EPIC: A phase III randomized, open-label study of ponatinib versus imatinib in adult patients with newly diagnosed chronic myeloid leukemia in chronic phase.
Bibliographic record
Abstract
TPS7129 Background: The hallmark genetic abnormality of chronic myeloid leukemia (CML), known as the Philadelphia chromosome, generates the BCR-ABL fusion gene; expression of BCR-ABL in hematopoietic stem cells gives rise to CML. Ponatinib is a potent oral pan–BCR-ABL tyrosine kinase inhibitor (TKI) that is active against native and mutated forms of BCR-ABL, including the T315I gatekeeper mutant. Results from the phase 1 and phase 2 studies of ponatinib demonstrated that ponatinib is generally well tolerated and has substantial anti-leukemic activity in patients with CML who are resistant or intolerant to prior TKI therapy, regardless of baseline mutation status. In addition, multivariate analyses suggest that ponatinib has greater activity in younger patients who are less heavily pretreated and have a shorter time since diagnosis. The phase 3 EPIC (Evaluation of Ponatinib vs Imatinib in CML) study is testing the hypothesis that ponatinib is an effective treatment for newly diagnosed chronic phase (CP) CML patients when compared with standard imatinib therapy. Methods: EPIC is a multicenter, international, phase 3, two-arm, open-label trial of ponatinib (45 mg once daily) versus imatinib (400 mg once daily) in patients with newly diagnosed CP-CML. Patients ≥18 years of age with CP-CML (diagnosed within 6 months prior to study entry) and adequate renal, hepatic, and pancreatic function are eligible for enrollment. Enrolled patients are assigned to receive ponatinib or imatinib in a 1:1 fashion, stratified by Sokal Risk score (low vs intermediate vs high). The primary efficacy endpoint for this trial is major molecular response (MMR) rate at 12 months. Secondary endpoints include MMR rate at 5 years, BCR-ABLIS<10% rate at 3 months, CCyR rate at 12 months, progression-free survival, overall survival, and safety. A sample size consisting of 480 patients will provide 90% power to detect a 15% absolute increase in MMR rate at 12 months using an unstratified Fisher exact 2-sided test at an alpha level of 0.05. Assuming a 10% dropout rate, approximately 528 patients will be enrolled. The first patient was enrolled in August 2012. Clinical trial information: NCT01650805.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".