Deep molecular responses achieved in patients with CML-CP who are switched to nilotinib after long-term imatinib
Bibliographic record
Abstract
Patients in complete cytogenetic response (CCyR) with detectable BCR-ABL1 after ≥2 years on imatinib were randomized to nilotinib (400 mg twice daily, n = 104) or continued imatinib (n = 103) in the Evaluating Nilotinib Efficacy and Safety in clinical Trials-Complete Molecular Response (ENESTcmr) trial. By 1 and 2 years, confirmed undetectable BCR-ABL1 was achieved by 12.5% vs 5.8% (P = .108) and 22.1% vs 8.7% of patients in the nilotinib and imatinib arms, respectively (P = .0087). Among patients without molecular response 4.5 (BCR-ABL1(IS) ≤0.0032%; MR(4.5)) and those without major molecular response at study start, MR(4.5) by 2 years was achieved by 42.9% vs 20.8% and 29.2% vs 3.6% of patients in the nilotinib and imatinib arms, respectively. No patient in the nilotinib arm lost CCyR, vs 3 in the imatinib arm. Adverse events were more common in the nilotinib arm, as expected with the introduction of a new drug vs remaining on a well-tolerated drug. The safety profile of nilotinib was consistent with other reported studies. In summary, switching to nilotinib enabled more patients with chronic myeloid leukemia in chronic phase (CML-CP) to sustain lower levels of disease burden vs remaining on imatinib. This trial was registered at www.clinicaltrials.gov as #NCT00760877.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".