Abstract P6-09-04: Benign breast disease and breast cancer risk across the spectrum of familial risk using a prospective family study cohort (ProF-SC)
Notice bibliographique
Résumé
Abstract Background: Benign breast disease (BBD) is one of the strongest risk factors for breast cancer but it is unclear whether the strength of the association with BBD and breast cancers varies by breast cancer family history. Few studies of BBD enrich specifically for putative genetic factors by over-sampling based on family history let alone evaluate potential interactions with measures of underlying familial risk. The aim of this study was to evaluate how risk associated with BBD is modified by underlying familial risk so as to guide clinical management and risk assessment of women with BBD. Methods: Using a prospective family study cohort of 17,154 women unaffected with breast cancer at baseline and followed by questionnaire at regular intervals, we examined the association between BBD and breast cancer risk using Cox Proportional Hazards models. We classified women as having BBD if they reported at baseline having been told by a doctor that they had BBD, such as a non-cancerous cyst or breast lump. We did not have information on histologic sub-type. We confirmed self-reported diagnosis of BBD with pathology reports in a subset of the New York cohort and found high agreement between self-reported and pathologically confirmed BBD (93.5%). We assessed multiplicative and additive interactions with underlying familial risk profile (FRP) defined as either fixed-time horizon of 1-year, or total lifetime risk, estimated from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. Results: During 176,756 person-years of follow-up (mean 10.2, maximum 23.7 years), we observed 968 incident breast cancers cases with an average age at diagnosis of 55.8 years and average age at enrollment into the cohort of 46.8 years. At baseline, 4,704 (27%) women reported having a previous diagnosis of BBD. Compared to women with no history of BBD, breast cancer risk was increased in women of all ages (HR: 1.37, 95% CI: 1.19,1.56), and in women up to age 45 years (using attained age models) (HR: 1.40, 95% CI: 1.01,1.93). In terms of recency of BBD, we found that the increased risk associated with BBD remained 21 years or more after the initial BBD diagnosis (HR: 1.37, 95% CI: 1.11, 1.68). We found no evidence for multiplicative interactions with FRP, which implies that the increase in absolute risk associated with BBD depends on a woman's FRP (Table 1). Conclusions: Women with a history of BBD have an increased risk of breast cancer that multiplies their underlying familial risk (FRP). These results could prove to be valuable for risk counseling and clinical management. Table 1: Cumulative Incidence of Breast Cancer to age 45, 55, and 65 by BBD and underlying FRP as measured by 10-year BOADICEA score.AgeNo BBD, <3.4 %BBD, <3.4%No BBD, ≥3.4%BBD, ≥3.4%454.6 (3.8, 5.6)6.1(4.7, 8.0)12.1 (10.2, 14.5)16.1 (13.1, 19.7)557.4 (6.3, 8.7)9.8 (7.5, 12.8)19.1 (16.6, 22.0)25.0 (21.7, 28.9)659.7 (8.2, 11.5)12.8 (9.9, 16.5)24.5 (21.8, 27.6)31.8 (28.3, 35.7) Citation Format: Zeinomar N, Phillips KA, Liao Y, MacInnis RJ, Dite GS, Daly MB, John EM, Andrulis IL, Buys SS, Hopper JL, Terry MB. Benign breast disease and breast cancer risk across the spectrum of familial risk using a prospective family study cohort (ProF-SC) [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 P6-09-04.
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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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».