Adherence of Adjuvant Hormonal Therapies in Post-Menopausal Hormone Receptor Positive (HR+) Early Stage Breast Cancer: A Population Based Study from British Columbia.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».