American Cancer Society; Centers for Disease Control and Prevention; Swiss Re; Swiss Cancer Research foundation; Swiss Cancer League; Institut National du Cancer; La Ligue Contre le Cancer; Rossy Family Foundation; US National Cancer Institute; and the Susan G Komen Foundation.

Background Rare cancers here defined as those with an annual incidence rate less than 6/100,000 in Europe, pose challenges for diagnosis, treatments, and clinical decision-making. Information on rare cancers is scant. We updated the estimates of the burden of rare cancers in Europe, their time trends in incidence and survival, and provide information on centralization of treatments in seven European countries. Methods We analysed data on more than two million rare cancer diagnoses, provided by 83 cancer registries, to estimate European incidence and survival in 2000-2007 and the corresponding time trends during 1995-2007. Incidence rates were calculated as the number of new cases divided by the corresponding total person years in the population. Five-year relative survival (RS) was calculated by the Ederer-2 method. Seven registries

This prospective study confirms that OLGA staging reliably predicts the risk for development of gastric epithelial neoplasia. Although no neoplastic lesions arose in naïve patients, the eradication in subjects with advanced stages (III-IV) did not abolish the risk for neoplastic progression.

Breast radiological density is a determinant of breast cancer risk and of mammography sensitivity and may be used to personalize screening approach. We first analyzed the reproducibility of visual density assessment by eleven experienced radiologists classifying a set of 418 digital mammograms: reproducibility was satisfactory on a four (BI-RADS D1-2-3-4: weighted kappa = 0.694-0.844) and on a two grade (D1-2 vs D3-4: kappa = 0.620-0.851), but subjects classified as with dense breast would range between 25.1 and 50.5% depending on the classifying reader. Breast density was then assessed by computer using the QUANTRA software which provided systematically lower density percentage values as compared to visual classification. In order to predict visual classification results in discriminating dense and non-dense breast subjects on a two grade scale (D3-4 vs, D1-2) the best fitting cut off value observed for QUANTRA was ≤22.0%, which correctly predicted 88.6% of D1-2, 89.8% of D3-4, and 89.0% of total cases. Computer assessed breast density is absolutely reproducible, and thus to be preferred to visual classification. Thus far few studies have addressed the issue of adjusting computer assessed density to reproduce visual classification, and more similar comparative studies are needed.

The distribution of ovarian cancer histology varies widely worldwide. Type I epithelial, germ cell and sex cord-stromal tumours are generally associated with higher survival than type II tumours, so the proportion of these tumours may influence survival estimates for all ovarian cancers combined. The distribution of histological groups should be considered when comparing survival between countries and regions.