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Record W2031978030 · doi:10.3747/co.v18i0.899

Patient Adherence to Aromatase Inhibitor Treatment in the Adjuvant Setting

2011· article· en· W2031978030 on OpenAlexafffundvenueabout
Sunil Verma, Yolanda Madarnas, Sandeep Sehdev, G. Martin, Jana Bajcar

Bibliographic record

VenueCurrent Oncology · 2011
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsWilliam Osler Health SystemKingston Health Sciences CentreCentre Hospitalier de l’Université de MontréalHealth Sciences CentreSunnybrook Health Science Centre
FundersSanofiAstraZeneca CanadaAstraZenecaPfizer
KeywordsMedicineAdjuvantBreast cancerAdjuvant therapyDiseaseHormonal therapyHormone therapyInternal medicineIntensive care medicineOncologyEstrogenCancerPhysical therapy

Abstract

fetched live from OpenAlex

Improvements in adjuvant systemic therapy and detection of early disease have resulted in a decline of breast cancer death rates across all patient age groups in Canada. Non-adherence to adjuvant hormonal therapy in the setting of early breast cancer may significantly affect patient outcome. Factors associated with medication adherence are complex and may be patient-related, therapy-related, and health care provider-related. To date, there is a gap in the literature concerning a comprehensive understanding of factors related to medication adherence with anti-estrogen therapy in the adjuvant setting. The literature suggests that strategies for improving adherence should focus on education of patients, assessment of the ability of patients to understand their disease and related recurrence factors, and facilitation of adherence by patients by providing adequate support and strategies for good self-management. However, more research is needed to better understand how health care providers can support women with breast cancer on oral therapy in the adjuvant setting.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.239
GPT teacher head0.427
Teacher spread0.188 · 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 teacher head, not a consensus.

Study designOther design
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

Citations28
Published2011
Admission routes4
Has abstractyes

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