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Record W2928272073 · doi:10.1200/jco.18.02096

Treatment of Multiple Myeloma: ASCO and CCO Joint Clinical Practice Guideline

2019· article· en· W2928272073 on OpenAlexaffabout
Joseph Mıkhael, Nofisat Ismaila, Matthew C. Cheung, Caitlin Costello, Madhav V. Dhodapkar, Shaji Kumar, Martha Q. Lacy, Brea Lipe, Richard F. Little, Anna S. Nikonova, James Omel, Namrata Peswani, Anca Prica, Noopur Raje, Rahul Seth, David H. Vesole, Irwin Walker, Alexander C. Whitley, Tanya M. Wildes, Sandy W. Wong, Tom Martin

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsMcMaster UniversityPrincess Margaret Cancer CentreHealth Sciences CentreJuravinski Cancer CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineGuidelineMultiple myelomaRandomized controlled trialEvidence-based medicineSystematic reviewMEDLINEIntensive care medicineEvidence-based practiceFamily medicineQuality of life (healthcare)Clinical trialOncologyInternal medicineAlternative medicineNursingPathology

Abstract

fetched live from OpenAlex

PURPOSE: To provide evidence-based recommendations on the treatment of multiple myeloma to practicing physicians and others. METHODS: ASCO and Cancer Care Ontario convened an Expert Panel of medical oncology, surgery, radiation oncology, and advocacy experts to conduct a literature search, which included systematic reviews, meta-analyses, randomized controlled trials, and some phase II studies published from 2005 through 2018. Outcomes of interest included survival, progression-free survival, response rate, and quality of life. Expert Panel members used available evidence and informal consensus to develop evidence-based guideline recommendations. RESULTS: The literature search identified 124 relevant studies to inform the evidence base for this guideline. RECOMMENDATIONS: Evidence-based recommendations were developed for patients with multiple myeloma who are transplantation eligible and those who are ineligible and for patients with relapsed or refractory disease.

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)0.014
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0070.006
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0080.004
Research integrity0.0110.010
Insufficient payload (model declined to judge)0.0060.004

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 head0.541
Teacher spread0.332 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations333
Published2019
Admission routes2
Has abstractyes

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