Ponatinib dose-ranging study in chronic-phase chronic myeloid leukemia: a randomized, open-label phase 2 clinical trial
Bibliographic record
Abstract
In PACE (Ponatinib Ph+ ALL and CML Evaluation), a phase 2 trial of ponatinib that included patients with chronic-phase chronic myeloid leukemia (CP-CML) resistant to multiple prior tyrosine kinase inhibitors (TKIs), ponatinib showed deep and durable responses, but arterial occlusive events (AOEs) emerged as notable adverse events. Post hoc analyses indicated that AOEs are dose dependent. We assessed the benefit/risk ratio across 3 ponatinib starting doses in the first prospective study to evaluate a novel, response-based, dose-reduction strategy for TKI treatment. Adults with CP-CML resistant to or intolerant of at least 2 prior BCR-ABL1 TKIs or with a BCR-ABL1 T315I mutation were randomly assigned 1:1:1 to 3 cohorts receiving ponatinib 45, 30, or 15 mg once daily. In patients who received 45 or 30 mg daily the dose was reduced to 15 mg upon response (BCR-ABL1IS transcript levels ≤1%). The primary end point was response at 12 months. From August 2015 through May 2019, 283 patients were randomly assigned to the cohorts: 282 (94 per dose group) received treatment (data cutoff, 31 May 2020). The primary end point (98.3% confidence interval) was achieved in 44.1% (31.7-57.0) in the 45-mg cohort, 29.0% (18.4-41.6) in the 30-mg cohort, and 23.1% (13.4-35.3) in the 15-mg cohort. Independently confirmed grade 3 or above treatment-emergent AOEs occurred in 5, 5, and 3 patients in the 45-, 30-, and 15-mg cohorts, respectively. All cohorts showed benefit in this highly resistant CP-CML population. Optimal benefit/risk outcomes occurred with the 45-mg starting dose, which was decreased to 15 mg upon achievement of a response. This trial is registered on www.clinicaltrials.gov as NCT02467270.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".