Gender and <i><scp>BCR</scp>‐<scp>ABL</scp></i> transcript type are correlated with molecular response to imatinib treatment in patients with chronic myeloid leukemia
Bibliographic record
Abstract
OBJECTIVES: Achieving a major molecular response (MMR) is the goal of imatinib therapy for chronic myeloid leukemia. However, the association between gender, BCR-ABL transcript type, and age with MMR is not well understood and often controversial. METHODS: We retrospectively analyzed 166 patients who have been treated with imatinib for up to 10 yr. RESULTS: Men had a lower MMR rate than women (63.3% vs. 81.6%, P = 0.006) and a shorter time to relapse (median 354 vs. 675 d, P = 0.049), while patients with b3a2 or with both b3a2 and b2a2 break point transcripts had higher MMR rate than those with b2a2 (81.8%, 77.1% vs. 60.7%, P = 0.023 for b3a2 vs. b2a2, P = 0.043 for both vs. b2a2). A striking difference was found between men with b2a2 and women with both b2a2 and b3a2 in terms of MMR rate (43.8% vs. 88.9%), MMR rate within 6 months (7.1% vs. 62.5%) and the time to MMR (median d 493 vs. 159, P = 0.036). CONCLUSIONS: Both gender and BCR-ABL transcript, but not age, were significantly associated with the molecular response. Men with b2a2 represent a less favorable group in their response to imatinib treatment and may need alternative therapy regimen and closer monitoring.
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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 | 0.000 | 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".