Molecular monitoring of therapeutic milestones and clinical outcomes in patients with chronic myeloid leukemia
Bibliographic record
Abstract
BACKGROUND: In the current study, the authors determined whether adhering to molecular monitoring guidelines in patients with chronic myeloid leukemia (CML) is associated with major molecular response (MMR) and assessed barriers to adherent monitoring. METHODS: Newly treated patients with CML from the Quebec province-wide CML registry from 2005 to 2016 were included. Timely polymerase chain reaction (tPCR) was defined as the molecular assessment of BCR-ABL1 at the 3-month, 12-month, and 18-month time points from the initiation of tyrosine kinase inhibitor (TKI) therapy. The cohort was analyzed as a nested case-control study. Cases with a first-ever MMR (BCR-ABL1 ≤0.1%, assessed at any time during follow-up) were matched to up to 5 controls by duration of TKI therapy, volume of patients with CML at the treatment center, year of cohort entry, and age. Odds ratios (ORs) for the performance of tPCR and MMR were adjusted for sex, comorbidities, type of TKI, and other important covariates. RESULTS: The cohort included 496 patients. Of 392 MMR events, 67.9% occurred before 18 months. The performance of tPCR was associated with a doubling of the MMR rate (OR, 2.23; 95% confidence interval [95% CI], 1.56-3.21) and was similar with 1 to 3 tPCRs performed (P = .67). Furthermore, tPCRs at 3 months (OR, 2.77; 95% CI, 1.81-4.23) and 12 months (OR, 3.00; 95% CI, 1.64-5.49) were associated with achieving early MMR, whereas tPCRs at 18 months were not (OR, 1.23; 95% CI, 0.80-1.89). Low-volume centers were found to have lower adherence to tPCR (OR, 0.60; 95% CI, 0.40-0.89). CONCLUSIONS: Timely molecular assessment at 3 months and 12 months appears to benefit patients with CML. Adherence to timely monitoring should be encouraged, especially in low-volume treatment centers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".