Clinically apparent haematomas are among most frequent complications after vacuum-assisted breast biopsy (VABB). We evaluated the prevalence and persistence of sonographically (US) detected haematomas and other tissue changes at the biopsy site after VABB.The changes at the biopsy site can be seen by US in most of the patients one and three weeks after the VABB. These changes could potentially be used for US guidance and localisation of microcalcifications in patients requiring surgical biopsy.
COBISS.SI-ID: 694907
Common variants within the 9p21 locus have not previously been associated with melanoma. Despite wide variation in allele frequency, these genetic variants show notable homogeneity of effect across populations of European ancestry living at different latitudes and show independent association to disease risk.
COBISS.SI-ID: 892539
Multinational case-only study tested the interaction between oral contraceptive use and genetic susceptibility in the occurrence of breast cancer. Participants were classified according to their probability of carrying a BRCA mutation on the basis of their family history of breast and ovarian cancer. These results suggest that BRCA mutation carriers, as well as women with a significant family history of breast and ovarian cancer are more vulnerable to exogenous hormones in oral contraceptives.
COBISS.SI-ID: 795259
Cardiac toxicity is an important late effect after anthracycline treatment . We hypothesized that deactivating variants of superoxide dismutase II may increase the risk of developing cardiac toxicity, in patients exposed to anthracyclines. The hypothesis was tested in a cohort of 76 long-term survivals of acute lymphoblastic leukemia in childhood. In our study group, we show statistically significant correlation between CC homozygosity for CAT (rs10836235 (c.66 + 78C ) T)) and cardiac damage after anthracycline exposure (p = 0.020).
COBISS.SI-ID: 2622577
In this paper, we describe the first practical application of two methods, which bridge the gap between the non-expert user and machine learning models. 1. method for explaining classifiers’ predictions, 2. a reliability estimation methodology for regression predictions, which helps the users to decide to what extent to trust a particular prediction. Both methods are successfully applied to a novel breast cancer recurrence prediction data set and the results are evaluated by expert oncologists.
COBISS.SI-ID: 7555668