Age- and Tumor Subtype-Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers.

PURPOSE: CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. PATIENTS AND METHODS: CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. RESULTS: Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. CONCLUSION: These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.NIH

International day of radiology : breast imaging

November 8, 2016, is the International Day of Radiology (IDoR), which is dedicated to breast imaging and the essential role that radiology plays in the detection, diagnosis, and management of diseases of the breast (http://www.internationaldayofradiology.com). On the website, you can find the book to honour the International Day of Radiology, Screening & Beyond, which provides an amazing overview of breast imaging, with contributions from many of the world’s top breast radiologists

Breast imaging surveillance after curative treatment for primary non-metastasised breast cancer in non-high-risk women: a systematic review

OBJECTIVES: The article summarises the available guidelines on breast imaging surveillance after curative treatment for locoregional breast cancer. METHODS: A systematic review of practice guidelines published from 1 January 2007 to 1 January 2017 was performed according to PRISMA methodology. The search was conducted for the EMBASE, MEDLINE, Cochrane and Centre for Reviews and Dissemination databases. On 8 July 2018, all included guidelines were updated to the most recent version. RESULTS: Twenty-one guidelines originating from 18 publishing bodies matched criteria. Publishing bodies consisted of seven governmental institutions, nine medical societies and two mixed collaborations. Publishing boards consisted of six radiological, four oncological, and 11 multidisciplinary teams. Annual bilateral mammography surveillance after breast-conserving therapy was recommended by 17/18 (94.4%) publishing bodies. Annual contralateral mammography surveillance after mastectomy was recommended by 13/18 (72.2%) publishing bodies. Routine use of digital breast tomosynthesis was recommended by 1/18 (5.6%) publishing bodies. Routine breast ultrasound surveillance was recommended by 2/18 (11.1%), deemed optional by 4/18 (22.2%) and not supported by 8/18 (44.4%) publishing bodies. Routine breast magnetic resonance imaging (MRI) surveillance was not recommended by 16/18 (88.9%) publishing bodies, although 6/18 (33.3%) specified subgroups for systematic MRI surveillance. CONCLUSIONS: Annual mammography is currently the 'gold standard' for breast imaging surveillance. The role of digital breast tomosynthesis (DBT) remains to be further investigated. Most guidelines do not recommend routine breast ultrasound or MRI surveillance, unless indicated by additional risk factors.status: publishe

Loopbaanbegeleiding in bedrijfscontext: de rol van organisatie, individu en overheid

status: publishe

Prediction of non-sentinel lymph node involvement in breast cancer patients with a positive sentinel lymph node

Completion axillary lymph node dissection (cALND) is the golden standard if breast cancer involves the sentinel lymph node (SLN). However, most non-sentinel lymph nodes (NSLN) are not involved, cALND has a considerable complication rate and does not improve outcome. We here present and validate our predictive model for positive NSLNs in the cALND if the SLN is positive. Consecutive early breast cancer patients from one center undergoing cALND for a positive SLN were included. We assessed demographic and clinicopathological variables for NSLN involvement. Uni- and multivariate analysis was performed. A predictive model was built and validated in two external centers. 21.9% of 470 patients had at least one involved NSLN. In univariate analysis, seven variables were significantly correlated with NSLN involvement: tumor size, grade, lymphovascular invasion (LVI), number of positive and negative SLNs, size of SLN metastasis and intraoperative positive SLN. In multivariate analysis, LVI, number of negative SLNs, size of SLN metastasis and intraoperative positive pathological evaluation were independent predictors for NSLN involvement. The calculated risk resulted in an AUC of 0.76. Applied to the external data, the model was accurate and discriminating for one (AUC = 0.75) and less for the other center (AUC = 0.58). A discriminative predictive model was constructed to calculate the risk of NSLN involvement in case of a positive SLN. External validation of our model reveals differences in performance when applied to data from other institutions concluding that such a predictive model requires validation prior to use. (C) 2014 Elsevier Ltd. All rights reserve