Abstract PD7-11: The role of multi-gene hereditary cancer panels in male patients with breast cancer
Notice bibliographique
Résumé
Abstract Background/Statement of Purpose: The role of cancer susceptibility genes in the male breast cancer population beyond BRCA1 and BRCA2 (BRCA) is not well defined. While breast cancer has been documented in men with pathogenic variants in a number of other breast cancer susceptibility genes (e.g. CHEK2, PALB2, PTEN), the yield of testing is not well documented nor are predictive clinical features of those likely to harbor causative variants. This study assesses the yield of pathogenic/likely pathogenic variants (collectively, PV) in male breast cancer patients who underwent multi-gene hereditary cancer panel testing. In addition, we aim to examine predictors of identifying a PV in this population. Methods: Clinical histories and test results were reviewed for men with a diagnosis of breast cancer who underwent panel testing that included a minimum of eight well-described breast cancer susceptibility genes (ATM, BRCA1, BRCA2, CDH1, CHEK2, PALB2, PTEN, TP53) and up to 24 additional genes. Using t-test and two-tailed Fisher's exact test, we assessed whether age at diagnosis, family history of breast cancer, or the presence of selected second primary cancers (second breast, prostate, pancreatic, colon, or melanoma cancers) were associated with a greater likelihood of identifying a PV. Results: The clinical histories and test results of 381 men with breast cancer were reviewed, of whom 12.1% had at least one PV (46/381). When we limited our assessment to men who had not had prior negative BRCA testing, 13.3% had at least one PV (42/315). Variants were most commonly detected in BRCA2 (21) and CHEK2 (17), followed by PALB2 (4), BRCA1 (4), and ATM (2). A two sample t-test showed no significant difference (p=0.39) in the average age of diagnosis for those with a PV (62.5y, n=47) compared to those without a PV (60.9y, n=334). Two-tailed Fisher's exact test showed no association between having a PV and a history of a selected second primary (SP) cancer [10.8% (7/65) w/SP vs 12.3% (39/316) w/out SP; p=0.84]. Lastly, two-tailed Fisher's exact test showed those with a family history of breast cancer (fhx br) were more likely to have a PV [15.1% (32/212) fhx br vs. 8.3% (14/169) no fhx br], although this did not reach statistical significance (p=0.06). Conclusions: While BRCA2 remains the most common gene in which PVs are identified in men with breast cancer, a significant proportion of patients will have a PV in another well-described breast cancer susceptibility gene, particularly CHEK2, PALB2, and ATM. Therefore, it is reasonable to utilize a panel that is inclusive of these genes when testing male breast cancer patients. As the likelihood to harbor a PV was not significantly associated with age of onset, family history of breast cancer, or presence of a second primary, all men with breast cancer could consider genetic testing. Further study is warranted as the current sample size may limit the power to detect associations. Citation Format: Vogel Postula KJ, Andolina LM, Theobald K, McGill AK, Sutcliffe E, Arvai KJ, Murphy PD, Klein RT, Hruska KS. The role of multi-gene hereditary cancer panels in male patients with breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD7-11.
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 | 0,006 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».