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)
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".