Monosomal karyotype in acute myeloid leukemia predicts adverse treatment outcome and associates with high functional multidrug resistance activity
Bibliographic record
Abstract
Monosomal karyotype (MK) reflects highly unfavorable prognosis in patients with acute myeloid leukemia (AML). This study aimed to study the association of AML-MK with multidrug resistance (MDR) functional activity. A total of 369 AML patients (excluding APL) between 1995 and 2008 at a single center were included retrospectively. Functional MDR activity was evaluated with rhodamine-123 efflux activity with/without verapamil inhibition. MK was noted in 23 patients, only among whom classified into unfavorable cytogenetic risk group. Unfavorable cytogenetic subgroup with MK showed shorter OS (8.7 ± 5.9% vs. 23.5 ± 7.5% at 3 years, P = 0.030), EFS (8.7 ± 5.9% vs. 19.0 ± 6.9% at 3 years, P = 0.029), and a lower CR rate (34.8% vs. 65.7%, P = 0.031) compared with unfavorable subgroup without MK. Functional MDR activity was significantly higher in the unfavorable cytogenetic group with MK compared to all other cytogenetic risk groups taken as a whole (P = 0.026) and showed a trend toward statistical significance when compared with the unfavorable cytogenetic risk group without MK (P = 0.06). AML patients harboring MK showed a poor outcome in terms of lower CR rate and worse EFS/OS, and the presence of MK appeared to be associated with higher MDR functional activity of leukemic blasts.
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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 | 0.001 | 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".