Abstract PD12-04: Long-term risks of cerebrovascular accidents (CVAs) in patients with breast cancer
Notice bibliographique
Résumé
Abstract Background: Previous survivorship research has focused primarily on treatment-related risks of coronary artery disease (CAD) and congestive heart failure (CHF) even though they share common pathogenic mechanisms with CVAs. However, there are limited data on the latter. This real-world evidence study aimed to assess the associations of breast cancer treatments with subsequent development of CVAs. Methods: We identified patients diagnosed with stage I-III breast cancer in a large Canadian province from 2004 to 2017. Data from the population-based registry were linked with data from administrative sources to identify a diagnosis of CVA during follow-up after cancer treatment. Adjuvant treatment was classified as receipt of none, one, two or three depending on the number of treatment modalities (chemotherapy, radiotherapy and hormone therapy) administered. Patients with pre-existing cardiovascular disease including CAD, CHF, arrythmias and CVAs were excluded. Multivariable logistic regression analysis was performed to determine the associations of number of adjuvant treatment modalities with CVAs. Results: A total of 23,259 patients were eligible for analysis. The median age was 58 years (interquartile range, 22-101 years) and 0.5% were men. Stage distribution included 49.6% with stage I, 37.1% with stage II, and 13.4% with stage III breast cancer. Chemotherapy, radiotherapy and hormonal therapy was administered in 45.0%, 60.6%, and 68.1% of patients, respectively. While 11.0% received no adjuvant treatment, 28.7%, 35.9% and 24.4% received one, two and three modalities. At a median follow-up of 5.9 years, 1,586 (6.8%) developed new onset CVAs. The median time from diagnosis of breast cancer to CVA was 3.1 years (interquartile range, 2.7-3.5 years). In comparison, the incidence of CVAs was higher in those who received any chemotherapy (8.2% vs 5.1%, P<.001), any radiotherapy (8.3% vs 5.9%, P<.001), and any hormonal therapy (7.8% vs 6.4%, P<.001). The incidence of CVAs was 4.9%, 5.9%, 8.2% and 10.5% in patients who received none, one, two and three adjuvant treatment modalities (P<.001). After adjusting for age, patients who received two or three modalities (odds ratio [OR], 1.20; 95% confidence interval [CI], 1.03-1.41; P=.020 and OR, 1.46; 95% CI, 1.21-1.75; P<.001) experienced a higher likelihood of CVAs, compared to those who received no adjuvant therapy, while those who received one modality were at similar risk (OR,1.00; 95% CI, 0.86-1.17, P=.974). In multivariable Cox regression models adjusting for stage and treatment, patients who developed CVAs were at increased risk of death (hazard ratio, 1.44; 95% CI, 1.30-1.58; P<.001). Conclusions: The risk of CVAs in patients with resected breast cancer increases with adjuvant treatment administration. It was highest in those who received a combination of chemotherapy, radiotherapy and hormone therapy. While breast cancer survivors are monitored for coronary events and cardiomyopathy, they may benefit from surveillance of risk factors for CVAs. Citation Format: Atul Batra, Shiying Kong, Rodrigo Rigo, Winson Y Cheung. Long-term risks of cerebrovascular accidents (CVAs) in patients with breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD12-04.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».