Citations

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 #12 Background: Meta-analyses (EBCTCG, Lancet 2005; 365:2687) have established in estrogen receptor (ER) positive breast cancer (BC) that 5 yrs of adjuvant tamoxifen (Tam) substantially reduces recurrence and mortality. The aromatase inhibitors (AIs) anastrozole, exemestane and letrozole have been studied in prospective trials in postmenopausal patients (pts) in comparison with Tam either as initial monotherapy (Cohort 1) or after 2 to 3 years of Tam in a switching strategy (Cohort 2); both to a total of 5 years (yrs) of endocrine therapy.
 Methods: Outcomes data submitted to EBCTCG were used in separate meta-analyses of Cohort 1 (trials: ATAC, BIG 1-98/IBCSG 18-98) and of Cohort 2 (trials: ABCSG 8, ARNO 95, IES/BIG 2-97, ITA). The primary analysis involved pts with tumors reported to be ER positive with endpoints of BC recurrence (all, local only, contralateral BC only, distant), death with and without recurrence, any death. Subgroup analyses included progesterone receptor (PgR) status, age, tumor grade and nodal status. All p-values were 2-sided.
 Results: Highlights include: Cohort 1: 9,856 pts with 50,000 woman-years of follow-up. At 5 yrs, AI therapy was associated with an absolute 2.7% (standard error [SE] 0.7) decrease in BC recurrence (10.7% vs 13.4%, relative decrease 20% [SE 5], p=0.00004). There appeared to be greater proportional decreases in isolated local recurrence (30% [SE 10], p=0.003) and in contralateral disease (38% [SE 12], p=0.003) than in distant recurrence (12% [SE 6], p= 0.04). AIs yielded an absolute 1.0% (SE 0.5) decrease in BC mortality (5.5% vs 6.5%, relative decrease 7% [SE 7], p=0.28). Cohort 2: 9,015 pts with 33,000 woman-years of follow-up. At 6 yrs from treatment divergence (i.e., 8-9 yrs from diagnosis), AI therapy was associated with an absolute 3.5% (SE 1.1) decrease in BC recurrence (12.6% vs 16.1%, relative decrease 29% [SE 6], p<0.00001). There appeared to be greater proportional reductions in isolated local recurrence (40% [SE 13], p=0.002) and in contralateral disease (35% [SE 16], p=0.03) than in distant recurrence (24% [SE 7], p= 0.001). AIs yielded an absolute 1.6% (SE 0.8) decrease in BC mortality (6.3% vs 8.0%, relative decrease 22% [SE 9], p=0.02). Subset analyses with respect to PgR status, age, tumor grade and nodal status revealed no apparent heterogeneity between the proportional reductions in recurrence and no indication of an increase or decrease in non-breast deaths with AIs in either cohort 1 or 2.
 Conclusions: In 2 separate meta-analyses considering both the initial monotherapy setting and the switching setting after 2 to 3 yrs of Tam, AIs produced significantly lower BC recurrence rates compared with Tam. Additional follow-up data will provide important information on long-term survival. Meta-analyses can be helpful even in the era of relatively large clinical trials. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 12.

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.

Abstract The majority of candidates for breast cancer prevention have not accepted tamoxifen because of the perception of an unfavorable risk/benefit ratio and the acceptance of raloxifene remains to be determined. One means of improving this ratio is to identify women at very high risk of breast cancer. Family history, age, atypia in a benign biopsy, and reproductive factors are the main parameters currently used to determine risk. The most powerful risk factor, mammographic density, is not presently employed routinely. Other potentially important factors are plasma estrogen and androgen levels, bone density, weight gain, age of menopause, and fracture history, which are also not currently used in a comprehensive risk prediction model because of lack of prospective validation. The Breast Cancer Prevention Collaborative Group (BCPCG) met to critically examine and prioritize risk factors that might be selected for further testing by multivariate analysis using existing clinical material. The BCPCG reached a consensus that quantitative breast density, state of the art plasma estrogen and androgen measurements, history of fracture and height loss, BMI, and waist–hip ratio had sufficient priority for further testing. As a practical approach, these parameters could be added to the existing Tyrer–Cuzick model which encompasses factors included in both the Claus and Gail models. The BCPCG analyzed potentially available clinical material from previous prospective studies and determined that a large case/control study to evaluate these new factors might be feasible at this time.