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Purpose: Percentage mammographic density (PMD) is a major risk factor for breast cancer (BC). It is strongly associated with body mass index (BMI) and age, which are themselves risk factors for breast cancer. This analysis investigated the association between the number of full-term pregnancies and PMD in different subgroups relative to age and BMI., Methods: Patients were identified in the breast cancer database of the University Breast Center for Franconia. A total of 2410 patients were identified, for whom information on parity, age, and BMI, and a mammogram from the time of first diagnosis were available for assessing PMD. Linear regression analyses were conducted to investigate the influence on PMD of the number of full-term pregnancies (FTPs), age, BMI, and interaction terms between them., Results: As in previous studies, age, number of FTPs, and BMI were found to be associated with PMD in the expected direction. However, including the respective interaction terms improved the prediction of PMD even further. Specifically, the association between PMD and the number of FTPs differed in young patients under the age of 45 (mean decrease of 0.37 PMD units per pregnancy) from the association in older age groups (mean decrease between 2.29 and 2.39 PMD units). BMI did not alter the association between PMD and the number of FTPs., Conclusions: The effect of pregnancies on mammographic density does not appear to become apparent before the age of menopause. The mechanism that drives the effect of pregnancies on mammographic density appears to be counter-regulated by other influences on mammographic density in younger patients.

Treatment decisions in oncology are based on a balance between the efficacy of therapy and its side effects. Patients with metastases and patients with a limited prognosis are a particular challenge, since communication about the disease situation and the expected therapeutic benefit is difficult not only for patients, but also for physicians. The aim of this study was therefore to compare the benefits expected of therapy by patients and physicians. Questionnaires were sent to 9,000 breast cancer patients and to 6,938 physicians. The questionnaires described 10 cases of breast cancer in the metastatic setting. The patients and physicians were asked to state the treatment benefit they would require to decide for the therapy options chemotherapy, endocrine therapy, antibody therapy, radiotherapy, and bisphosphonates. Additionally, the participants provided data on patient and physician characteristics. Expected treatment benefits were compared between patients and physicians, and influencing factors that modified the expected benefit were identified. Patients expected much greater benefits from the therapies offered than the physicians. For all treatment modalities, about 50 % or more of patients expected more than a 12-month increase in overall survival from all therapies. Among the doctors, this proportion ranged from 7 to 30 %. Among patients, previous experience of side effects and having young children in the family were the strongest influencing factors. Among the doctors, age and level of education had a strong influence on the expected prognostic improvement to indicate a therapy option. As expectations of treatment differ greatly between patients and doctors, a structured approach to solving this conflict is required. There appear to be some indicators that might help address the problem, such as the physicians' level of training and experience and the patients' specific social circumstances.

Prediction of the prognosis for metastatic breast cancer patients depends on molecular subtypes similar to those found in patients with primary breast cancer. Several studies have shown that estrogen receptor (ER) and progesterone receptor (PR) status determine the course of the disease and the prognosis. As Ki-67 helps to differentiate molecular subtypes in patients with primary breast cancer, the aim of this study was to assess the prognostic relevance of Ki-67 in the primary tumor in relation to its prognostic relevance for patients with metastatic breast cancer. A total of 467 patients with invasive breast cancer were identified in the database of a single breast cancer center, in whom Ki-67 had been assessed in tumor material from the breast at the time of the primary diagnosis and who had developed a metastasis at any time during the subsequent course. For these patients, tumor and patient characteristics were used to determine prognostic factors relative to overall survival after the diagnosis of distant metastases. Ki-67 was added to this model to investigate whether this might improve the prediction of overall survival. In the multivariate Cox model, age at diagnosis, body mass index, nodal status, tumor size, ER and PR status, and time from diagnosis to metastasis were identified as relevant prognostic factors. Adding Ki-67 to the model improved the prediction of overall survival. There was also a significant and relevant interaction with the PR status. In patients with a low-proliferation primary tumor, a high level of PR expression would indicate an extraordinarily good prognosis (HR 0.39; 95 % CI, 0.23-0.66). In patients with higher-proliferation primary tumors, PR status was not capable of differentiating prognostic groups. Ki-67 is useful in addition to known prognostic factors for breast cancer. It is able to indicate a group of women with a poorer prognosis, specifically in the group of patients with PR-positive breast cancer.

There is growing evidence that certain breast cancer (BC) risk factors specifically increase the risk for specific molecular tumor subtypes. Different molecular subtypes of BC can partly be described by analyzing proliferation in tumors. Very few data are available regarding the association of mammographic density (MD), as a BC risk factor, with proliferation. The aim of this study was to analyze the association between Ki-67 expression in BCs and MD. In this case-only study, data on BC risk factors, hormone receptor expression, and MD were available for 1,975 patients with incident BC. MD was assessed as percentage mammographic density (PMD) using a semiautomated method by two readers for every patient. The association of the Ki-67 proliferation index and PMD was studied using multifactorial analyses of covariance (ANCOVA), with PMD as the target variable and including well-known factors that are also associated with MD such as age, parity, use of hormone replacement therapy (HRT), and body mass index (BMI). There were no significant differences in PMD between women with BC who had low and high Ki-67 values (P = 0.31). However, there were relevant differences in women with low BMI (P = 0.07), and in women using postmenopausal HRT (P = 0.06) as well as in women with low PR values (P = 0.07). In these subgroups, the Ki-67 expression index increased with decreasing PMD. Likewise PMD is correlated with BMI, parity status, and menopausal status stronger in patients with low proliferating tumors, and with progesterone receptor expression in patients with high proliferating tumors. MD correlates inversely with Ki-67 proliferation in BC tumors only in some subgroups of BC patients, defined by commonly known BC risk factors that are usually associated with MD as well.

It has been shown in several studies that antihormonal compounds can offer effective prophylactic treatment to prevent breast cancer. In view of the low participation rates in chemoprevention trials, the purpose of this study was to identify the characteristics of women taking part in a population-based mammography screening program who wished to obtain information about the risk of breast cancer and then participate in the the International Breast Cancer Intervention Study II (IBIS-II) trial, a randomized double-blind controlled chemoprevention trial comparing anastrozole with placebo. A paper-based survey was conducted in a population-based mammography screening program in Germany between 2007 and 2009. All women who met the criteria for the mammography screening program were invited to complete a questionnaire. A total of 2,524 women completed the questionnaire, and 17.7% (n = 446) met the eligibility criteria for the IBIS-II trial after risk assessment. The women who wished to receive further information about chemoprevention were significantly younger (P < 0.01) and had significantly more children (P = 0.03) and significantly more relatives with breast cancer (P < 0.001). There were no significant differences between the participants with regard to body mass index or hormone replacement therapy. Normal mammographic findings at screening were the main reason (42%) for declining to participate in the IBIS-II trial or attend risk counseling. The ultimate rate of recruitment to the IBIS-II trial was very low (three women). Offering chemoprevention to women within a mammography screening unit as part of a paper-based survey resulted in low participation rates for both, the survey and the final participation in the IBIS-II trial. More individualized approaches and communication of breast cancer risk at the time of the risk assessment might be helpful to increase the participation and the understanding of chemopreventive approaches.

Chronic pain and neural irritation after breast surgery and radiation are still relevant sequelae of the treatment. Pain quantification and localization in patient groups are difficult to standardize. In order to quantify and localize pain in a group of breast cancer patients, a Java-based program was developed to visualize the frequency of pain in "pain maps." A questionnaire with structured questions on the perception of pain included pictograms of a body to mark possible pain areas. A group of 343 breast cancer survivors completed the questionnaires. The image information was digitalized and processed using a Java applet. Gray-scale summation pictures with numbers from "0," indicating black (100% pain), to "255," indicating white (0% pain), were generated. The visualization of pain by creating pain maps revealed the location of pain in breast cancer survivors on pictograms of the body. Analyzing the total number of pixels, in which pain was stated, made it possible to compare pain areas in several subgroups, showing that patients after mastectomy versus breast-conserving therapy (3,011 vs. 2,224 pixels), and patients with lymphedema versus patients without lymphedema (3,010 vs. 2,239 pixels), have larger pain areas. This study presents a method of visualizing pain areas and assigning them to a pictogram of the body in a sample of breast cancer patients. The method is easy to use and could help generate pain maps in several types of disease.

Purpose: Mammography (MG), breast (BU) and axillary ultrasound (AU), and clinical examination (CE) are commonly used for clinical staging. These different methods were compared in order to assess the accuracy of clinical tumor staging (cT)., Method: About 503 breast cancer (BC) patients were prospectively measured by MG, ultrasound and clinical examination. Pearson's correlation to pathological tumor size (pT) was tested and the deviation of MG, BU and CE to pT was analyzed in subgroups defined by pT, grading (G), estrogen receptor (ER), progesteron receptor (PR), proliferation (MIB-1) and HER2/neu. Association of AU to pN was examined by chi(2)-test. Receiver operating characteristics (ROC) were used to test the prediction of a pT > 2 cm., Results: Mammography correlated best with pT (r = 0.752). Mammography (mean (MG) = 2.17 cm) overestimated tumors in size (mean (pT) = 2.04 cm) rather than ultrasound (mean (BU) = 1.86 cm) and clinical examination (mean (cT) = 1.70 cm). pT of invasive ductal BC could be estimated significantly better than pT of invasive lobular BC. Smaller tumors were better to assess than larger ones. Tumors with a grading G1 were easier to estimate than tumors with G2/3. Best predictor of a pT > 2 cm was the mammography with an area under the curve of 0.876. The combination of all three modalities by linear regression performed even better with an AUC of 0.906., Conclusions: The dimension of invasive ductal carcinomas, small and low grading tumors is significantly better to estimate. Concerning treatment decisions, we propose a combination of all three modalities, as the best predictive value was seen for the complementary use of mammography, ultrasound and clinical examination.