Bibliographic record
Abstract
), is being developed by Astex Pharmaceuticals (a subsidiary of Otsuka Pharmaceuticals) for the treatment of various cancers like myelodysplastic syndromes (MDS), chronic myelomonocytic leukaemia (CMML), acute myeloid leukaemia (AML), glioma and solid tumours. Decitabine, a DNA methyltransferase inhibitor approved for the treatment of MDS and CMML, is degraded by cytidine deaminase in the gastrointestinal tract and liver, thereby limiting oral bioavailability. Cedazuridine is a proprietary, patented cytidine deaminase inhibitor that, when added to decitabine, increases oral bioavailability of the drug. In July 2020, decitabine/cedazuridine received its first approval in the USA and Canada for the treatment of MDS and CMML. In the USA, it is indicated for use in adults with MDS and CMML, including previously treated and untreated, de novo and secondary MDS with the following French-American-British subtypes (refractory anaemia, refractory anaemia with ringed sideroblasts, refractory anaemia with excess blasts and CMML) and intermediate-1, intermediate-2 and high-risk International Prognostic Scoring System groups. Clinical studies for AML, glioma and solid tumours are underway in several countries worldwide. This article summarizes the milestones in the development of decitabine/cedazuridine leading to this first approval for the treatment of MDS and CMML.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
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".