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Record W2216707999 · doi:10.3109/10428194.2014.974043

The risk of secondary primary malignancies after therapy for multiple myeloma

2015· review· en· W2216707999 on OpenAlexaff
Nuchanan Areethamsirikul, Donna Reece

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2015
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsLenalidomideMultiple myelomaMedicineContext (archaeology)MalignancyIncidence (geometry)DiseaseOncologyMaintenance therapyInternal medicineHematologic malignancyCancerIntensive care medicineChemotherapy

Abstract

fetched live from OpenAlex

The development of a secondary primary malignancy (SPM) has become an important issue in myeloma management, given the remarkable improvement in survival afforded by the introduction of novel agents. Treatment with immunomodulatory derivatives, specifically lenalidomide, has recently been identified as a potential risk factor for SPM in several studies, especially in the maintenance setting. This study reviews potential mechanisms for development of SPM, incidence of SPM with different treatment regimens, risk factors associated with SPM and features of SPM after myeloma therapy. The incidence of SPM is discussed in the context of different settings in which lenalidomide is used during the course of the disease. No clear evidence indicates that lenalidomide alone is associated with SPM in the absence of other risk factors. Routine cancer surveillance, lifestyle modification to avoid cancer risk factors and prompt evaluation if new symptoms occur should be emphasized to patients who are on continuous myeloma therapy.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.301
Teacher spread0.272 · 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
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

Citations16
Published2015
Admission routes1
Has abstractyes

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