Assessment of Impact of HLA Type on Outcomes of Allogeneic Hematopoietic Stem Cell Transplantation for Chronic Lymphocytic Leukemia
Bibliographic record
Abstract
Chronic lymphocytic leukemia (CLL) is a common hematologic malignancy with many highly effective therapies. Chemorefractory disease, often characterized by deletion of chromosome 17p, has historically been associated with very poor outcomes, leading to the application of allogeneic hematopoietic stem cell transplantation (allo-HCT) for medically fit patients. Although the use of allo-HCT has declined since the introduction of novel targeted therapy for the treatment of CLL, there remains significant interest in understanding factors that may influence the efficacy of allo-HCT, the only known curative treatment for CLL. The potential benefit of transplantation is most likely due to the presence of alloreactive donor T cells that mediate the graft-versus-leukemia (GVL) effect. The recognition of potentially tumor-specific antigens in the context of class I and II major histocompatibility complex on malignant B lymphocytes by donor T cells may be influenced by subtle differences in the highly polymorphic HLA locus. Given previous reports of specific HLA alleles impacting the incidence of CLL and the clinical outcomes of allo-HCT for CLL, we sought to study the overall survival and progression-free survival of a large cohort of patients with CLL who underwent allo-HCT from fully HLA-matched related and unrelated donors at Center for International Blood and Marrow Transplant Research transplantation centers. We found no statistically significant association of allo-HCT outcomes in CLL based on previously reported HLA combinations. Additional study is needed to further define the immunologic features that portend a more favorable GVL effect after allo-HCT for CLL.
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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 | 0.001 | 0.003 |
| 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) | 0.001 | 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".