient- and transplant-related variables. A 2-sided P value < .01 was considered significant. Among the 14 825 allo-HCT recipients, 6259 (42.2%) and 6675 (45.0%) patients developed acute GVHD (aGVHD) and chronic GVHD (cGVHD), respectively. Among patients with aGVHD, non-Hispanic Black patients had increased TRM and overall mortality compared with non-Hispanic White patients; this association disappeared when severity of aGVHD was included in the model. Lower SES was associated with increased risk of disease relapse but not OS or TRM. In patients who developed cGVHD, race and ethnicity were not associated with OS, TRM, or disease relapse. However, the highest quartile of annual household income (≥$80 000) had improved OS and reduced TRM compared with the lowest quartile, after adjusting for race and ethnicity. In summary, race/ethnicity and SES are associated with outcomes after GVHD. Optimizing the health care resources available to low SES patients and strategies to minimize the risk of severe GVHD in non-Hispanic Black patients may improve long-term outcomes.
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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) | 0.000 | 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) | 0.000 | 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".