Molecular predictors of response to decitabine in advanced chronic myelomonocytic leukemia: a phase 2 trial
Bibliographic record
Abstract
Hydroxyurea is the standard therapy of chronic myelomonocytic leukemia (CMML) presenting with advanced myeloproliferative and/or myelodysplastic features. Response to hypomethylating agents has been reported in heterogeneous series of CMML. We conducted a phase 2 trial of decitabine (DAC) in 39 patients with advanced CMML defined according to a previous trial. Median number of DAC cycles was 10 (range, 1-24). Overall response rate was 38% with 4 complete responses (10%), 8 marrow responses (21%), and 3 stable diseases with hematologic improvement (8%). Eighteen patients (46%) demonstrated stable disease without hematologic improvement, and 6 (15%) progressed to acute leukemia. With a median follow-up of 23 months, overall survival was 48% at 2 years. Mutations in ASXL1, TET2, AML1, NRAS, KRAS, CBL, FLT3, and janus kinase 2 (JAK2) genes, and hypermethylation of the promoter of the tumor suppressor gene TIF1γ, did not predict response or survival on DAC therapy. Lower CJUN and CMYB gene expression levels independently predicted improved overall survival. This trial confirmed DAC efficacy in approximately 40% of CMML patients with advanced myeloproliferative or myelodysplastic features and suggested that CJUN and CMYB expression could be potential biomarkers in this setting. This trial is registered at EudraCT (eudract.ema.europa.eu) as #2008-000470-21 and www.clinicaltrials.gov as #NCT01098084.
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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 | 0.001 |
| Open science | 0.001 | 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".