Citations

Abstract Background: Uncontrolled proliferation is a defining feature of the malignant phenotype. Ki67 is a marker for proliferating cells and is overexpressed in many breast cancers. Atypical hyperplasia is a premalignant lesion of the breast (relative risk ∼ 4.0). Here we asked if Ki67 expression could stratify risk in women with atypia.Methods: Ki67 expression was assessed immunohistochemically by digital image analysis in archival sections from 192 women with atypia diagnosed at the Mayo Clinic 1/1/67-12/31/91. Risk factor and follow-up data were obtained via study questionnaire and medical records. Observed breast cancer events were compared to population expected rates (Iowa SEER) using standarized incidence ratios (SIRs). We examined both short-term (within 10 years) and long-term (after 10 years) risk of breast cancer (BC) following atypia biopsy.Results: The median value for percent positive cells for Ki67 was 1.0%; the 75th percentile value was 2.3%. Based on the empirical distribution of staining values in our cohort, we selected a cutoff of 2% cells positive to separate high from low staining. There were no differences in Ki67 levels by age at biopsy, type of atypia (ADH, ALH, or both), number of foci of atypia, or family history. 32 women developed BC over a median of 14.6 years. Among them, those with ≥2% Ki67 expression had a shorter time to breast cancer (median 5.5 years, IQR=3.2-7.2) than those with <2% cells positive (median=13.8 years, IQR=11.6-20.3). There was a positive association between Ki67 overexpression (≥2% of cells positive) and risk of BC in the first 10 years of follow-up (SIR=4.42 [95% CI 2.21-8.84]). This excess risk resulted in a 10-year cumulative incidence of 14.1%. In contrast, in the women with low Ki67 expression, we found no increased risk of BC in the first 10 years, with SIR 1.01 (95% CI 0.38-2.70), which was significantly lower than the women with high expression (p=0.01). The 10-year cumulative incidence of BC was 3% for the low Ki67group, in line with population averages. After 10 years, risk increased significantly in the low Ki67 group [SIR 5.69 (3.63-8.92)] vs. no increased risk in the high Ki67 group [SIR 0.78 (0.11-5.55)]. We formally examined this apparent time-dependent difference in incidence patterns by Ki67 staining levels via Poisson regression analysis, and found a statistically significant interaction between pre- vs. post-10 years incidence and high vs. low staining levels (p<0.001).Conclusions: Ki67 appears to be a time-varying biomarker of risk of breast cancer in women with atypical hyperplasia. Women whose atypias show higher proliferation rates have an increased risk for an earlier BC (within 10 years). Those with lower proliferation rates tend to develop BCs later, after 10 years. Ki67 levels may help to define the time period of greatest risk for women with atypia. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 909.

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 #62 Background: Breast cancer is the leading cause of cancer deaths in younger women (25 to 49 years of age). Young women with breast cancer also have worse overall survival and increased risk of recurrence compared to older women with breast cancer. Innovative approaches to understanding risk factors and tissue characteristics for the younger population can improve understanding of breast cancer etiology and enhance risk-stratification for these women. This study was aimed at examining breast cancer risk factors among young women (<50 years) with BBD. Materials and Methods: Utilizing the Mayo Clinic Surgical and Pathology Indices, women ages 18 to 85 who had benign excisional breast biopsy between January 1, 1967 and December 31, 1991 were identified. The diagnosis of breast cancer served as the study endpoint and was determined using the Mayo medical record and questionnaire information from study participants. The breast pathologist, blinded to the initial diagnosis and clinical outcome, performed pathology review. BBD was classified as non-proliferative disease (NPD), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH). Age-related lobular involution (reduction in number and size of acini per lobule) was classified as none-0%, partial- 1 to74%, or complete- >75% involution. Relative risk (RR) was estimated by comparing the number of observed breast cancers with the number expected, based on breast cancer rates in the Iowa Surveillance, Epidemiology, and End Results registry. Results: Of the 9376 women in the Mayo BBD cohort, 4460 women were aged <50 years at BBD diagnosis and formed the study cohort. The mean age at BBD diagnosis was 39.4 (+ 8.3) years. With a median follow-up of 20 years, 326 breast cancer cases were identified. The histologic findings were NPD in 72% of women, PDWA in 26%, and AH in 2%. The relative risk of breast cancer for the overall cohort of young women with BBD was 1.5 (95% CI [1.4, 1.7]). The relative risk among those with AH was 6.9 (95% CI [4.6, 10.1), compared with a RR of 2.0 (95% CI [1.7, 2.4]) for PDWA, and RR of 1.2 (95% CI [1.0, 1.4]) for NPD. Risk was associated with extent of lobular involution (RR for no involution was 1.7 (95%CI [1.4, 2.1]); partial involution 1.4 (95%CI [1.2, 1.7]); complete involution 0.7 (95%CI [0.3, 1.4]). Family history was available for 83% of the cohort and RR was 2.2 (95% CI [1.7, 2.8]) for women with strong family history and was 1.3 (95% CI [1.1, 1.6]) for women with no family history. Discussion: Young women with BBD are at increased risk of breast cancer. Risk is high in women with atypical hyperplasia, and those with a family history of breast cancer. Lobular involution is associated with reduced breast cancer risk in this population, suggesting a role in modifying breast cancer risk. These findings suggest the need for further research in this population, along with tissue-based studies to examine the processes leading to breast cancer, and enable identification of those women at highest risk. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 62.

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.

Purpose Accurate breast cancer risk assessment is vital to personalize screening and risk reduction strategies. Women with atypical hyperplasia have a four-fold higher risk of breast cancer. We evaluated the performance of the Tyrer-Cuzick model, which was designed to predict 10-year risk of breast cancer development, in a well-defined cohort of women with atypia. Patients and Methods The Mayo Benign Breast Disease cohort includes 9,376 women who had a benign breast biopsy between 1967 and 1991. Among those, 331 women with atypia were identified by our study pathologists. Risk factor data for the Tyrer-Cuzick model were collated for each woman and used to predict individual risk of developing invasive breast cancer within 10 years. Results Over a median follow-up of 14.6 years, 64 (19%) of the 331 women developed invasive breast cancer. In the first 10 years after biopsy, 31 women developed invasive breast cancer whereas the Tyrer-Cuzick model predicted 58.9. The observed-to-predicted ratio was 0.53 (95% CI, 0.37 to 0.75). The concordance statistic was 0.540, revealing that the Tyrer-Cuzick model did not accurately distinguish, on an individual level, between women who developed invasive breast cancer and those who did not. Conclusion The Tyrer-Cuzick model significantly overestimated risk of breast cancer for women with atypia, and individual risk estimates showed poor concordance between predicted risk and invasive breast cancer development. Thus, we cannot recommend the use of the Tyrer-Cuzick model to predict 10-year breast cancer risk in women with atypical hyperplasia.

Background— Factors that determine survival in pulmonary arterial hypertension (PAH) drive clinical management. A quantitative survival prediction tool has not been established for research or clinical use. Methods and Results— Data from 2716 patients with PAH enrolled consecutively in the US Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL) were analyzed to assess predictors of 1-year survival. We identified independent prognosticators of survival and derived a multivariable, weighted risk formula for clinical use. One-year survival from the date of enrollment was 91.0% (95% confidence interval [CI], 89.9 to 92.1). In a multivariable analysis with Cox proportional hazards, variables independently associated with increased mortality included pulmonary vascular resistance >32 Wood units (hazard ratio [HR], 4.1; 95% CI, 2.0 to 8.3), PAH associated with portal hypertension (HR, 3.6; 95% CI, 2.4 to 5.4), modified New York Heart Association/World Health Organization functional class IV (HR, 3.1; 95% CI, 2.2 to 4.4), men >60 years of age (HR, 2.2; 95% CI, 1.6 to 3.0), and family history of PAH (HR, 2.2; 95% CI, 1.2 to 4.0). Renal insufficiency, PAH associated with connective tissue disease, functional class III, mean right atrial pressure, resting systolic blood pressure and heart rate, 6-minute walk distance, brain natriuretic peptide, percent predicted carbon monoxide diffusing capacity, and pericardial effusion on echocardiogram all predicted mortality. Based on these multivariable analyses, a prognostic equation was derived and validated by bootstrapping technique. Conclusions— We identified key predictors of survival based on the patient’s most recent evaluation and formulated a contemporary prognostic equation. Use of this tool may allow the individualization and optimization of therapeutic strategies. Serial follow-up and reassessment are warranted. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00370214.

Purpose Accurate, individualized risk prediction for breast cancer is lacking. Tissue-based features may help to stratify women into different risk levels. 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. However, this does not occur in all women. Methods We have quantified the extent of lobule regression on a benign breast biopsy in 85 patients who developed breast cancer and 142 age-matched controls from the Mayo Benign Breast Disease Cohort, by determining number of acini per 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 per lobule (P = .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 = .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 to 0.70); the acinar count c statistic was 0.65 (95% CI, 0.54 to 0.75). Combining acinar count and lobular area, the c statistic was 0.68 (95% CI, 0.58 to 0.78). Adding the Gail model to these measures did not improve the c statistic. Conclusion Novel, tissue-based features that reflect the status of a woman's normal breast lobules are associated with breast cancer risk. These features may offer a novel strategy for risk prediction.

Purpose An accurate estimate of a woman's breast cancer risk is essential for optimal patient counseling and management. Women with biopsy-confirmed atypical hyperplasia of the breast (atypia) are at high risk for breast cancer. The Gail model is widely used in these women, but has not been validated in them. Patients and Methods Women with atypia were identified from the Mayo Benign Breast Disease (BBD) cohort (1967 to 1991). Their risk factors for breast cancer were obtained, and the Gail model was used to predict 5-year–and follow-up–specific risks for each woman. The predicted and observed numbers of breast cancers were compared, and the concordance between individual risk levels and outcomes was computed. Results Of the 9,376 women in the BBD cohort, 331 women had atypia (3.5%). At a mean follow-up of 13.7 years, 58 of 331 (17.5%) patients had developed invasive breast cancer, 1.66 times more than the 34.9 predicted by the Gail model (95% CI, 1.29 to 2.15; P < .001). For individual women, the concordance between predicted and observed outcomes was low, with a concordance statistic of 0.50 (95% CI, 0.44 to 0.55). Conclusion The Gail model significantly underestimates the risk of breast cancer in women with atypia. Its ability to discriminate women with atypia into those who did and did not develop breast cancer is limited. Health care professionals should be cautious when using the Gail model to counsel individual patients with atypia.