for first and second ER-positive and ER-negative BCs ranged between 0.73 and 0.82.Conclusions:ThePREDICTtool largely underestimated the 5-year BC-specific mortality in women diagnosed with a second ER-positive breast cancer and in many subgroups of women diagnosed with a second ER-negative cancer...
PREDICT is a widely used online prognostication and treatment benefit tool for patients with early stage breast cancer. The aim of this study was to conduct an independent validation exercise of the most up-to-date version of the PREDICT algorithm (version 2) using real-world outcomes from the...
LONDON, March 15 (Xinhua) -- Scientists have been trying to better predict if and when women's breast cancer could come back using statistical tools. A team consisting of researchers from the University of Cambridge and Stanford University has examined the patterns of genetic changes within tumour...
We assessed the PREDICT v 2.2 for prognosis of breast cancer patients with pathogenic germline BRCA1 and BRCA2 variants, using follow-up data from 5453 BRCA1/2 carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast C
A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation i... Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aime...
PREDICT Breast (www.breast .predict.nhs.uk) is a prognostication tool for early invasive breast cancer. The current version was based on cases diagnosed in 1999–2003 and did not incorporate the benefits of radiotherapy or the harms associated with therapy. Since then, there has been a substant...
An image-based risk prediction model using digital breast tomosynthesis (DBT) can predict the risk for breast cancer after a negative screening exam, according to a study published in the May 11 issue of Science Translational Medicine.
In an interview with Targeted Oncology™, lead study author Elisa Agostinetto, MD, of the Istituto Clinico Humanitas in Rozzano, Milan, Italy, discussed the accuracy of PREDICT+ in HER2-positive breast cancer in greater detail and its clinical implicat
to identify never before seen gene variants and mutations in various diseases, including cancer, by pitting computers against huge data sets. Andlast year15-year-old Nathan Han won an Intel prize for his machine learning tool that studies mutations of a particular gene linked to breast cancer. ...
Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors. Methods We included data from 207,510 invasive...