Abstract SP097: Local Regional Management Following Neoadjuvant Chemotherapy: Minding the Knowledge Gaps
Notice bibliographique
Résumé
Abstract Neoadjuvant chemotherapy is often used in managing breast cancer patients, particular those with HER2-positive (HER2+) or triple negative disease. Among the known benefits of administering chemotherapy prior to surgery is the opportunity to assess response which informs prognosis. The CTneoBC analysis, which included 12 trials enrolling over 11,950 patients, showed that patients experiencing a pathologic complete response (pCR; ypT0ypN0 or ypT0/isN0) have improved event-free and overall survival with the association between pCR and longterm outcomes being strongest in patients with triple negative breast cancer (TNBC) and in those with HER2+/hormone receptor-negative breast cancer receiving trastuzumab. In triple negative and HER2+ breast cancer, the response to neoadjuvant chemotherapy also informs the need for additional adjuvant therapy. For patients with TNBC and significant residual disease after neoadjuvant chemotherapy, the CREATE-X trial showed benefit for adjuvant xeloda. For patients with HER2+ breast cancer not experiencing a pCR to neoadjuvant chemotherapy plus HER2-targeted therapy, the KATHERINE trial showed a significant improvement in invasive disease-free survival and overall survival in patients receiving adjuvant T-DM1 versus adjuvant trastuzuamb. With respect to considerations for local regional therapy, it is known that neoadjuvant chemotherapy decreases the primary tumor size such that tumors thought to be inoperable become operable and tumors thought to require mastectomy downstage to be eligible for lumpectomy. More recently it has been shown that neoadjuvant chemotherapy can decrease the extent of axillary surgery required. While historically patients with clinically node positive disease at presentation were thought to require axillary lymph node dissection (ALND), the American College of Surgeons Oncology Group Z1071 trial demonstrated that sentinel lymph node biopsy (SLNB) was feasible in those who convert to clinically node negative disease following neoadjuvant chemotherapy. These findings were confirmed in the European SENTINA trial and Canadian SN-FNAC study. All three of these studies suggested that technical aspects of the SLNB procedure were critical to ensure a sufficiently low false negative rate. While these are the “known knowns”, there are many “known unknowns” and evolving data, particularly as it relates to local regional therapy following neoadjuvant chemotherapy. Included among the “known unknowns” are the optimal imaging modality to assess response to neoadjuvant chemotherapy thereby facilitating surgical planning, optimal technique for performing SLNB for those patients converting from clinical N1 to clinical N0 disease after neoadjuvant chemotherapy, the definition of negative margins for a lumpectomy, the role of routine use of immunohistochemistry for cytokeratins in pathologic evaluation of the sentinel lymph nodes, the optimal method for pathologic staging following neoadjuvant chemotherapy, and the role of ALND versus radiation therapy for patients with residual nodal metastases in the sentinel nodes. More recently, it has been questioned whether patients experiencing a complete radiographic response can undergo image guided biopsy in lieu of surgery; yet data from 3 prospective series demonstrate unacceptably high false negative rates with this approach. Given the significant implications of accurately assessing response to therapy and the presence of residual disease, optimizing local regional management is a critical component of the multidisciplinary care of these patients. In this lecture, the available data guiding local regional management after neoadjuvant chemotherapy will be reviewed with attention focused on areas in which there is limited data, therefore knowledge gaps. Citation Format: E Mittendorf. Local Regional Management Following Neoadjuvant Chemotherapy: Minding the Knowledge Gaps [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 SP097.
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 | 0,010 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,003 |
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 ».