Antirelapse effect of pretransplant exposure to rabbit antithymocyte globulin
Bibliographic record
Abstract
It remains unknown why rabbit antithymocyte globulin (ATG; Thymoglobulin) has not affected relapse after hematopoietic cell transplantation (HCT) in randomized studies. We hypothesized that high pre-HCT ATG area under the curve (AUC) would be associated with a low incidence of relapse, whereas high post-HCT AUC would be associated with a high incidence of relapse. We measured serum levels of ATG capable of binding to mononuclear cells (MNCs), lymphocytes, T cells, CD4 T cells, or CD33 cells. We estimated pre- and post-HCT AUCs in 152 adult recipients of myeloablative conditioning and blood stem cells. High pre-HCT AUCs of MNC- and CD33 cell-binding ATG were associated with a low incidence of relapse and high relapse-free survival (RFS). There was a trend toward an association of high post-HCT AUC of lymphocyte-binding ATG with a high incidence of relapse and low RFS. High pre-HCT AUCs were also associated with faster engraftment and had no impact on graft-versus-host disease (GVHD) or fatal infections. High post-HCT AUCs were associated with a low risk of GVHD, seemed associated with an increased risk of fatal infections, and had no impact on engraftment. In conclusion, pre-HCT AUC seems to have a positive, whereas post-HCT AUC seems to have a negative, impact on relapse.
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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 | 0.002 |
| 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) | 0.001 | 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".