Activity of the Janus kinase inhibitor ruxolitinib in chronic lymphocytic leukemia: results of a phase II trial
Bibliographic record
Abstract
B cell receptor (BCR)-signaling inhibitors such as Ibrutinib and Idelalisib do not cure CLL, suggesting the importance of other pathways.1 Cytokines are also important in CLL biology and mediate transcription of oncogenic genes such as miR-17 by activating signal transducer and activator of transcription (STAT) proteins including STAT5A/B and STAT3 through Janus kinases (JAKs).2–4 We hypothesized that Ruxolitinib, a selective JAK1/2 inhibitor licensed for myelofibrosis,5 might have unrecognized activity in CLL and designed a single center phase II trial to evaluate it in patients considered unfit for FCR on the basis of age and comorbidities.6 The demonstrated safety of Ruxolitinib in myelofibrosis was felt to make it ethical to use as first-line therapy for elderly CLL patients. The primary endpoint was overall response rate (ORR) assessed after 7 treatment cycles.7 Secondary endpoints were safety and tolerability.7 The study was approved by the Sunnybrook REB and Health Canada and registered with ClinicalTrials.gov, {type:clinical-trial,attrs:{text:NCT02015208,term_id:NCT02015208}}NCT02015208.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".