Radiotherapy after mastectomy for screen-detected ductal carcinoma in situ

Background. A role for radiotherapy after mastectomy for ductal carcinoma in situ (DCIS) is unclear. Using a prospective audit of DCIS detected through the NHS Breast Screening Programme we sought to determine a rationale for the use of postmastectomy radiotherapy for DCIS. Methods. Over a nine year period, from 9,972 patients with screen-detected DCIS and complete surgical, pathology, radiotherapy and follow up data, 2,944 women underwent mastectomy for DCIS of whom 33 (1.12%) received radiotherapy. Results. Use of post mastectomy radiotherapy was significantly associated with a close (<1mm) pathology margin, particularly (χ2(1) 95.81; p<0.00001), DCIS size (χ2 (3) 16.96; p<0.001) and the presence of microinvasion (χ2(1) 3.92; p<0.05). At median follow up 61 months, no woman who received radiotherapy had an ipsilateral further event, and only 1/33 women (3.0%) had a contralateral event. Of the women known not to have had radiotherapy post mastectomy, 45/2,894 (1.6%) had an ipsilateral further event and 83 (2.9%) had a contralateral event. Conclusion: For DCIS treated by mastectomy, a close (<1mm) margin, large tumour size and microinvasion, may merit radiotherapy to reduce ipsilateral recurrence

Adjuvant radiotherapy and chemotherapy in breast cancer: 30 year follow-up of survival

BACKGROUND:The long term outcome (more than 15 years) of adjuvant treatment in patients with primary operable breast cancer has rarely been examined.METHODS:A randomised clinical trial of radiotherapy, chemotherapy (28 day cycles of cyclophosphamide, methotrexate and 5-fluorouracil) or both on women with primary operable breast cancer (n = 322) was followed-up for a median of 27 years.RESULTS:260 (81%) patients died, 204 (78%) from breast cancer. Cancer specific survival (SE) at 10 years, 20 years and 30 years was 41 (3)%, 34 (3)% and 33 (3)% respectively. Presence of more than 3 involved lymph nodes increased cancer-specific mortality (HR 1.88, 95% CI 1.34-2.63) after adjustment for age, socio-economic deprivation and adjuvant treatment. Both age (HR 1.63, 95% CI 1.19-2.22) and involved lymph nodes (HR 1.59, 95% CI 1.17-2.14) were significant predictors of all-cause mortality after adjustment for other factors. There was no significant difference in all-cause or cancer-specific survival between patients in each of the 3 treatment arms.CONCLUSIONS:The present study highlights the long term impact of node positive disease but does not indicate that any regimen was associated with significantly better long-term surviva

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Introduction The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Methods Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Results Differences in overall actual and predicted mortality were <1% at eight years for ECRIC (18.9% vs. 19.0%) and WMCIU (17.5% vs. 18.3%) with area under receiver-operator-characteristic curves (AUC) of 0.81 and 0.79 respectively. Differences in breast cancer specific actual and predicted mortality were <1% at eight years for ECRIC (12.9% vs. 13.5%) and <1.5% at eight years for WMCIU (12.2% vs. 13.6%) with AUC of 0.84 and 0.82 respectively. Model calibration was good for both ER positive and negative models although the ER positive model provided better discrimination (AUC 0.82) than ER negative (AUC 0.75). Conclusions We have developed a prognostication model for early breast cancer based on UK cancer registry data that predicts breast cancer survival following surgery for invasive breast cancer and includes mode of detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort

Classifying breast cancer surgery: a novel, complexity-based system for oncological, oncoplastic and reconstructive procedures, and proof of principle by analysis of 1225 operations in 1166 patients

<p>Abstract</p> <p>Background</p> <p>One of the basic prerequisites for generating evidence-based data is the availability of classification systems. Attempts to date to classify breast cancer operations have focussed on specific problems, e.g. the avoidance of secondary corrective surgery for surgical defects, rather than taking a generic approach.</p> <p>Methods</p> <p>Starting from an existing, simpler empirical scheme based on the complexity of breast surgical procedures, which was used in-house primarily in operative report-writing, a novel classification of ablative and breast-conserving procedures initially needed to be developed and elaborated systematically. To obtain proof of principle, a prospectively planned analysis of patient records for all major breast cancer-related operations performed at our breast centre in 2005 and 2006 was conducted using the new classification. Data were analysed using basic descriptive statistics such as frequency tables.</p> <p>Results</p> <p>A novel two-type, six-tier classification system comprising 12 main categories, 13 subcategories and 39 sub-subcategories of oncological, oncoplastic and reconstructive breast cancer-related surgery was successfully developed. Our system permitted unequivocal classification, without exception, of all 1225 procedures performed in 1166 breast cancer patients in 2005 and 2006.</p> <p>Conclusion</p> <p>Breast cancer-related surgical procedures can be generically classified according to their surgical complexity. Analysis of all major procedures performed at our breast centre during the study period provides proof of principle for this novel classification system. We envisage various applications for this classification, including uses in randomised clinical trials, guideline development, specialist surgical training, continuing professional development as well as quality of care and public health research.</p

Global collaborative networks on meta-analyses of randomized trials published in high impact factor medical journals: a social network analysis

BackgroundResearch collaboration contributes to the advancement of knowledge by exploiting the results of scientific efforts more efficiently, but the global patterns of collaboration on meta-analysis are unknown. The purpose of this research was to describe and characterize the global collaborative patterns in meta-analyses of randomized trials published in high impact factor medical journals over the past three decades.MethodsThis was a cross-sectional, social network analysis. We searched PubMed for relevant meta-analyses of randomized trials published up to December 2012. We selected meta-analyses (including at least randomized trials as primary evidence source) published in the top seven high impact factor general medical journals (according to Journal Citation Reports 2011): The New England Journal of Medicine, The Lancet, the BMJ, JAMA, Annals of Internal Medicine, Archives of Internal Medicine (now renamed JAMA Internal Medicine), and PLoS Medicine. Opinion articles, conceptual papers, narrative reviews, reviews without meta-analysis, reviews of reviews, and other study designs were excluded.ResultsOverall, we included 736 meta-analyses, in which 3,178 authors, 891 institutions, and 51 countries participated. The BMJ was the journal that published the greatest number of articles (39%), followed by The Lancet (18%), JAMA (15%) and the Archives of Internal Medicine (15%). The USA, the UK, and Canada headed the absolute global productivity ranking in number of papers. The 64 authors and the 39 institutions with the highest publication rates were identified. We also found 82 clusters of authors (one group with 55 members and one group with 54 members) and 19 clusters of institutions (one major group with 76 members). The most prolific authors were mainly affiliated with the University of Oxford (UK), McMaster University (Canada), and the University of Bern (Switzerland).ConclusionsOur analysis identified networks of authors, institutions and countries publishing meta-analyses of randomized trials in high impact medical journals. This valuable information may be used to strengthen scientific capacity for collaboration and to help to promote a global agenda for future research of excellence

Phosphorylated c-Src in the nucleus is associated with improved patient outcome in ER-positive breast cancer

Elevated c-Src protein expression has been shown in breast cancer and &lt;i&gt;in vitro&lt;/i&gt; evidence suggests a role in endocrine resistance. To investigate whether c-Src is involved in endocrine resistance, we examined the expression of both total and activated c-Src in human breast cancer specimens from a cohort of oestrogen receptor (ER)-positive tamoxifen-treated breast cancer patients. Tissue microarray technology was employed to analyse 262 tumour specimens taken before tamoxifen treatment. Immunohistochemistry using total c-Src and activated c-Src antibodies was performed. Kaplan–Meier survival curves were constructed and log-rank test were performed. High level of nuclear activated Src was significantly associated with improved overall survival (&lt;i&gt;P&lt;/i&gt;=0.047) and lower recurrence rates on tamoxifen (&lt;i&gt;P&lt;/i&gt;=0.02). Improved patient outcome was only seen with activated Src in the nucleus. Nuclear activated Src expression was significantly associated with node-negative disease and a lower NPI (&lt;i&gt;P&lt;/i&gt;&#60;0.05). On subgroup analysis, only ER-positive/progesterone receptor (PgR)-positive tumours were associated with improved survival (&lt;i&gt;P&lt;/i&gt;=0.004). This shows that c-Src activity is increased in breast cancer and that activated Src within the nucleus of ER-positive tumours predicts an improved outcome. In ER/PgR-positive disease, activated Src kinase does not appear to be involved in &lt;i&gt;de novo&lt;/i&gt; endocrine resistance. Further study is required in ER-negative breast cancer as this may represent a cohort in which it is associated with poor outcome

Prediction of higher mortality reduction for the UK Breast Screening Frequency Trial: A model-based approach on screening intervals

Background: The optimal interval between two consecutive mammograms is uncertain. The UK Frequency Trial did not show a significant difference in breast cancer mortality between screening every year (study group) and screening every 3 years (control group). In this study, the trial is simulated in order to gain insight into the results of the trial and to predict the effect of different screening intervals on breast cancer mortality. Methods: UK incidence, life tables and information from the trial were used in the microsimulation model MISCAN-Fadia to simulate the trial and predict the number of breast ca