Anderson, Stewart

Abstract Background: Women with benign breast disease are at elevated breast cancer risk. In order to accurately predict a woman's individual risk of breast cancer, a breast cancer risk-prediction model is needed that incorporates significant breast cancer risk factors. This report describes two factors: tissue based assessment of lobular involution, and radiological marker- mammographic density (MD). Lobular involution, or physiologic atrophy of the breast glandular epithelium, is inversely associated with breast cancer risk. MD is a strong positive risk factor for breast cancer. With increasing age, the extent of lobular involution increases while MD decreases. However, it is unclear whether involution and MD represent independent breast cancer risk factors. We examined breast cancer risk associated with lobular involution and MD in women with benign breast disease (BBD) to determine whether these features are independently associated with breast cancer risk.Methods: Using the Mayo Clinic Surgical and Pathology Indices, 9376 women ages 18 to 85 with benign excisional breast biopsy between January 1, 1967 and December 31, 1991 were identified and formed the Mayo BBD cohort. We studied a sub-cohort of women diagnosed with BBD between 1985 and 1991 (when MD was clinically assessed and recorded) who had a mammogram within 6 months of the BBD diagnosis. Breast cancer outcomes were determined through the Mayo medical records and a study-specific questionnaire. Lobular involution extent was assessed in background tissue as 'none' (0% lobules involuted), 'partial' (1-74% lobules involuted) or 'complete' (≥75% lobules involuted). MD was classified as Wolfe's parenchymal pattern (PP) as N1/ fatty; P1; P2; and DY/ homogenously dense. Hazard ratios and confidence intervals were calculated using Cox regression analyses, adjusting for confounders: age, parity, BMI, BBD histology, menopausal status, family history, PP and involution extent.Results: A total of 2666 women in the Mayo BBD cohort, with biopsies between 1985 and 1991, had a mammogram within 6 months of the breast biopsy. The mean age at biopsy was 54.6 years. After a mean follow-up of 13.3 years, 172 (6.5%) women developed breast cancer. After adjustment for PP and other confounders, women with no or partial involution had elevated risk compared to women with complete involution (HR 2.62 [95% CI 1.39, 4.94] for no involution and 1.61 [95% CI 1.03, 2.53] for partial involution; complete involution as reference group; p for trend 0.003). Moreover, women with dense breasts were at greater risk compared to women with nondense breasts (HR 1.67 [95% CI 1.0, 2.73] for DY pattern, 1.96 [95% CI 1.2 – 3.21] for P2, 1.23 [95% CI 0.67, 2.26] for P1; N1 category as reference group; p for trend 0.02). Multivariate analyses also showed that women with the combination of no involution and dense breasts had greater risk compared to those with complete involution and nondense breasts (HR 4.08 [95% CI 1.72, 9.68]).Conclusion: Lobular involution and MD are both risk factors for breast cancer; this report is the first to demonstrate that each provides unique information about breast cancer risk. These findings emphasize the potential for inclusion of both these factors in future breast cancer risk-prediction models. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6064.

Abstract Background: Risk prediction models are important clinical tools for counseling and decision making for women with an elevated risk of breast cancer, such as women with atypical lobular or ductal hyperplasia (atypia). The Gail model has been shown to underestimate the risk of breast cancer in women with atypia. We sought to evaluate the performance of the Tyrer-Cuzick model in a well-defined cohort of women with atypia.Methods: The Mayo Benign Breast Disease (BBD) Cohort includes 9,376 women aged 18 to 85 who had an open breast biopsy with benign pathological findings between 1967 and 1991. The subset of women with atypia was identified by our study pathologists. Risk factor data required by the Tyrer-Cuzick model were collated for each woman, and the model was used to predict each woman's risk of developing invasive breast cancer within ten years. The predicted numbers of breast cancers were compared to the observed numbers to assess overall model calibration, and the concordance between breast cancer outcomes and predicted probabilities was used to measure the accuracy of the model on the individual level. Subset analysis of women with strong family history was performed. Strong family history was defined as: at least one first-degree relative with breast cancer before the age of 50 years or two or more relatives with breast cancer, at least one being a first degree relative.Results: Three hundred and thirty one women with atypia were identified. Over a mean follow up of 13.7 years, 62 (19%) women have developed invasive breast cancer. Thirty one women developed invasive cancer in the first ten years after biopsy. The Tyrer-Cuzick model predicted that 64.6 invasive breast cancers would occur in the first ten years after biopsy. Thus, the predicted to observed ratio was 2.08 [95% CI: 1.47 – 2.96], p < 0.001).The concordance statistic was 0.51, revealing that the Tyrer-Cuzick model did not accurately distinguish, on an individual level, between women who were diagnosed with invasive breast cancer within ten years of biopsy and those who were not.Performance was somewhat better in the subset of 68 women with a strong family history of breast cancer. The model predicted 12.3 invasive breast cancers, and 7 were observed, for a predicted to observed ratio of 1.76 [95% CI: 0.84 – 3.70]. The concordance statistic was 0.57.Conclusion: The Tyrer-Cuzick model significantly overestimated the risk of breast cancer in the first ten years after biopsy for this group of women with atypia. Individual risk estimates showed poor concordance. Performance was slightly improved in women with a strong family history of breast cancer. Physicians should be cautious when using the Tyrer-Cuzick model to predict ten-year risk in patients with atypia. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6063.

Abstract Abstract #5008 Background: Accurate, individualized risk prediction for breast cancer is lacking. Tissue-based features, such as the terminal duct lobular unit (TDLU), may help to stratify women into different risk levels as breast lobules are the anatomic sites of origin of breast cancer. As women age, these lobular structures should regress, which results in reduced breast cancer risk. Regression, however, does not occur in all women.
 Materials and Methods: We have quantified the extent of lobule regression on a benign breast biopsy in 85 breast cancer cases and 142 age-matched controls from the Mayo Benign Breast Disease Cohort, by determining number of acini/lobule and lobular area. We also calculated Gail model 5-year predicted risks for these women.
 Results: There is a step-wise increase in breast cancer risk with increasing numbers of acini/lobule (p=0.0004). Adjusting for Gail model score, parity, histology, and family history did not attenuate this association.
 
 Lobular area was similarly associated with risk. The Gail model estimates were associated with risk of breast cancer (p=0.03). We examined the individual accuracy of these measures using the concordance (c) statistic. The Gail model c-statistic was 0.60 (95% CI; 0.50-0.70); the acinar count c-statistic was 0.65 (95% CI; 0.54-0.75). Combining acinar count and lobular area, the c-statistic was 0.68 (95% GI; 0.58-0.78). Adding the Gail model to these did not improve the c-statistic.
 
 Discussion: Novel, tissue-based features that reflect the status of a woman's normal breast lobules are strongly associated with breast cancer risk. These features appear to provide more accurate risk assessment than the currently used Gail model. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 5008.