Abstract P5-10-06: Retrospective, population-based cohort study on associations between tumor size, receptor status, & regional nodal positivity rates for early-stage breast cancer: implications for decision between upfront surgery vs neoadjuvant systemic therapy
Notice bibliographique
Résumé
Abstract Purpose: For clinically node-negative T1-T2 breast cancers, the ASCO/Ontario Health guidelines discourage staging axillary ultrasound (AxUS). At the same time, neoadjuvant systemic therapy (NST) is recommended for HER2-positive(+) and triple negative (TN) breast cancers over 2 cm, with controversy whether clinical T1cN0 HER2+ and TN breast cancers should receive NST or upfront surgery. We evaluated the rates of regional nodal positivity across T1a, T1b, T1c and T2 tumor sizes for hormone receptor (HR)+HER2-, HR-HER2+, HR+HER2+, and TN breast cancers. Methods: We performed a population-based, retrospective cohort study using administrative health databases at ICES Ontario. Data from all patients diagnosed with invasive breast cancer between 2000 – 2019 in Ontario, Canada were extracted from the Ontario Cancer Registry. Demographic, tumor, and treatment data were collected from the linked databases. The following variables were analyzed: T stage, number of positive regional lymph nodes, and estrogen, progesterone, and HER2 receptor statuses. The proportion of patients with positive lymph nodes was calculated for each receptor subtype. Chi-square tests (significance of P <0.05) with post-hoc Marascuilo correction were conducted. Analyses were conducted using SAS® and Python software. Results: There were 52,888 invasive breast cancers, including 39,265 HR+HER2- (74%), 5,511 HR+HER2+ (10%), 2,523 HR-HER2+ (5%), and 5,589 HR-/HER2- (11%). Increasing tumor size was associated with increasing rates of regional nodal positivity across all receptor subtypes (P < .001 for all). Among TN tumors, T1a lesions had a nodal positivity rate of 19% (95% CI 0.12 – 0.24), T1b 19% (95% CI 0.15 – 0.23), T1c 28% (95% CI 0.26 – 0.30), and T2 42% (95% CI 0.40 – 0.43). Among HR-HER2+ tumors, T1a lesions had a nodal positivity rate of 18% (95% CI 0.13 – 0.24), T1b 30% (95% CI 0.24 – 0.37), T1c 42% (95% CI 0.37 – 0.46), and T2 54% (95% CI 0.51 – 0.57). Among HR+HER2+ tumors, T1a lesions had nodal positivity rate of 23% (95% CI 0.19 – 0.29), T1b 20% (95% CI 0.17 – 0.25), T1c 32% (95% CI 0.29 – 0.34), and T2 56% (95% CI 0.54 – 0.58). Among HR+HER2- tumors, T1a had a rate of 16% (95% CI 0.15 – 0.18), T1b 16% (95% CI 0.15 – 0.17); T1c 30% (95% CI 0.29 – 0.30), and T2 54% (95% CI 0.54 – 0.56). For T1a lesions, nodal positivity rates were similar across all receptor subtypes. For T1b and T2 lesions, pairwise comparisons were significantly different between all receptor subtypes, except between HR+HER2+ and TN, and HR+HER2- and HR-HER2+, respectively. For T1c, HR-HER2+ had the highest rates of nodal positivity, followed by HR+HER2+, HR+HER2-, and TN (P < .001). Conclusion: While current guidelines discourage AxUS for cT1-T2N0 breast cancers, at the population-level, pathologic regional nodal positivity rates are not insignificant for T1-T2 tumors, especially TN and HER2+ tumors. Taking these patients with pathologically positive lymph nodes to upfront surgery results in undertreatment. Furthermore, for clinical T1c tumors, regional nodal positivity rates reached 42%, 32%, and 28% for HR-HER2+, HR+HER2+, and TNBC, respectively. These data need to be shared with patients with cT1c tumors when deciding between a NST or upfront surgery approach. Finally, we advocate that staging AxUS should be considered for all HER2+ and TN T1-T2 tumors, irrespective of tumor size. Citation Format: Yerin R. Lee, Vasily Giannakeas, David W. Lim. Retrospective, population-based cohort study on associations between tumor size, receptor status, & regional nodal positivity rates for early-stage breast cancer: implications for decision between upfront surgery vs neoadjuvant systemic therapy [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P5-10-06.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».