Overall survival in lower <scp>IPSS</scp> risk <scp>MDS</scp> by receipt of iron chelation therapy, adjusting for patient‐related factors and measuring from time of first red blood cell transfusion dependence: an <scp>MDS</scp>‐<scp>CAN</scp> analysis
Bibliographic record
Abstract
Analyses suggest iron overload in red blood cell (RBC) transfusion-dependent (TD) patients with myleodysplastic syndrome (MDS) portends inferior overall survival (OS) that is attenuated by iron chelation therapy (ICT) but may be biassed by unbalanced patient-related factors. The Canadian MDS Registry prospectively measures frailty, comorbidity and disability. We analysed OS by receipt of ICT, adjusting for these patient-related factors. TD International Prognostic Scoring System (IPSS) low and intermediate-1 risk MDS, at RBC TD, were included. Predictive factors for OS were determined. A matched pair analysis considering age, revised IPSS, TD severity, time from MDS diagnosis to TD, and receipt of disease-modifying agents was conducted. Of 239 patients, 83 received ICT; frailty, comorbidity and disability did not differ from non-ICT patients. Median OS from TD was superior in ICT patients (5·2 vs. 2·1 years; P < 0·0001). By multivariate analysis, not receiving ICT independently predicted inferior OS, (hazard ratio for death 2·0, P = 0·03). In matched pair analysis, OS remained superior for ICT patients (P = 0·02). In this prospective, non-randomized analysis, receiving ICT was associated with superior OS in lower IPSS risk MDS, adjusting for age, frailty, comorbidity, disability, revised IPSS, TD severity, time to TD and receiving disease-modifying agents. This provides additional evidence that ICT may confer clinical benefit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".