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Record W1973125664 · doi:10.1158/0008-5472.sabcs-09-36

Adherence of Adjuvant Hormonal Therapies in Post-Menopausal Hormone Receptor Positive (HR+) Early Stage Breast Cancer: A Population Based Study from British Columbia.

2009· article· en· W1973125664 on OpenAlexaffabout
Arlene Chan, Caroline Speers, Séamus O’Reilly, Ruth Pickering, Stephen Chia

Bibliographic record

VenueCancer Research · 2009
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineBreast cancerTamoxifenOncologyInternal medicineHormonal therapyCancerPopulationAromataseGynecologyStage (stratigraphy)AdjuvantAromatase inhibitorCohort

Abstract

fetched live from OpenAlex

Abstract Background: Adjuvant hormonal therapies for early-stage breast cancer significantly reduce the risk of recurrence, incidence of contralateral breast cancer and death from breast cancer. Optimal compliance to prescribed therapies is associated with improved patient outcomes. However, non-adherence to adjuvant tamoxifen and aromatase inhibitors (AIs) has been reported to range from 17-49% and 19-31% respectively.Objective: To evaluate medication adherence for a large population of post-menopausal women with HR+ early stage breast cancer that were prescribed initial adjuvant hormonal therapies in a publicly funded health care system, and to assess for predictive factors associated with higher rates of non-adherence.Methods: A retrospective cohort of post-menopausal patients diagnosed with HR+ stage I-III breast cancers referred to the BCCA between 2005-2008 whom were prescribed initial adjuvant hormonal therapies (either tamoxifen or an AI) were identified using the British Columbia (BC) Breast Cancer Outcomes Unit database. Cases were matched with the provincial BCCA pharmacy data repository to evaluate patterns of prescription filling. Factors including age, stage, tumor characteristics, use of chemotherapy, hormonal agent prescribed, and prescribing physician were pre-identified as potential factors predicting for non-adherence. Non-adherence was defined as less than 80% of days covered with a prescription.Results: A total of 4,592 patients were prescribed adjuvant hormonal therapies through the BCCA from 2005-2008. 2,414 patients were available for analysis after applying pre-defined inclusion criteria. Overall non-adherence rate was 40%, with non-adherence to tamoxifen and aromatase inhibitors at 42% and 37% respectively. The non-adherence cohort were older, had smaller tumor size, less nodal involvement, lower grade and lower rate of initial chemotherapy (all p<0.001). Non-adherence rates specific to individual physician prescribers ranged from 16% to 67% (p<0.001), and non-adherence rates between specialist provider groups were 34% among medical oncologists compared with 47% in radiation oncologists (p<0.001).Conclusion: Overall non-adherence to adjuvant tamoxifen and AIs in this large population of postmenopausal women with HR+ positive early stage breast cancer was 40%. This likely represents a true reflection of both non-adherence and multiple factors associated with non-adherence given the population size, public health care setting and follow-up strategies. The non-adherent cohort may be the group that is most likely to benefit from hormonal therapy (lower tumor grade) and require hormonal therapy (less adjuvant chemotherapy). Future directions should include interventions directed at physicians in addition to patients given the discrepancy in non-adherence rates among prescribers. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 36.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.381
Teacher spread0.328 · 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 designObservational
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

Citations14
Published2009
Admission routes2
Has abstractyes

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