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Record W3034037943 · doi:10.1111/bjh.16793

Early relapse after high‐dose melphalan autologous stem cell transplant predicts inferior survival and is associated with high disease burden and genetically high‐risk disease in multiple myeloma

2020· article· en· W3034037943 on OpenAlexfundno aff
Ceri Bygrave, Charlotte Pawlyn, Faith E. Davies, Zoe Craig, David A. Cairns, Anna Hockaday, Matthew Jenner, Gordon Cook, Mark T. Drayson, Roger G. Owen, Walter M. Gregory, Gareth J. Morgan, Graham Jackson, Martin Kaiser

Bibliographic record

VenueBritish Journal of Haematology · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
FundersMerck Sharp and DohmeMyeloma UKUniversity of LeedsNational Institute for Health and Care ResearchInstitute of Cancer ResearchCancer Research UKRoyal Marsden NHS Foundation TrustNational Cancer Research InstituteCelgeneUniversity of BirminghamCancer Research Institute
KeywordsMedicineMultiple myelomaMelphalanOncologyStem cellInternal medicineDiseaseTransplantationOverall survivalSurgeryBiology

Abstract

fetched live from OpenAlex

Predicting patient outcome in multiple myeloma remains challenging despite the availability of standard prognostic biomarkers. We investigated outcome for patients relapsing early from intensive therapy on NCRI Myeloma XI. Relapse within 12 months of autologous stem cell transplant was associated with markedly worse median progression-free survival 2 (PFS2) of 18 months and overall survival (OS) of 26 months, compared to median PFS2 of 85 months and OS of 91 months for later relapsing patients despite equal access to and use of subsequent therapies, highlighting the urgent need for improved outcome prediction and early intervention strategies for myeloma patients.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations51
Published2020
Admission routes1
Has abstractyes

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