Exploring Differences in Breast Cancer Presentation, Recurrence and Survival by Race/Ethnicity among Young Women in the Prospective PYNK Database
Notice bibliographique
Résumé
Abstract Background: While socioeconomic factors contribute to most of the disparities in breast cancer (BC) outcomes between countries, the contribution of biological factors related to race/ethnicity has not been fully explored. Using our prospective database of young BC patients referred from the Greater Toronto Area, we compared clinical/pathological features of the BC, distant recurrence-free survival, and BC-specific survival according to patient race/ethnicity. Methods: A chart review was conducted of the 240 women aged 40 years and younger with a new diagnosis of BC who were seen at the Sunnybrook Odette Cancer Center (an academic tertiary referral cancer center in multiethnic Toronto, Canada) between February 2008 and January 2015 and enrolled in the prospective PYNK database. Associations between patients’ race/ethnicity (classified into five groups) and personal characteristics (age, weight, education, and estimated household income), results of germ-line genetic testing, tumor characteristics, treatment, and clinical outcomes were assessed. Results: Among the 209 women (87%) for whom parental race/ethnicity was known and who were not of “mixed” ancestry, race/ethnicity was as follows: Caucasian 57.4% ( n = 120), Black 8.6% ( n = 18), East Asian 15.8% ( n = 33), South Asian 8.6% ( n = 18), and South-East Asian 9.6% ( n = 20). Median age at the diagnosis of BC was 37. Median tumor size was 2.5 cm, and 58% had lymph node involvement. The majority of patients had hormone receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative BC, 26% had HER2-positive disease, and 13% had triple-negative BC (TNBC). One hundred and seventy-five (83.7%) patients were treated with chemotherapy, 51 (29.1%) of whom received it in the neoadjuvant setting. There were no statistically significant differences in median age, residence type (urban vs. rural), income level, germ-line genetic test results, tumor histology (lobular vs. ductal), BC subtype, stage of disease at presentation, or proportion of patients who received chemotherapy across the various racial/ethnic groups. With a median follow-up of 10.5 years, South Asian women had a nonsignificantly higher risk of distant recurrence and BC-specific death compared with Caucasian women (hazard ratio [HR] = 1.27, 95% confidence interval [CI]: 0.49–3.29, P = 0.627 and HR = 1.42, 95% CI: 0.48–4.16, P = 0.521, respectively), while East Asian ethnicity was associated with lowest risk of distant recurrence (HR = 0.52, 95% CI: 0.18–1.49, P = 0.224) and BC-related death (HR = 0.36, 95% CI: 0.08–1.53, P = 0.167). Conclusion: Our study shows interesting trends of worse BC outcomes among South Asian women and better outcomes among those of East Asian descent. Future validation of our findings in a larger cohort of young women with BC would be of interest.
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 | 0,001 | 0,004 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».