Treatment‐free remission after dasatinib in patients with chronic myeloid leukaemia in chronic phase with deep molecular response: Final 5‐year analysis of <scp>DASFREE</scp>
Bibliographic record
Abstract
Patients with chronic myeloid leukaemia in chronic phase (CML-CP) who have a sustained deep molecular response (DMR) are eligible to discontinue treatment and attempt treatment-free remission (TFR). In the DASFREE study (ClinicalTrials.gov; NCT01850004), the 2-year TFR rate after dasatinib discontinuation was 46%; here we present the 5-year update. Patients with a stable DMR after ≥2 years of dasatinib therapy discontinued treatment and were followed for 5 years. At a minimum follow-up of 60 months, in 84 patients discontinuing dasatinib, the 5-year TFR rate was 44% (n = 37). No relapses occurred after month 39 and all evaluable patients who relapsed and restarted dasatinib (n = 46) regained a major molecular response in a median of 1.9 months. The most common adverse event during the off-treatment period was arthralgia (18%, 15/84); a total of 15 withdrawal events were reported in nine patients (11%). At the 5-year final follow-up, almost half of the patients who discontinued dasatinib after a sustained DMR maintained TFR. All evaluable patients who experienced a relapse quickly regained a DMR after restarting dasatinib, demonstrating that dasatinib discontinuation is a viable and potentially long-term option in patients with CML-CP. The safety profile is consistent with the previous report.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".