Treatment Outcomes in Chronic Myeloid Leukemia: Does One Size Fit All?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the success of tyrosine kinase inhibitors (TKIs) in achieving next-to-normal overall survival in chronic myeloid leukemia (CML), treatment-free remission (TFR) has become a significant goal in the management of this disease. Discontinuation of therapy is attractive to both patients and physicians because maintaining a stable BCR-ABL transcript level without therapy would imply true operational CML cure. With TFR, patients are not exposed to unknown long-term adverse effects of TKIs and common adverse effects that may affect quality of life. Several factors need to be considered before attempting TFR, because this goal is not appropriate for a significant proportion of patients with CML. Patient-related factors, CML response to therapy and its duration, monitoring capacity, patient preferences and compliance with monitoring, and economic factors influence the decision to attempt to discontinue TKIs. Unfortunately, only 50% of patients are appropriate candidates for discontinuation of treatment. Of those, another 50% maintain stable disease while off TKIs. This means that merely 25% of patients achieve TFR. Further optimization and research are required to be able to extend this treatment goal to a larger population of patients. Although TFR is attractive and desirable, this goal is not a one-size-fits-all approach, and we should continue to focus on patients with CML having a normal OS with the best quality of life possible.
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.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.001 |
| 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 it