The Benefit of Allogeneic Hematopoietic Cell Transplantation in Older Patients with Acute Myeloid Leukemia Is Restricted to Those in First Complete Remission At the Time of Transplantation.
Bibliographic record
Abstract
Abstract Abstract 3097 Allogeneic hematopoietic cell transplantation (HCT) is a potentially curative treatment for some patients with acute myeloid leukemia (AML). Whether older patients with AML benefit from curative potential of HCT similar to younger patients is not well understood. To understand this issue, we evaluated the impact of age and remission status on 242 consecutive patients that underwent HCT between 1999 and 2011 in our program. Based on age and remission status, patients were divided into 4 groups: Gp 1, CR1 age <60 (n=116); Gp 2, CR1 age ≥60 (n=32); Gp 3, CR2 age <60 (n=78); and Gp 4, CR2 age ≥60 (n=16). Median age of all patients was 48 years (range 18–71), 123 patients (51%) were male. Peripheral blood stem cells were used in 178 patients (74%), bone marrow in 64 patients (26%). Donors were matched related (n=155, 64%) or matched unrelated (n=87, 36%). Median follow up of survivors was 65 months (range 12–145). No significant difference was found in terms of cytogenetic risk distribution between the 4 groups (p=0.14). Of the 48 patients ≥60 years of age, 46 (96%) received reduced-intensity conditioning regimens. Survival at 2-years in Gp 1, Gp 2, Gp 3, Gp 4 was 59%, 43%, 43% and 23%, respectively (Fig 1). Corresponding relapse free survival (RFS) was 59%, 34%, 40%, and 19%, respectively. Cumulative incidence (CI) of relapse in the four groups was 14%, 34%, 21% and 25% respectively. The corresponding CI of non-relapse mortality (NRM) was 27%, 31%, 38% and 56% respectively. In a univariate analysis, the hazard ratios for survival for Gp 2, Gp 3 and Gp 4 were 1.488, 1.533 and 2.718 in reference to Gp 1, respectively. Our data demonstrate that patients ≥60 years with AML in CR1 benefit from curative potential of HCT. Due to high NRM, patients ≥60 years in CR2 do not appear to benefit from curative potential of HCT. Therefore, if in an older patient HCT is indicated, attempts should be made to deliver the HCT in CR1. Disclosures: No relevant conflicts of interest to declare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.002 | 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".