Biological Markers Predictive of Invasive Recurrence in DCIS

DCIS is a heterogeneous group of non-invasive cancers of the breast characterized by various degrees of differentiation and unpredictable propensity for transformation into invasive carcinoma. We examined the expression and prognostic value of 9 biological markers with a potential role in tumor progression in 133 patients with pure DCIS treated with breast conserving surgery alone, between 1982–2000. Histology was reviewed and immunohistochemical staining was performed. Pearson correlation coefficient was used to determine the associations between markers and histopathological features. Univariate and multivariate analysis examined associations between time to recurrence and clinicopathologic features and biological markers

The shifting nature of women’s experiences and perceptions of ductal carcinoma in situ

Aim: This paper is a report of a descriptive qualitative study of the evolution of women’s perceptions and experiences of ductal carcinoma in situ from the period near to diagnosis to one year later. Background: Ductal carcinoma in situ is a non-invasive breast condition where cancer cells are detected but confined to the ducts of the breast. With treatment, the condition has a positive prognosis but ironically patients undergo treatment similar to that for invasive breast cancer. There is a lack of longitudinal qualitative research studying women’s experiences of ductal carcinoma in situ, especially amongst newly diagnosed patients and how experiences change over time. Methods: Forty-five women took part in an initial interview following a diagnosis of ductal carcinoma in situ and twenty-seven took part in a follow-up interview 9-13 months later. Data were collected between January 2007 and October 2008. Transcripts were analysed using a hybrid approach to thematic analysis. Findings: Women’s early perceptions of ductal carcinoma in situ merged and sometimes conflicted with their lay beliefs of breast cancer. Perceptions and experiences of the condition shifted over time. These overriding aspects were evident within four themes identified across the interviews: 1) perceptions of DCIS versus breast cancer, 2) from paradox to acceptance, 3) personal impact, and 4) support and interactions with others. Conclusion: This study represents one of the few longitudinal qualitative studies with newly diagnosed patients, capturing women’s initial and shifting experiences and perceptions of the condition. The issues identified need to be recognised in clinical practice and supported appropriately

Changes in surgical management resulting from case review at a breast cancer multidisciplinary tumor board

BACKGROUND The treatment of breast cancer requires a multidisciplinary approach, and patients are often referred to a multidisciplinary cancer clinic. The purpose of the current study was to evaluate the impact of this approach on the surgical management of breast cancer. METHODS The medical records of 149 consecutive patients referred to a multidisciplinary breast cancer clinic over a 1-year period with a diagnosis of breast cancer were reviewed retrospectively for alterations in radiologic, pathologic, surgical, and medical interpretations and the effect that these alterations had on recommendations for surgical management. RESULTS A review of the imaging studies resulted in changes in interpretations in 67 of the 149 patients studied (45%). This resulted in a change in surgical management in 11% of patients. Review of the pathology resulted in changes in the interpretation for 43 of the 149 patients (29%). Thirteen patients (9%) had surgical management changes made solely as a result of pathologic reinterpretation. In 51 patients (34%), a change in surgical management was recommended after discussion with the surgeons, medical oncologists, and radiation oncologists that was not based on reinterpretation of the radiologic or pathologic findings. Overall, a second evaluation of patients referred to a multidisciplinary tumor board led to changes in the recommendations for surgical management in 77 of 149 of those patients studied (52%). CONCLUSIONS The changes in management stemmed from differences in mammographic interpretation, pathologic interpretation, and evaluation by medical and radiation oncologists and surgical breast specialists. Multidisciplinary review can provide patients with useful additional information when making difficult treatment decisions. Cancer 2006. © 2006 American Cancer Society.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55868/1/22266_ftp.pd

The use of complementary and alternative medicines among patients with locally advanced breast cancer – a descriptive study

BACKGROUND: Complementary and alternative medicine (CAM) use is common among cancer patients. This paper reviews the use of CAM in a series of patients with locally advanced breast cancer (LABC). METHODS: Women with LABC attending a specialist clinic at a single Canadian cancer centre were identified and approached. Participants completed a self-administered survey regarding CAM usage, beliefs associated with CAM usage, views of their risks of developing recurrent cancer and of dying of breast cancer. Responses were scored and compared between CAM users and non-users. RESULTS: Thirty-six patients were approached, 32 completed the questionnaire (response rate 89%). Forty-seven percent of LABC patients were identified as CAM users. CAM users were more likely to be younger, married, in a higher socioeconomic class and of Asian ethnicity than non-users. CAM users were likely to use multiple modalities simultaneously (median 4) with vitamins being the most popular (60%). Motivation for CAM therapy was described as, "assisting their body to heal" (75%), to 'boost the immune system' (56%) and to "give a feeling of control with respect to their treatment" (56%). CAM therapy was used concurrently with conventional treatment in 88% of cases, however, 12% of patients felt that CAM could replace their conventional therapy. Psychological evaluation suggests CAM users perceived their risk of dying of breast cancer was similar to that of the non-Cam group (33% vs. 35%), however the CAM group had less severe anxiety and depression. CONCLUSION: The motivation, objectives and benefits of CAM therapy in a selected population of women with LABC are similar to those reported for women diagnosed with early stage breast cancer. CAM users display less anxiety and depression and are less likely to believe they will die of their breast cancer. However the actual benefit to overall and disease free survival has yet to be demonstrated, as well as the possible interactions with conventional therapy. Consequently more research is needed in this ever-growing field

Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies

Purpose Better tools are needed to estimate local recurrence (LR) risk after breast-conserving surgery (BCS) for DCIS. The DCIS score (DS) was validated as a predictor of LR in E5194 and Ontario DCIS cohort (ODC) after BCS. We combined data from E5194 and ODC adjusting for clinicopathological factors to provide refined estimates of the 10-year risk of LR after treatment by BCS alone. Methods Data from E5194 and ODC were combined. Patients with positive margins or multifocality were excluded. Identical Cox regression models were fit for each study. Patient-specific meta-analysis was used to calculate precision-weighted estimates of 10-year LR risk by DS, age, tumor size and year of diagnosis. Results The combined cohort includes 773 patients. The DS and age at diagnosis, tumor size and year of diagnosis provided independent prognostic information on the 10-year LR risk (p ≤ 0.009). Hazard ratios from E5194 and ODC cohorts were similar for the DS (2.48, 1.95 per 50 units), tumor size ≤ 1 versus > 1–2.5 cm (1.45, 1.47), age ≥ 50 versus 15%) 10-year LR risk after BCS alone compared to utilization of DS alone or clinicopathological factors alone. Conclusions The combined analysis provides refined estimates of 10-year LR risk after BCS for DCIS. Adding information on tumor size and age at diagnosis to the DS adjusting for year of diagnosis provides improved LR risk estimates to guide treatment decision making

Evaluation of psychosocial distress in patients treated in a community-based oncology group practice in Germany

Background: Systematic evaluation of psychosocial distress in oncology outpatients is an important issue. We assessed feasibility and benefit of standardized routine screening using the Distress Thermometer (DT) and Problem List (PL) in all patients of our community-based hematooncology group practice

Benefit of low-dose tamoxifen in a large observational cohort of high risk ER positive breast DCIS

Lega Italiana per la Lotta contro i Tumori Gruppo Bancario Credito Valtellinese Ministero della Salute Cancer Research UK Associazione Italiana per la Ricerca sul Cancr

Quantitative thermal imaging biomarkers to detect acute skin toxicity from breast radiation therapy using supervised machine learning

Purpose Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes associated with radiation-induced dermatitis, such as inflammation, may also increase body-surface temperature, which can be detected by thermal imaging. Quantitative thermal imaging markers were identified and used in supervised machine learning to develop a predictive model for radiation dermatitis. Methods and Materials Ninety patients treated for adjuvant whole-breast RT (4250 cGy/fx = 16) were recruited for the study. Thermal images of the treated breast were taken at 4 intervals: before RT, then weekly at fx = 5, fx = 10, and fx = 15. Parametric thermograms were analyzed and yielded 26 thermal-based features that included surface temperature (°C) and texture parameters obtained from (1) gray-level co-occurrence matrix, (2) gray-level run-length matrix, and (3) neighborhood gray-tone difference matrix. Skin toxicity was evaluated at the end of RT using the Common Terminology Criteria for Adverse Events (CTCAE) guidelines (Ver.5). Binary group classes were labeled according to a CTCAE cut-off score of ≥2, and thermal features obtained at fx = 5 were used for supervised machine learning to predict skin toxicity. The data set was partitioned for model training, independent testing, and validation. Fifteen patients (∼17% of the whole data set) were randomly selected as an unseen test data set, and 75 patients (∼83% of the whole data set) were used for training and validation of the model. A random forest classifier with leave-1-patient-out cross-validation was employed for modeling single and hybrid parameters. The model performance was reported using receiver operating characteristic analysis on patients from an independent test set. Results Thirty-seven patients presented with adverse skin effects, denoted by a CTCAE score ≥2, and had significantly higher local increases in skin temperature, reaching 36.06°C at fx = 10 (P = .029). However, machine-learning models demonstrated early thermal signals associated with skin toxicity after the fifth RT fraction. The cross-validated model showed high prediction accuracy on the independent test data (test accuracy = 0.87) at fx = 5 for predicting skin toxicity at the end of RT. Conclusions Early thermal markers after 5 fractions of RT are predictive of radiation-induced skin toxicity in breast RT

A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks

Abstract: Breast cancer is currently the second most common cause of cancer-related death in women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination. However, the manual process of histopathological analysis is laborious, time-consuming, and limited by the quality of the specimen and the experience of the pathologist. This study's objective was to determine if deep convolutional neural networks can be trained, with transfer learning, on a set of histopathological images independent of breast tissue to segment tumor nuclei of the breast. Various deep convolutional neural networks were evaluated for the study, including U-Net, Mask R-CNN, and a novel network (GB U-Net). The networks were trained on a set of Hematoxylin and Eosin (H&E)-stained images of eight diverse types of tissues. GB U-Net demonstrated superior performance in segmenting sites of invasive diseases (AJI = 0.53, mAP = 0.39 & AJI = 0.54, mAP = 0.38), validated on two hold-out datasets exclusively containing breast tissue images of approximately 7,582 annotated cells. The results of the networks, trained on images independent of breast tissue, demonstrated that tumor nuclei of the breast could be accurately segmented

Updated standardized definitions for efficacy endpoints in adjuvant breast cancer clinical trials: STEEP Version 2.0

Purpose The Standardized Definitions for Efficacy End Points (STEEP) criteria, established in 2007, provide standardized definitions of adjuvant breast cancer clinical trial end points. Given the evolution of breast cancer clinical trials and improvements in outcomes, a panel of experts reviewed the STEEP criteria to determine whether modifications are needed.Methods We conducted systematic searches of ClinicalTrials.gov for adjuvant systemic and local-regional therapy trials for breast cancer to investigate if the primary end points reported met STEEP criteria. On the basis of common STEEP deviations, we performed a series of simulations to evaluate the effect of excluding non-breast cancer deaths and new nonbreast primary cancers from the invasive disease-free survival end point.Results Among 11 phase III breast cancer trials with primary efficacy end points, three had primary end points that followed STEEP criteria, four used STEEP definitions but not the corresponding end point names, and four used end points that were not included in the original STEEP manuscript. Simulation modeling demonstrated that inclusion of second nonbreast primary cancer can increase the probability of incorrect inferences, can decrease power to detect clinically relevant efficacy effects, and may mask differences in recurrence rates, especially when recurrence rates are low.Conclusion We recommend an additional end point, invasive breast cancer-free survival, which includes all invasive disease-free survival events except second nonbreast primary cancers. This end point should be considered for trials in which the toxicities of agents are well-known and where the risk of second primary cancer is small. Additionally, we provide end point recommendations for local therapy trials, low-risk populations, noninferiority trials, and trials incorporating patient-reported outcomes