A study design to explore the determinants of breast cancer survival in Ontario’s First Nations women
Notice bibliographique
Résumé
B51 Background: Recent data have shown that survival after a breast cancer diagnosis is poorer among First Nations women compared to other Ontario women. There are many possible determinants of this survival discrepancy, many of which have not been studied among a Native population. The main purpose of this study is to identify determinants for the poorest breast cancer survival by comparing stage, treatment and other risk factors among First Nations and non-First Nations women diagnosed with breast cancer from 1995-2004 in Ontario. Once these have been determined, actions can be taken to improve the prognosis of First Nations women with breast cancer. Objectives: 1)To compare the distribution of stage at diagnosis (stage II+ vs. stage I) for Ontario First Nations and non-First Nations women diagnosed with breast cancer between 1995 to 2004. 2) To compare other potential determinants of survival between the two populations, such as treatment, prognostic features of breast cancer, co-morbidity, and distance from an Integrated Cancer Program by stage at diagnosis. 3) Depending on the number of deaths in the First Nations women at the end of the study, we propose to compare stage specific survival between the two populations. Hypotheses: 1) First Nations women are diagnosed with breast cancer at a later stage of disease (either stage II, III or IV) than non-First Nations women in Ontario. 2) First Nations women diagnosed with breast cancer at a later stage in Ontario may differ by the treatment they receive, prognostic features of breast cancer, co-morbidity, and distance from an Integrated Cancer Program compared to the general population. 3) Stage-specific survival among women diagnosed with breast cancer is worse for First Nations women in Ontario compared to general population. Study Design: This study employs a case-case design using the cohort of First Nations people in Ontario to identify an estimated 315 women diagnosed with invasive breast cancer between 1995 and 2004. Concurrently, a random sample of 630 non-First Nations women will be selected through the population-based cancer registry at Cancer Care Ontario and matched 2 to 1 on five-year date of diagnosis, age at diagnosis (15-54 vs. 55+), and Integrated Cancer Program first attended. Data on stage at diagnosis, treatment received, risk factors and co-morbid conditions will be collected from medical charts at the provincial Integrated Cancer Programs. Analysis: To address the primary objective of the study, stage at diagnosis will be aggregated into a binary variable to obtain the distribution across the two populations. Logistic regression models will be performed to investigate the second study objective. The analyses will test the influence of the independent variables of interest by stage at diagnoses comparing the two populations. We propose a Cox-proportional hazards regression model to assess stage specific survival (for stages 2+) for the third study objective. Contribution of Study: This is a unique opportunity to study factors related to breast cancer survival in this Ontario’s First Nations women. This work is expected to inform health care decision makers about where barriers may exist with respect to cancer screening, treatment and surveillance for First Nations women. The results of this study may support improvements of cancer care for this population.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».