Azacitidine in the ‘real‐world’: an evaluation of 1101 higher‐risk myelodysplastic syndrome/low blast count acute myeloid leukaemia patients in Ontario, Canada
Bibliographic record
Abstract
The outcome of myelodysplastic syndrome (MDS) patients with uniformly higher-risk disease treated with azacitidine (AZA) in the 'real-world' remains largely unknown. We evaluated 1101 consecutive higher-risk MDS patients (International Prognostic Scoring System intermediate-2/high) and low-blast count acute myeloid leukaemia (AML; 21-30% blasts) patients treated in Ontario, Canada. By dosing schedule, 24·7% received AZA for seven consecutive days, 12·4% for six consecutive days and 62·9% by 5-2-2. Overall, median number of cycles was 6 (range 1-67) and 8 (range 6-14) when restricted to the 692 (63%) patients who received at least 4 cycles. The actuarial median survival was 11·6 months [95% confidence interval (CI) 10·7-12·4) for the entire cohort and 18·0 months (landmark analysis; 95% CI 16·6-19·1 months) for those receiving at least 4 cycles. There was no difference in overall survival (OS) between the 3 dosing schedules (P = 0·87). In our large 'real-world' evaluation of AZA in higher-risk MDS/low-blast count AML, we demonstrated a lower than expected OS. Reassuringly, survival did not differ by dosing schedules. The OS was higher in the 2/3 of patients who received at least 4 cycles of treatment, reinforcing the necessity of sustained administration until therapeutic benefits are realised. This represents the largest 'real-world' evaluation of AZA in higher-risk MDS/low-blast count AML.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".