Total Body Irradiation without Chemotherapy as Conditioning for an Allogeneic Hematopoietic Cell Transplantation for Adult Acute Myeloid Leukemia
Bibliographic record
Abstract
Current therapies for acute myeloid leukemia (AML), failing induction, are rarely effective. We report our experience in 4 patients with AML who received 16 Gy TBI prior to allogeneic hematopoietic cell transplantation (alloHCT), between June 2010 and May 2011. Patients were 20 to 55 years of age, 2 with relapsed disease and 2 with AML failing induction. An HLA-matched graft from related or unrelated donor was infused on day 0. All but one, who received a CD34+-selected graft, received methotrexate and tacrolimus +/− antithymocyte globulin, as GVHD prophylaxis. The other patient received tacrolimus alone. Neutrophil and platelet engraftment occurred at a median of 18 and 14 days, respectively. Patients were discharged at a median of 28 days. There were no unexpected toxicities in the first 30 days. One patient had cytomegalovirus (CMV) viremia and anorexia, at two months. One patient had grade 2 acute GVHD of the skin. One patient developed chronic GVHD of the eyes, mouth, skin, joints, and lung at 4 months. Two patients died from relapse of their leukemia at days 65 and 125. Two patients remain in remission beyond day 1500. 16 Gy TBI followed by an alloHCT for AML, failing induction, is feasible and tolerable.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".