Pre-diagnosis morbidity related to health care utilization in young women with breast cancer : a matched case-control study
Notice bibliographique
Résumé
Background- Early-onset breast cancer is the leading cause of cancer deaths in Canadian women aged 30-39. There is much that is not known about what causes this disease. Many of the potential risk factors associated with this disease have strong hormonal, inflammatory or immunologic mechanisms, and may be reflected in morbidity prior to diagnosis. \nResearch Question- This study addresses the question: Is morbidity in the five years prior to diagnosis associated with an increased risk of early-onset breast cancer? The primary objective of this study is to describe the extent and patterns of non-cancer morbidity in women diagnosed with breast cancer by age 40, and to compare them with similarly-aged women without a breast cancer by that age. \nMethods- A total of 1132 female breast cancer patients diagnosed in British Columbia from 1999 to 2008 inclusive were identified through the provincial cancer registry; 1302 female birth year-matched comparators were randomly selected from the provincial health insurance registry. Linked provincial registry, clinical, and healthcare administrative data were used to examine the morbidity experience of subjects for five years before the breast cancer diagnosis or matched date among controls. Morbidity was measured using Johns Hopkins ACG System Aggregated Diagnostic Group (ACG) codes. A multivariate conditional logistic regression model estimated the association between ACG grouping and breast cancer incidence using a one-tailed significance level of α = 0.05. \nResults- Five (pregnancy, prevention, signs and symptoms/major, unstable orthopedic and stable eye) of 32 ACGs were statistically significantly higher among women with breast cancer than the population sample in at least two of the five years prior to diagnosis. The ACG for asthma produced results of interest. The majority of significant results were observed two to three years preceding diagnosis. \nDiscussion- The increased rate of major signs and symptoms, and asthma, in particular, among young women with breast cancer may point to important underlying risks in this population. Given the number of breast cancer risk factors that have strong associations with hormonal mechanisms, such as reproductive health, hormonal conditions may determine whether lifestyle and other risk factors lead to carcinogenesis.
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 | 0,000 | 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 ».