Evolution of bosutinib (BOS) toxicity in patients (pts) with Ph+ leukemia after resistance/intolerance to prior therapy.
Bibliographic record
Abstract
7099 Background: BOS is an oral dual Src/Abl tyrosine kinase inhibitor (TKI) approved for treatment of Ph+ CML following resistance/intolerance to prior therapy. Prior reports from this phase I/II trial indicated the BOS safety profile was primarily characterized by myelosuppression, gastrointestinal events, and rash. The current analysis compares the incidence of toxicity in Year 1 (Y1) for pts on treatment ≤1 y and within Y1 and Year 2 (Y2) for pts on treatment for >1 y. Methods: BOS 500 mg/d was evaluated in 3 cohorts: chronic phase (CP) CML after imatinib only (CP 2L cohort; n = 286); CP CML after imatinib + dasatinib and/or nilotinib (CP 3L cohort; n = 119); and accelerated/blast phase CML or ALL after prior TKI therapy (ADV cohort; n = 164). Results: The most common treatment-emergent adverse events (TEAEs) in each cohort occurred more frequently within Y1 than Y2 (Table). The incidence for grade 3/4 events followed a similar pattern. AEs were the most common reason for BOS discontinuation in Y1 (CP 2L, 53%; CP 3L, 32%; ADV, 41%). Of the pts whose primary reason for discontinuing BOS was an AE during the first 2 y, most did so during Y1 (CP 2L, n = 51/60 [85%]; CP 3L, n = 22/24 [92%]; ADV, n = 24/25 [96%]); the most common reasons during Y1 were thrombocytopenia (12%; 9%; 4%), increased ALT (6%; 4%; 2%), neutropenia (3%; 6%; 0%), diarrhea (4%; 3%; 0%), and vomiting (3%; 4%; 1%). Serious AEs were more common among pts who discontinued BOS ≤1 y versus on treatment >1 y in the CP 3L and ADV cohorts, but similar in the CP 2L cohort (Table). Conclusions: Discontinuation due to AEs was observed primarily in Y1. For pts on BOS for >1 y, the incidence of common TEAEs decreased substantially after Y1, suggesting BOS tolerability improves after long-term exposure. Clinical trial information: NCT00261846. [Table: see text]
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".