Diagnostic delay among young women with breast cancer.
Notice bibliographique
Résumé
117 Background: Breast cancer in women under 40 is uncommon, but often presents with greater disease burden and worse survival compared to the post-menopausal population. Given its infrequence, it is not well-understood how young patients initiate contact with care and how they are investigated prior to establishing the diagnosis. Whether young women experience diagnostic delay and whether it might impact survival is unclear. We aimed to describe the presentation of breast cancer among women <40 and to understand the diagnostic timeline using patient-reported outcomes. Methods: We evaluated patients in the Reducing the Burden of Breast Cancer in Young Women (RUBY) cohort, a pan-Canadian study recruiting women <40 with breast cancer at the time of diagnosis. Five online surveys detailing demographics, medical/family history and the diagnostic journey, distributed by e-mail at the time of recruitment, were used. All subjects who completed the surveys from 2015-2022 were included. A “patient delay” was considered >4 weeks from onset of symptoms to first contact with the healthcare system. A “system delay” was considered >3 weeks from presentation to first investigation, based on Canadian Partnership Against Cancer screening guidelines. Analysis was conducted using descriptive statistics. Results: There were 1148 patients included for analysis. Median age (IQR) was 37 (33.9, 39.0). Eighty-nine percent of patients had a symptom prompting assessment, of which most had a palpable mass (77.3%), and 27.7% had a painful mass. The median (IQR) number of weeks that patients waited was 2.0 (1.0, 8.0), and 364 patients (31.7%) experienced a patient delay. Most patient delays were attributed to lack of awareness of associated symptoms: 27.7% of patients were not concerned about their symptom and 3.9% were falsely reassured by practitioners. Other reasons included difficulty accessing timely care (3.6%; 37 patients) and conflicting priorities (2.1%; 21 patients). One hundred sixteen patients (10.1%) experienced a system delay. When asked about perceived timeliness of diagnosis, only 248 patients (24.4%) felt their time to assessment was not fast enough. Conclusions: The majority of young women with breast cancer present with palpable, often painful masses. A significant proportion of women experienced a patient delay, suggesting opportunities for increased education regarding presentation of early-onset breast cancer; After presentation to care, most women were investigated in a timely manner.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».