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Record W4284887577 · doi:10.1182/blood.2022016171

Longer-term benefit of luspatercept in transfusion-dependent lower-risk myelodysplastic syndromes with ring sideroblasts

2022· article· en· W4284887577 on OpenAlexaff
Amer M. Zeidan, Uwe Platzbecker, Guillermo Garcia‐Manero, Mikkael A. Sekeres, Pierre Fenaux, Amy E. DeZern, Peter L. Greenberg, Michael R. Savona, Joseph G. Jurcic, Amit Verma, Ghulam J. Mufti, Rena Buckstein, Valeria Santini, Jeevan K. Shetty, Rodrigo Ito, Jennie Zhang, George Zhang, Xianwei Ha, Jay T. Backstrom, Rami S. Komrokji

Bibliographic record

VenueBlood · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Cancer InstituteBlood Cancer UK
KeywordsMedicineMyelodysplastic syndromesPlaceboBlood transfusionAnemiaInternal medicineSurgeryBone marrow

Abstract

fetched live from OpenAlex

Luspatercept is an approved therapy for selected patients with lower risk myelodysplasia requiring transfusion despite erythropoiesis-stimulating agents, based on the early results of a randomized trial against placebo. Zeidan and colleagues report that after a median of 26 months follow-up, 27% of patients commencing luspatercept were continuing therapy. Their updated analyses confirm that a significant minority (45%) of eligible patients can achieve transfusion independence, with a median durability of 30 weeks. These longer follow-up data better quantify the incremental benefit of luspatercept over placebo.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.011
GPT teacher head0.241
Teacher spread0.230 · 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 teacher head, not a consensus.

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

Citations25
Published2022
Admission routes1
Has abstractyes

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