When to Stop Tyrosine Kinase Inhibitors for the Treatment of Chronic Myeloid Leukemia
Bibliographic record
Abstract
OPINION STATEMENT: Strict criteria for when to stop tyrosine kinase inhibitor (TKI) therapy in clinical practice are not easily defined without an agreement on what probability of achieving a treatment-free remission (TFR) constitutes a medically acceptable standard and consideration of the potential medical risks of continued TKI therapy and/or patient preferences. Patients in sustained deep molecular response (DMR) have no significant chronic myelogenous leukemia-related risk of progression and death, and thus, safety is of paramount importance. Patients with prior history of advanced disease, additional chromosomal abnormalities (ACA), atypical transcripts, TKI resistance, high Sokal score, or who cannot be relied upon to come for regular molecular monitoring should generally be excluded from TKI cessation in clinical practice. Similarly, stopping TKIs should not be attempted without the availability of standardized BCR-ABL1 testing with a sensitivity of at least MR4.5 and a turnaround time of less than 4 weeks. Prior TKI therapy of 5 years and stable MR4.0 of 2 years or more constitutes reasonable minimal criteria for stopping TKIs with approximately a 50% chance of success. The risk of morbidity with continued TKI therapy and patient preferences need to be considered to determine to what extent these minimal criteria should be exceeded and at what threshold to re-initiate therapy whether on the loss of major molecular response or at a lower molecular endpoint.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".