MétaCan
Menu
Back to cohort
Record W2145345262 · doi:10.1586/erp.11.80

Adherence to long-term adjuvant hormonal therapy for breast cancer

2011· review· en· W2145345262 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueExpert Review of Pharmacoeconomics & Outcomes Research · 2011
Typereview
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTamoxifenMedicineBreast cancerAromataseAdjuvantOncologyHormonal therapyInternal medicineGynecologyIntensive care medicineCancer

Abstract

fetched live from OpenAlex

Tamoxifen is an essential drug in treating hormone receptor-positive breast cancer and has been used successfully for the past three decades. More recently, aromatase inhibitors (AIs) have also shown great promise in reducing breast cancer recurrence. To receive the optimal benefits, patients need to take these drugs for a period of 5 years. Yet, despite the known positive patient outcomes associated with their use, adherence to both tamoxifen and AIs is substantially less than ideal. This article reviews the most recent literature reporting adherence rates for tamoxifen and AIs, as well as correlates of adherence. Factors that help to explain nonadherence are reviewed, including the side-effect profile, and approaches to intervention to enhance adherence are 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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0200.002

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 head0.242
GPT teacher head0.616
Teacher spread0.374 · 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