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Record W4212864787 · doi:10.3747/co.2007.149

Canadian Supportive Care Recommendations for the Management of Anemia in Patients with Cancer

2007· article· en· W4212864787 on OpenAlexafffundvenueabout
Joseph Mıkhael, Barbara Melosky, C. Cripps, Daniel Rayson, C. Tom Kouroukis

Bibliographic record

VenueCurrent Oncology · 2007
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsJuravinski Cancer CentrePrincess Margaret Cancer CentreBC Cancer AgencyOttawa HospitalQueen Elizabeth II Health Sciences CentreOttawa Regional Cancer Foundation
FundersAmgen CanadaMcGill University Health CentreMcGill UniversityAmgen
KeywordsMedicineAnemiaIntensive care medicineCancerDosingErythropoiesisIntravenous ironChemotherapyIron deficiencyInternal medicine

Abstract

fetched live from OpenAlex

Anemia is a common finding in cancer patients, most often as a result of chemotherapy. Management of anemia requires a comprehensive approach of appropriate diagnosis, exclusion of reversible causes, use of erythropoiesis-stimulating agents (ESAS), and iron supplementation. Recently, consensus guidelines on the management of chemotherapy-induced anemia were published in Europe and the United States. The present review is intended to be a practical guide for Canadian physicians, based on published guidelines, but specifically tailored to the Canadian environment. Recommendations for the use of ESAS are presented, including initiation, target hemoglobin, dosing and adjustments, monitoring, and re-initiation. Issues of safety are also addressed, including thromboembolic risk, impact on survival, and tumour progression. The importance of iron metabolism and the use of iron supplementation (both oral and parenteral) is discussed.

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)0.002
metaresearch head score (Gemma)0.008
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: Review · Consensus signal: none
Teacher disagreement score0.523
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.003

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 head0.057
GPT teacher head0.404
Teacher spread0.347 · 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

Citations15
Published2007
Admission routes4
Has abstractyes

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