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Record W4297464661 · doi:10.3390/curroncol29100560

A Canadian Perspective on the Treatment of Waldenström Macroglobulinemia

2022· article· en· W4297464661 on OpenAlexaffvenueabout
Rayan Kaedbey, Nicholas Forward, Laurie H. Sehn, Mona Shafey, Sarah Doucette, Christine I. Chen

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsFluidigm (Canada)Princess Margaret Cancer CentreFoothills Medical CentreImpactUniversity of CalgarySpinal Cord Injury BCNova Scotia Health AuthorityDalhousie UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineLymphoplasmacytic LymphomaRituximabBendamustineIbrutinibWaldenstrom macroglobulinemiaChemoimmunotherapyBortezomibBruton's tyrosine kinaseOncologyPurine analogueFludarabineInternal medicineImmunologyMultiple myelomaLymphomaChronic lymphocytic leukemiaTyrosine kinaseChemotherapyLeukemiaCyclophosphamide

Abstract

fetched live from OpenAlex

Waldenström macroglobulinemia (WM) is a slowly progressing B-cell non-Hodgkin lymphoma characterized by monoclonal IgM gammopathy in the blood and infiltration of the bone marrow by clonal lymphoplasmacytic cells. As an incurable disease, the goals for therapy for WM are to relieve symptoms, slow disease progression, prevent organ damage, and maintain quality of life. However, given the rarity of WM, clinical trials comparing treatments for WM are limited and there is no definitive standard of care. The selection of first-line WM therapy is thus based on patient factors, disease characteristics, and drug access, with bendamustine-rituximab and Bruton's tyrosine kinase (BTK) inhibitor therapy considered preferred treatments. Other treatments such as proteasome inhibitor- or purine analogue-based therapy, alternative chemoimmunotherapy, and autologous stem cell transplantation are generally reserved for the relapsed setting but may be used in rare circumstances in earlier lines of therapy. This paper summarizes the efficacy and safety of these WM therapies and discusses considerations for treatment from a Canadian perspective.

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)0.003
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.207
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0220.003

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 head0.102
GPT teacher head0.429
Teacher spread0.327 · 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
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

Citations2
Published2022
Admission routes3
Has abstractyes

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