Abstract P3-02-06: Magnetic resonance imaging (MRI) surveillance for patients with dense breasts and a previous breast cancer (BC) and/or high risk lesion
Notice bibliographique
Résumé
Abstract BACKGROUND AND PURPOSE The benefits of breast MRI for screening women at high risk of developing BC is established, but its role in women with a personal history of BC or dense breasts is unknown. We sought to estimate the performance of annual surveillance MRI added to mammography in women at moderately increased BC risk due to a personal history of breast cancer and/or a high-risk breast lesion and dense breasts. METHOD AND MATERIALS We performed a retrospective chart review of the clinical, radiological, and pathological parameters of women who received annual, concurrent surveillance breast MRI and mammography between 04/2013 and 12/2015. We included women who met all of the following criteria: age<69; prior diagnosis of high-risk lesion (ADH, ALH, LCIS), DCIS, or invasive BC; heterogeneously (50-75%) or extremely dense (>75%) breasts; and did not qualify for our provincial MRI screening program for high risk women (calculated lifetime BC risk ≥ 25%). Results of each scan were analyzed using descriptive statistics and Chi squared for comparisons between subgroups. RESULTS A total of 199 patients (267 MRI exams) were included in this study. The mean age at initial diagnosis was 45 years and at subsequent diagnosis of DCIS or invasive cancer was 53 years. Mean time to new diagnosis was 86 months (range 14-202). All 15 cancers diagnosed during the study period were MRI detected: 11 invasive stage I (66% IDC, 7% ILC) and 4 DCIS (27%). Of these 15, all but 1 were mammographically occult. Five (33%) were found in the breast ipsilateral to the original lesion. The cancer detection rate was 6% (12/199) on the first screening round and 4.7% (3/64) on the second screening round. Specificity and positive predictive value respectively for MRI exams increased from 77% and 22% on the first screening round to 88% and 30% on the second round. Of women who developed BC, 57% had a history of breast or ovarian cancer in a first degree relative. None of the 72 women who were on hormonal therapy at the time of surveillance imaging had a new cancer detected compared to 11% (14/125) of those who were not on hormonal therapy (p=0.0025). CONCLUSIONS The incremental early-stage BC detection rate and specificity of MRI in this population are comparable to what is observed in screening women at high risk. The addition of annual MRI to mammography should be considered for surveillance of women with a personal history of BC / premalignant lesion and heterogeneous / extremely dense breasts, particularly if they have a family history of BC and are not on hormonal therapy. Citation Format: Nadler M, Al Attar H, Curpen B, Martel AL, Balasingham S, Zhang L, Eisen A, Warner E. Magnetic resonance imaging (MRI) surveillance for patients with dense breasts and a previous breast cancer (BC) and/or high risk lesion [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-02-06.
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 | 0,000 | 0,002 |
| 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) | 0,003 | 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 ».