Final report of <scp>TKI</scp> discontinuation trial with dasatinib for the second attempt of treatment‐free remission after failing the first attempt with imatinib: Treatment‐free Remission Accomplished by Dasatinib (<scp>TRAD</scp>) study
Bibliographic record
Abstract
Multiple studies have reported a significant treatment-free remission (TFR) rate of 50%-60% in patients with chronic myeloid leukaemia (CML) who discontinue tyrosine kinase inhibitor (TKI) therapy. However, the remaining half of these patients still require re-initiation of TKI therapy for leukaemia control. It remains unclear if TKI drugs should be switched for re-therapy in patients who failed the first TFR (TFR1) attempt. Our study attempted to determine whether dasatinib therapy after TFR1 failure post-imatinib discontinuation could improve the likelihood of TFR2. Of 59 patients who lost molecular response after imatinib discontinuation for TFR1, 55 patients (93.2%) were treated with dasatinib, of whom 49 (89.1%) regained MR4.5 or deeper response, with a median time of 1.85 months to achieve MR4.5. Dasatinib was discontinued in 35 patients for TFR2 attempt, of whom 26 patients (74.28%) lost MMR and 6 (17.14%) MR4. Risk factor analysis for the TFR2 after dasatinib discontinuation suggested three significant factors: (1) doubling time of BCR::ABL1 transcript following TFR1 attempt, (2) rapid regaining of molecular response following dasatinib therapy and (3) undetectable BCR::ABL1 transcript prior to TFR2 attempt. The present study showed that dasatinib does not increase the TFR2 rate in general, but a selected group of patients could benefit from this approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".