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Record W2803388295 · doi:10.1200/edbk_200841

Global Approaches in Myeloma: Critical Trials That May Change Practice

2018· review· en· W2803388295 on OpenAlexaff
Philippe Moreau, Cyrille Touzeau

Bibliographic record

VenueAmerican Society of Clinical Oncology Educational Book · 2018
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsClinical trialMultiple myelomaMedicineIntensive care medicineClinical PracticeTransplantationFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

The treatment of multiple myeloma (MM) has changed dramatically in the past decade with the introduction of new drugs into therapeutic strategies both in the frontline and relapse settings. With the availability of at least six different classes of agents that can be combined in doublet, triplet, or even quadruplet regimens and used together with high-dose therapy and autologous stem cell transplantation, the choice of the optimal strategy at diagnosis and at relapse represents a challenge for physicians. Also problematic is the lack of trials addressing questions, such as sequencing or the duration of maintenance. This review will focus on the results of recent clinical trials both in the frontline and relapse settings that have induced changes in clinical practice and will discuss the impact of important ongoing trials. A specific section will discuss therapeutic strategies when new drugs are not available.

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)0.007
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.674
GPT teacher head0.641
Teacher spread0.034 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2018
Admission routes1
Has abstractyes

Explore more

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