Cytogenetics Abnormalities Predict the Outcome of Allogeneic Transplantation In AML: A CIBMTR Study
Bibliographic record
Abstract
Abstract Abstract 680 Cytogenetics play an essential role in determining the prognosis of patients with AML. However, there is still no validated cytogenetics grouping scheme that specifically applies to patients undergoing allogeneic stem cell transplantation, which hampers accurate prognostication and risk stratification. We studied 821 adult patients (median age 41, range 18–74) who underwent SCT between 1999 and 2004 for AML (excluding APL) in CR1 or CR2 and who were reported to the CIBMTR from centers with >20 patients meeting study criteria. 75% of patients received a myeloablative conditioning. 496 patients had a normal karyotype. The primary cytogenetics reports were manually reviewed for 92% of the patients with an abnormal karyotype. We compared the ability of the 6 existing grouping schemes (MRC, CALGB, EORTC/GIMEMA, SWOG/ECOG, DFCI, and Monosomal Karyotype (MK) classifications) to stratify patients, using both the Akaike Information Criterion in multivariable models and the C-statistic. Among all existing schemes, the DFCI system provided a marginally superior stratification for overall and leukemia-free survival. We also built a new classification using individual cytogenetic abnormalities in a Cox model that included other significant covariates (performance status, therapy-related disease, conditioning intensity, graft source, donor match, duration of CR1, and gender match). This CIBMTR scheme (see Table), which is similar to the DFCI scheme except for the inclusion of patients with t(8;21) in the intermediate group, could stratify patients into 3 groups with similar treatment-related mortality but significantly different overall survival, leukemia-free survival, and incidence of relapse. This scheme appeared to apply to both patients in CR1 and in CR2 (see FiguresF2). This transplant-specific scheme could be adopted for prognostication purposes and to stratify patients with karyotypic abnormalities entering transplantation clinical trials. Future studies may clarify the relative outcome of patients with t(8;21) and refine this scheme with the inclusion of molecular abnormalities. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".