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Record W4393951096 · doi:10.3390/curroncol31040134

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

2024· article· en· W4393951096 on OpenAlexaffvenue
S. Mortuza, Benjamin Chin‐Yee, Tyler E. James, Ian Chin‐Yee, Benjamin D. Hedley, Jenny Ho, Lalit Saini, Alejandro Lazo‐Langner, Laila C. Schenkel, Pratibha Bhai, Bekim Sadiković, Jonathan Keow, Nikhil Sangle, Cyrus C. Hsia

Bibliographic record

VenueCurrent Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsAlberta Hospital EdmontonUniversity of OttawaLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineMyelodysplastic syndromesInternational Prognostic Scoring SystemInternal medicineLenalidomideOncologyBone marrowPediatrics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.209
GPT teacher head0.442
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes2
Has abstractyes

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