A randomized phase 3 trial of interferon-α vs hydroxyurea in polycythemia vera and essential thrombocythemia
Bibliographic record
Abstract
The goal of therapy for patients with essential thrombocythemia (ET) and polycythemia vera (PV) is to reduce thrombotic events by normalizing blood counts. Hydroxyurea (HU) and interferon-α (IFN-α) are the most frequently used cytoreductive options for patients with ET and PV at high risk for vascular complications. Myeloproliferative Disorders Research Consortium 112 was an investigator-initiated, phase 3 trial comparing HU to pegylated IFN-α (PEG) in treatment-naïve, high-risk patients with ET/PV. The primary endpoint was complete response (CR) rate at 12 months. A total of 168 patients were treated for a median of 81.0 weeks. CR for HU was 37% and 35% for PEG (P = .80) at 12 months. At 24 to 36 months, CR was 20% to 17% for HU and 29% to 33% for PEG. PEG led to a greater reduction in JAK2V617F at 24 months, but histopathologic responses were more frequent with HU. Thrombotic events and disease progression were infrequent in both arms, whereas grade 3/4 adverse events were more frequent with PEG (46% vs 28%). At 12 months of treatment, there was no significant difference in CR rates between HU and PEG. This study indicates that PEG and HU are both effective treatments for PV and ET. With longer treatment, PEG was more effective in normalizing blood counts and reducing driver mutation burden, whereas HU produced more histopathologic responses. Despite these differences, both agents did not differ in limiting thrombotic events and disease progression in high-risk patients with ET/PV. This trial was registered at www.clinicaltrials.gov as #NCT01259856.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".