Reynolds, Carol

Abstract Purpose. The Oncotype DX assay predicts likelihood of distant recurrence and improves patient selection for adjuvant chemotherapy in estrogen receptor–positive (ER-positive) early stage breast cancer. This study has two primary endpoints: to evaluate the impact of Oncotype DX recurrence scores (RS) on chemotherapy recommendations and to compare the estimated recurrence risk predicted by breast oncology specialists to RS. Methods. One hundred fifty-four patients with ER-positive early stage breast cancer and available RS results were selected. Clinicopathologic data were provided to four surgeons, four medical oncologists, and four pathologists. Participants were asked to estimate recurrence risk category and offer their chemotherapy recommendations initially without and later with knowledge of RS results. The three most important clinicopathologic features guiding their recommendations were requested. Results. Ninety-five (61.7%), 45 (29.2%), and 14 (9.1%) tumors were low, intermediate, and high risk by RS, respectively. RS significantly correlated with tumor grade, mitotic activity, lymphovascular invasion, hormone receptor, and HER2/neu status. Estimated recurrence risk by participants agreed with RS in 54.2% ± 2.3% of cases. Without and with knowledge of RS, 82.3% ± 1.3% and 69.0% ± 6.9% of patients may be overtreated, respectively (p = 0.0322). Inclusion of RS data resulted in a 24.9% change in treatment recommendations. There was no significant difference in recommendations between groups of participants. Conclusions. Breast oncology specialists tended to overestimate the risk of tumor recurrence compared with RS. RS provides useful information that improves patient selection for chemotherapy and changes treatment recommendations in approximately 25% of cases.

Abstract Background. Half of all breast cancers are early stage, lymph node negative, and hormone receptor positive. A 21-gene (Oncotype DX®; Genomic Health, Inc., Redwood City, CA) recurrence score (RS) is prognostic for recurrence and predictive of chemotherapy benefit. We explored the ability of oncologists to predict the RS using standard prognostic criteria. Methods. Standard demographic and tumor prognostic criteria were obtained from patients with an available RS. Two academic pathologists provided tumor grade, histologic type, and hormone receptor status. Six academic oncologists predicted the RS category (low, intermediate, or high) and provided a recommendation for therapy. The oncologists were then given the actual RS and provided recommendations for therapy. Analysis for agreement was performed. Results. Thirty-one cases, including nine additional cases with variant pathology reads, were presented. There was substantial agreement in oncologists' ability to discriminate between true low or true intermediate and true high (κ = 0.75; p < .0001). Predictions between low and intermediate were not consistent. The most common discrepancies were predictions of a low RS risk when cases were true intermediate and predictions of an intermediate RS risk when cases were true low. The actual RS resulted in a change in the treatment recommendations in 19% of cases. Of the 186 scenarios and six oncologists in aggregate, five fewer chemotherapy recommendations resulted with the actual RS. Conclusions. Oncologists are able to differentiate between a low or intermediate RS and a high RS using standard prognostic criteria. However, provision of the actual RS changed the treatment recommendations in nearly 20% of cases, suggesting that the RS may reduce chemotherapy use. This effect was observed in particular in intermediate-risk cases. Prospective clinical trials are necessary to determine whether decisions based on the RS change outcomes.

Abstract p16, a nuclear protein encoded by the p16INK4a gene, is a regulator of cell-cycle regulation. Previous studies have shown that expression of p16 in tissue biopsies of patients with ductal carcinoma in situ (DCIS) is associated with increased risk of breast cancer, particularly when considered in combination with other markers such as Ki-67 and COX-2. Here, we evaluated how expression of p16 in breast tissue biopsies of women with atypical hyperplasia (AH), a putative precursor lesion to DCIS, is associated with subsequent development of cancer. p16 expression was assessed by immunohistochemistry in archival sections from 233 women with AH diagnosed at the Mayo Clinic. p16 expression in the atypical lesions was scored by percentage of positive cells and intensity of staining. We also studied coexpression of p16, with Ki-67 and COX-2, biomarkers of progression in AH. Risk factor and follow-up data were obtained via study questionnaire and medical records. Forty-seven patients (20%) developed breast cancer with a median follow-up of 14.5 years. Staining of p16 was increased in older patients relative to younger patients (P = 0.0025). Although risk of developing breast cancer was not associated with increased p16 expression, joint overexpression of Ki-67 and COX-2 was found to convey stronger risk of breast cancer in the first 10 years after diagnosis as compared with one negative marker (P < 0.01). However, the addition of p16 levels did not strengthen this association. p16 overexpression, either alone or in combination with COX-2 and Ki-67, does not significantly stratify breast cancer risk in women with AH. Cancer Prev Res; 4(12); 1953–60. ©2011 AACR.

Abstract Estrogen receptor (ER) is expressed in normal and malignant breast epithelium, and expression levels have been found to increase with age in normal breast epithelium but not in atypical hyperplasia (AH) and carcinoma in situ. Here we assess ER expression in AH and its association with later breast cancer. ER expression was assessed immunohistochemically in archival sections from 246 women with AH who had open benign breast biopsy from 1967 to 1991. The ACIS III (Dako) was utilized to calculate ER expression in all atypical foci. Using multivariate linear regression, we examined associations of ER expression with age at biopsy, indication for biopsy, type of atypia, number of atypical foci, involution status, and family history. Breast cancer risk across levels of ER expression was also assessed compared with the Iowa SEER control population. Among 246 women, 87 (35%) had atypical ductal hyperplasia (ADH), 141 (57%) had atypical lobular hyperplasia (ALH), and 18 (7%) had both. Forty-nine (20%) developed breast cancer (median follow-up of 14.4 years). Multivariate analysis indicated that type of atypia and age at diagnosis were significantly associated with ER percent staining and intensity (P < 0.05). ER expression was increased in women with ADH and/or those over age 55. ER expression did not significantly impact breast cancer risk in patients diagnosed with atypia. We found increasing ER expression in AH with increasing age. ER expression in AH does not further discriminate breast cancer risk in women with atypia. Cancer Prev Res; 4(3); 435–44. ©2011 AACR.

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.

Purpose Mammographic density and lobular involution are both significant risk factors for breast cancer, but whether these reflect the same biology is unknown. We examined the involution and density association in a large benign breast disease (BBD) cohort. Patients and Methods Women in the Mayo Clinic BBD cohort who had a mammogram within 6 months of BBD diagnosis were eligible. The proportion of normal lobules that were involuted was categorized by an expert pathologist as no (0%), partial (1% to 74%), or complete involution (≥ 75%). Mammographic density was estimated as the four-category parenchymal pattern. Statistical analyses adjusted for potential confounders and evaluated modification by parity and age. We corroborated findings in a sample of women with BBD from the Mayo Mammography Health Study (MMHS) with quantitative percent density (PD) and absolute dense and nondense area estimates. Results Women in the Mayo BBD cohort (n = 2,667) with no (odds ratio, 1.7; 95% CI, 1.2 to 2.3) or partial (odds ratio, 1.3; 95% CI, 1.0 to 1.6) involution had greater odds of high density (DY pattern) than those with complete involution (P trend < .01). There was no evidence for effect modification by age or parity. Among 317 women with BBD in the MMHS study, there was an inverse association between involution and PD (mean PD, 22.4%, 21.6%, 17.2%, for no, partial, and complete, respectively; P trend = .04) and a strong positive association of involution with nondense area (P trend < .01). No association was seen between involution and dense area (P trend = .56). Conclusion We present evidence of an inverse association between involution and mammographic density.

Occult breast cancer has frequently been described as presenting as axillary lymph node metastases but rarely as gastrointestinal metastases, Varadarajan et al. (2007). In extremely rare situations, cancerous lesions identified in the gastrointestinal tract have been determined to be metastatic lesions from primary breast cancers, Taal et al. (2000). We report a case of an occult lobular adenocarcinoma presenting as gastrointestinal metastases. It is essential that the possibility of lesions found in the gastrointestinal tract originating from distant or occult cancers be considered in order that appropriate therapeutic options may be discussed and considered early after diagnosis.

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.