Correlation of RANK and RANKL with mammographic density in primary breast cancer patients.

PURPOSE: The receptor activator of nuclear factor kappa B (RANK) and its ligand (RANKL) have been shown to promote proliferation of the breast and breast carcinogenesis. The objective of this analysis was to investigate whether tumor-specific RANK and RANKL expression in patients with primary breast cancer is associated with high percentage mammographic density (PMD), which is a known breast cancer risk factor. METHODS: Immunohistochemical staining of RANK and RANKL was performed in tissue microarrays (TMAs) from primary breast cancer samples of the Bavarian Breast Cancer Cases and Controls (BBCC) study. For RANK and RANKL expression, histochemical scores (H scores) with a cut-off value of > 0 vs 0 were established. PMD was measured in the contralateral, non-diseased breast. Linear regression models with PMD as outcome were calculated using common predictors of PMD (age at breast cancer diagnosis, body mass index (BMI) and parity) and RANK and RANKL H scores. Additionally, Spearman rank correlations (ρ) between PMD and RANK and RANKL H score were performed. RESULTS: In the final cohort of 412 patients, breast cancer-specific RANK and RANKL expression was not associated with PMD (P = 0.68). There was no correlation between PMD and RANK H score (Spearman's ρ = 0.01, P = 0.87) or RANKL H score (Spearman's ρ = 0.04, P = 0.41). RANK expression was highest in triple-negative tumors, followed by HER2-positive, luminal B-like and luminal A-like tumors, while no subtype-specific expression of RANKL was found. CONCLUSION: Results do not provide evidence for an association of RANK and RANKL expression in primary breast cancer with PMD.

Comprehensive characterization of endometriosis patients and disease patterns in a large clinical cohort.

PURPOSE: In many diseases, it is possible to classify a heterogeneous group into subgroups relative to tumor biology, genetic variations, or clinical and pathological features. No such classification is available for endometriosis. In our retrospective case-case analysis we defined subgroups of endometriosis patients relative to the type and location of the endometriosis lesion and relative to basic patient characteristics. METHODS: From June 2013 to July 2017, a total of 1576 patients with endometriosis diagnosed at surgery were included in this study. The patients' history and clinical data were documented using a web-based remote data entry system. To build subgroups, all possible combinations of endometriosis locations/types (peritoneal; ovarian endometriosis; deeply infiltrating endometriosis; adenomyosis) were used. Due to the variation in group sizes, they were combined into five substantial larger groups. RESULTS: Age, pregnancy rate, and live birth rate were identified as characteristics that significantly differed between the five patient groups that were defined. No significant differences were noted in relation to body mass index, length of menstrual cycle, age at menarche, reason for presentation, or educational level. CONCLUSION: This study describes basic patient characteristics in relation to common clinical subgroups in a large clinical cohort of endometriosis patients. Epidemiological information about different clinical groups may be helpful in identifying groups with specific clinical courses, potentially suggesting novel approaches to early detection and to surgical and systemic treatment.

Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression.

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.

Association between mammographic density and pregnancies relative to age and BMI: a breast cancer case-only analysis.

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.

What do patients want to know about contraception and which method would they prefer?

PURPOSE: The aim of this study was to determine the extent to which women's choice of contraceptive method depends on the advice received from their gynecologist and whether more intensive counseling might lead to more frequent use of long-acting reversible contraception (LARC). METHODS: A total of 1089 physicians and 18,521 women responded to 32 or 37 questions, respectively, using an online questionnaire. The women were asked about their current use of contraceptive methods, the extent of their satisfaction with them, their satisfaction with the counseling they had received, and whether they wanted to have more information about contraception. The physicians were similarly asked which contraceptive methods were being used, how satisfied with them they were, how they would assess their patients' satisfaction with them, and whether the women wanted to have more information. RESULT: The results showed that 61% of the women were using oral contraceptives, and a total of only 9% were using behavior-independent long-term contraceptive methods. However, 60% of the women stated that long-term contraception would be an option for them if they had more information about it. Gynecologists underestimated this figure, at only 18%. Whereas 66% of the gynecologists believed that their patients never forgot to take the pill, nearly, half of the women stated that they had forgotten it at least once during the previous 3 months. CONCLUSION: The small number of women who use long-term contraception is in clear contrast to the fact that many women want to have a very safe but also behavior-independent method.

Operative techniques and complications of extraction and transplantation of ovarian tissue: the Erlangen experience.

PURPOSE: Extracting ovarian tissue before oncologic therapy and transplanting it afterwards are increasingly being used to preserve fertility in women. This study describes standardized and safe operative procedures, with few complications, and reports the resulting ovarian function and pregnancy rates. METHODS: The standardized operative techniques for removing and transplanting ovarian tissue used at the Erlangen center are: for tissue removal, one-third to half of the tissue from one ovary is excised with scissors, without tissue coagulation; for subsequent transplantation, pieces of ovarian tissue are placed in a retroperitoneal pocket without closure of the pocket. RESULTS: Between January 2007 and December 2015, ovarian tissue was extracted in 399 women and transplanted following cancer therapy in 38. No surgical complications were observed within 28 days. To date, there have been ten pregnancies and nine live births after transplantation in seven different women; 26 of the 38 women developed hormonal activity, confirmed by a menstrual cycle or raised serum estradiol levels. CONCLUSIONS: The techniques for laparoscopic removal and transplantation of ovarian tissue described here provide a standardized method with a very low risk of complications. The pregnancy rate after ovarian tissue transplantation, currently 15-30%, can be expected to rise further in the near future.

Mammographic density is the main correlate of tumors detected on ultrasound but not on mammography.

Although mammography screening programs do not include ultrasound examinations, some diagnostic units do provide women with both mammography and ultrasonography. This article is concerned with estimating the risk of a breast cancer patient diagnosed in a hospital-based mammography unit having a tumor that is visible on ultrasound but not on mammography. A total of 1,399 women with invasive breast cancer from a hospital-based diagnostic mammography unit were included in this retrospective study. For inclusion, mammograms from the time of the primary diagnosis had to be available for computer-assisted assessment of percentage mammographic density (PMD), as well as Breast Imaging Reporting and Data System (BIRADS) assessment of mammography. In addition, ultrasound findings were available for the complete cohort as part of routine diagnostic procedures, regardless of any patient or imaging characteristics. Logistic regression analyses were conducted to identify predictors of mammography failure, defined as BIRADS assessment 1 or 2. The probability that the visibility of a tumor might be masked at diagnosis was estimated using a regression model with the identified predictors. Tumors were only visible on ultrasound in 107 cases (7.6%). PMD was the strongest predictor for mammography failure, but age, body mass index and previous breast surgery also influenced the risk, independently of the PMD. Risk probabilities ranged from 1% for a defined low-risk group up to 40% for a high-risk group. These findings might help identify women who should be offered ultrasound examinations in addition to mammography.

Endometriosis as a risk factor for ovarian or endometrial cancer - results of a hospital-based case-control study.

BACKGROUND: No screening programs are available for ovarian or endometrial cancer. One reason for this is the low incidence of the conditions, resulting in low positive predictive values for tests, which are not very specific. One way of addressing this problem might be to use risk factors to define subpopulations with a higher incidence. The aim of this study was to investigate the extent to which a medical history of endometriosis can serve as a risk factor for ovarian or endometrial cancer. METHODS: In a hospital-based case-control analysis, the cases represented patients with endometrial or ovarian cancer who were participating in studies aimed at assessing the risk for these diseases. The controls were women between the age of 40 and 85 who were invited to take part via a newspaper advertisement. A total of 289 cases and 1016 controls were included. Using logistic regression models, it was tested whether self-reported endometriosis is a predictor of case-control status in addition to age, body mass index (BMI), number of pregnancies and previous oral contraceptive (OC) use. RESULTS: Endometriosis was reported in 2.1 % of the controls (n = 21) and 4.8 % of the cases (n = 14). Endometriosis was a relevant predictor for case-control status in addition to other predictive factors (OR 2.63; 95 % CI, 1.28 to 5.41). CONCLUSION: This case-control study found that self-reported endometriosis may be a risk factor for endometrial or ovarian cancer in women between 40 and 85 years. There have been very few studies addressing this issue, and incorporating it into a clinical prediction model would require a more precise characterization of the risk factor of endometriosis.

Prognostic relevance of Ki-67 in the primary tumor for survival after a diagnosis of distant metastasis.

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.

Shared decision-making in metastatic breast cancer: discrepancy between the expected prolongation of life and treatment efficacy between patients and physicians, and influencing factors.

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.

Predicting mammographic density with linear ultrasound transducers.

BACKGROUND: High mammographic density (MD) is a risk factor for the development of breast cancer (BC). Changes in MD are influenced by multiple factors such as age, BMI, number of full-term pregnancies and lactating periods. To learn more about MD, it is important to establish non-radiation-based, alternative examination methods to mammography such as ultrasound assessments. METHODS: We analyzed data from 168 patients who underwent standard-of-care mammography and performed additional ultrasound assessment of the breast using a high-frequency (12 MHz) linear probe of the VOLUSON® 730 Expert system (GE Medical Systems Kretztechnik GmbH & Co OHG, Austria). Gray level bins were calculated from ultrasound images to characterize mammographic density. Percentage mammographic density (PMD) was predicted by gray level bins using various regression models. RESULTS: Gray level bins and PMD correlated to a certain extent. Spearman's ρ ranged from - 0.18 to 0.32. The random forest model turned out to be the most accurate prediction model (cross-validated R2, 0.255). Overall, ultrasound images from the VOLUSON® 730 Expert device in this study showed limited predictive power for PMD when correlated with the corresponding mammograms. CONCLUSIONS: In our present work, no reliable prediction of PMD using ultrasound imaging could be observed. As previous studies showed a reasonable correlation, predictive power seems to be highly dependent on the device used. Identifying feasible non-radiation imaging methods of the breast and their predictive power remains an important topic and warrants further evaluation. Trial registration 325-19 B (Ethics Committee of the medical faculty at Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany).

Characterizing mammographic images by using generic texture features.

INTRODUCTION: Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. METHODS: A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. RESULTS: Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. CONCLUSIONS: Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy.

Association of mammographic density with hormone receptors in invasive breast cancers: results from a case-only study.

For many breast cancer (BC) risk factors, there is growing evidence concerning molecular subtypes for which the risk factor is specific. With regard to mammographic density (MD), there are inconsistent data concerning its association with estrogen receptor (ER) and progesterone receptor (PR) expression. The aim of our study was to analyze the association between ER and PR expression and MD. In our case-only study, data on BC risk factors, hormone receptor expression and MD were available for 2,410 patients with incident BC. MD was assessed as percent MD (PMD) using a semiautomated method by two readers for every patient. The association of ER/PR and PMD was studied with multifactorial analyses of covariance 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, and body mass index (BMI). In addition to the commonly known associations between PMD and age, parity, BMI and hormone replacement therapy, a significant inverse association was found between PMD and ER expression levels. Patients with ER-negative tumors had an average PMD of 38%, whereas patients with high ER expression had a PMD of 35%. A statistical trend toward a positive association between PMD and PR expression was also seen. PMD appears to be inversely associated with ER expression and may correlate positively with PR expression. These effects were independent of other risk factors such as age, BMI, parity, and hormone replacement therapy, possibly suggesting other pathways that mediate this effect.

Association of mammographic density with the proliferation marker Ki-67 in a cohort of patients with invasive 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.

Ki67, chemotherapy response, and prognosis in breast cancer patients receiving neoadjuvant treatment.

BACKGROUND: The pathological complete response (pCR) after neoadjuvant chemotherapy is a surrogate marker for a favorable prognosis in breast cancer patients. Factors capable of predicting a pCR, such as the proliferation marker Ki67, may therefore help improve our understanding of the drug response and its effect on the prognosis. This study investigated the predictive and prognostic value of Ki67 in patients with invasive breast cancer receiving neoadjuvant treatment for breast cancer. METHODS: Ki67 was stained routinely from core biopsies in 552 patients directly after the fixation and embedding process. HER2/neu, estrogen and progesterone receptors, and grading were also assessed before treatment. These data were used to construct univariate and multivariate models for predicting pCR and prognosis. The tumors were also classified by molecular phenotype to identify subgroups in which predicting pCR and prognosis with Ki67 might be feasible. RESULTS: Using a cut-off value of > 13% positively stained cancer cells, Ki67 was found to be an independent predictor for pCR (OR 3.5; 95% CI, 1.4, 10.1) and for overall survival (HR 8.1; 95% CI, 3.3 to 20.4) and distant disease-free survival (HR 3.2; 95% CI, 1.8 to 5.9). The mean Ki67 value was 50.6 ± 23.4% in patients with pCR. Patients without a pCR had an average of 26.7 ± 22.9% positively stained cancer cells. CONCLUSIONS: Ki67 has predictive and prognostic value and is a feasible marker for clinical practice. It independently improved the prediction of treatment response and prognosis in a group of breast cancer patients receiving neoadjuvant treatment. As mean Ki67 values in patients with a pCR were very high, cut-off values in a high range above which the prognosis may be better than in patients with lower Ki67 values may be hypothesized. Larger studies will be needed in order to investigate these findings further.

Assessment of breast cancer tumour size using six different methods.

OBJECTIVES: Tumour size estimates using mammography (MG), conventional ultrasound (US), compound imaging (CI) and real-time elastography (RTE) were compared with histopathological specimen sizes. METHODS: The largest diameters of 97 malignant breast lesions were measured. Two US and CI measurements were made: US1/CI1 (hypoechoic nucleus only) and US2/CI2 (hypoechoic nucleus plus hyperechoic halo). Measurements were compared with histopathological tumour sizes using linear regression and Bland-Altman plots. RESULTS: Size prediction was best with ultrasound (US/CI/RTE: R (2) 0.31-0.36); mammography was poorer (R(2) = 0.19). The most accurate method was US2, while US1 and CI1 were poorest. Bland-Altman plots showed better size estimation with US2, CI2 and RTE, with low variation, while mammography showed greatest variability. Smaller tumours were better assessed than larger ones. CI2 and US2 performed best for ductal tumours and RTE for lobular cancers. Tumour size prediction accuracy did not correlate significantly with breast density, but on MG tumours were more difficult to detect in high-density tissue. CONCLUSIONS: The size of ductal tumours is best predicted with US2 and CI2, while for lobular cancers RTE is best. Hyperechoic tumour surroundings should be included in US and CI measurements and RTE used as an additional technique in the clinical staging process.

Breast volumetry using a three-dimensional surface assessment technique.

BACKGROUND: Breast volume is a relevant measure for the prevention and prediction of diseases and for aesthetic surgery. This study evaluated a new technique to determine breast volume and compared measures using a three-dimensional (3D) body surface scanner and magnetic resonance imaging (MRI) scans, with the latter used as the standard method. METHODS: Both MRI scans and body surface 3D scans were obtained from 22 women. For each method, breast volumes were assessed. The MRI calculations of the breast volumes were performed by a specially trained radiologist using analysis software. A textured 3D image was generated by a calibrated digital texture camera after breast surface data acquisition. The volume assessment of the 3D photography was calculated using a software package after manual outlining of the breast and automated projection of a dorsal limit. Linear regression was used to predict the MRI volume assessment with the 3D image volume assessment. RESULTS: The mean breast volume according to MRI volumetry was 442.8 ml on the left side and 471.8 ml on the right side. The mean breast volume using a 3D body surface volume assessment method was 273.8 ml (observer A) and 226.2 ml (observer B) on the left side and 284.4 ml (observer A) and 234.9 ml (observer B) on the right side. The use of linear regression models showed R (2) values of 0.59-0.77. The mean time for MRI recording and volume assessment was 68.0 ± 14.1 min for both sides and 11.6 ± 1.5 min for 3D recording and volume assessment. CONCLUSIONS: The 3D surface-based volume measurements are feasible in terms of time and can predict the MRI breast volume with sufficient accuracy. This might facilitate the broad use of such an assessment technique in a large-scale epidemiologic study using breast volume as a study aim. Additionally, further development of volume assessments could help to implement this technique in breast surgery procedures.

Mammographic density and prognosis in primary breast cancer patients.

PURPOSE: Mammographic density (MD) is one of the strongest risk factors for breast cancer (BC). However, the influence of MD on the BC prognosis is unclear. The objective of this study was therefore to investigate whether percentage MD (PMD) is associated with a difference in disease-free or overall survival in primary BC patients. METHODS: A total of 2525 patients with primary, metastasis-free BC were followed up retrospectively for this analysis. For all patients, PMD was evaluated by two readers using a semi-automated method. The association between PMD and prognosis was evaluated using Cox regression models with disease-free survival (DFS) and overall survival (OS) as the outcome, and the following adjustments: age at diagnosis, year of diagnosis, body mass index, tumor stage, grading, lymph node status, hormone receptor and HER2 status. RESULTS: After median observation periods of 9.5 and 10.0 years, no influence of PMD on DFS (p = 0.46, likelihood ratio test (LRT)) or OS (p = 0.22, LRT), respectively, was found. In the initial unadjusted analysis higher PMD was associated with longer DFS and OS. The effect of PMD on DFS and OS disappeared after adjustment for age and was caused by the underlying age effect. CONCLUSIONS: Although MD is one of the strongest independent risk factors for BC, in our collective PMD is not associated with disease-free and overall survival in patients with BC.

Pain perception and detailed visual pain mapping in breast cancer survivors.

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.

Breast cancer risk assessment in a mammography screening program and participation in the IBIS-II chemoprevention trial.

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.