Myelodysplastic Neoplasms (MDS) with Ring Sideroblasts or SF3B1 Mutations: The Improved Clinical Utility of World Health Organization and International Consensus Classification 2022 Definitions, a Single-Centre Retrospective Chart Review
Bibliographic record
Abstract
Myelodysplastic neoplasms (MDS) with ring sideroblasts (RS) are diagnosed via bone marrow aspiration in the presence of either (i) ≥15% RS or (ii) 5–14% RS and an SF3B1 mutation. In the MEDALIST trial and in an interim analysis of the COMMANDS trial, lower-risk MDS-RS patients had decreased transfusion dependency with luspatercept treatment. A total of 6817 patients with suspected hematologic malignancies underwent molecular testing using a next-generation-sequencing-based genetic assay and 395 MDS patients, seen at our centre from 1 January 2018 to 31 May 2023, were reviewed. Of these, we identified 39 evaluable patients as having lower-risk MDS with SF3B1 mutations: there were 20 (51.3%) males and 19 (48.7%) females, with a median age of 77 years (range of 57 to 92). Nineteen (48.7%) patients had an isolated SF3B1 mutation with a mean variant allele frequency of 35.2% +/− 8.1%, ranging from 7.4% to 46.0%. There were 29 (74.4%) patients with ≥15% RS, 6 (15.4%) with 5 to 14% RS, one (2.6%) with 1% RS, and 3 (7.7%) with no RS. Our study suggests that a quarter of patients would be missed based on the morphologic criterion of only using RS greater than 15% and supports the revised 2022 definitions of the World Health Organization (WHO) and International Consensus Classification (ICC), which shift toward molecularly defined subtypes of MDS and appropriate testing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".