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Record W2100395884 · doi:10.1586/era.10.160

Use of aromatase inhibitors and bisphosphonates as an anticancer therapy in postmenopausal breast cancer

2010· review· en· W2100395884 on OpenAlexaff
Henning T. Mouridsen, Per Eystein Lønning, Matthias W. Beckmann, Kimberly Blackwell, Julie Doughty, Joseph Gligorov, Antonio Llombart‐Cussac, André Robidoux, Beat Thürlimann, Michael Gnant

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineAromataseBreast cancerOncologyAdjuvantCancerInternal medicineAdjuvant therapyAromatase inhibitorGynecology

Abstract

fetched live from OpenAlex

Breast cancer is a major cause of morbidity and mortality in postmenopausal women worldwide. Reducing the risk of distant disease recurrence is a primary goal of adjuvant endocrine therapy. As we await data from ongoing Phase III comparison trials, an emerging body of evidence demonstrates important differences between third-generation aromatase inhibitors, particularly with respect to potency and prevention of early distant metastases. Furthermore, a growing body of evidence demonstrates anticancer benefits of bisphosphonates in adjuvant breast cancer and other settings. This article outlines the proceedings from an Expert Panel meeting of regionally diverse breast cancer specialists regarding the appropriate use of aromatase inhibitors in postmenopausal hormone-responsive early breast cancer and bisphosphonates as anticancer therapy in adjuvant breast cancer.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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)0.0020.002

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 head0.020
GPT teacher head0.356
Teacher spread0.335 · 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

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

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