HER2-low breast cancer brain metastases: Incidence and treatment implications.
Notice bibliographique
Résumé
2035 Background: Brain metastases (BrM) are a major cause of morbidity and mortality among women with breast cancer (BC). Central nervous system (CNS)-penetrating systemic therapies for patients with HER2-negative BrM are lacking; this is particularly problematic for patients with triple negative disease (TNBC) who have a high likelihood of developing BrM. Given CNS activity of trastuzumab deruxtecan, efficacy for patients with HER2-low BrM is of interest. Methods: A retrospective study of two cohorts of patients who underwent surgery for BC BrM at Sunnybrook Health Sciences Centre between 1999-2013 and 2008-2018 were identified. Estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 (HER2) status were assessed based on 2018 ASCO/CAP guidelines. HER2-zero was defined as immunohistochemistry (IHC) 0; HER2-low was defined as IHC 1+ or IHC 2+ with fluorescence in situ hybridization (FISH) negative status. HER2-positive was defined as IHC 3+ or IHC 2+ with positive FISH. Clinicopathological features were recorded. We also assessed the prognostic association between extent of HER2 expression and i) brain-specific progression free survival (bsPFS), as well as ii) overall survival (OS). Results: Out of 137 patients with resected BrM, tissue for HER2 assessment was available in 74.5% (n=102) of cases. In this cohort, the median age at BrM diagnosis was 53.5 (range, 32-85). 18.6% (n=19) had leptomeningeal disease and 68.6% (n=70) had extracranial disease. 53% (n=54) of the BrM were HER2-positive; 29.4% (n=30) were HER2-low and 17.6% (n=18) had HER2-zero status. Among BrM that were triple negative based on ASCO/CAP guidelines, 14 out of 22 cases (63.6%) were re-classified as being HER2-low. 15/25 (60%) BrM that were hormone receptor positive/HER2 negative (HR+/HER2-) based on ASCO/CAP guidelines were re-classified as being HER2-low. In total, 51 patients had matched primary breast and BrM tissue available; results of HER2 status when categorized as HER2-zero, HER2-low and HER2-positive were concordant in 82.3% (n= 42/51) of cases (Cohen’s kappa 0.58, p=0.0719). In 7 cases, the primary breast tissue was HER2-zero whereas the BrM was either HER2-low (n=5) or HER2-positive (n=2). In only one case (2%), expression of HER2 was lower in the BrM (HER2-low) compared to the primary BC (HER2-positive). Median time from primary BC to the development of BrM was 35 months (IQR, 14-69) in the overall cohort; patients with HER2-zero BrM had a numerically longer time to development of BrM (45.8 months), compared to those with HER2-low (35 months) and HER2-positive (35 months) BrM (p=0.948). There was no significant association between HER2-zero, HER2-low and HER2-positive status in BrM and either bsPFS or OS. Conclusions: Among patients with surgically resected BrM, a high proportion of those with metastatic TNBC and HR+/HER2-negative disease have “HER2-low” BrM with potential to benefit from HER2-targeted therapy.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».