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Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.
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http://dx.doi.org/10.1146/annurev-biodatasci-020722-092748 | DOI Listing |
Circ Cardiovasc Interv
September 2025
Keele Cardiovascular Research Group, Keele University, United Kingdom (M.A.M., R.B.).
Background: Evidence informing clinical guidelines assumes that all transcatheter aortic valve implantation (TAVI) devices have similar effectiveness, in other words, displaying a class effect across TAVI valves. We aimed to assess the comparative effectiveness of different TAVI platforms relative to other TAVI counterparts or surgical aortic valve replacement (SAVR).
Methods: MEDLINE/Embase/CENTRAL were searched from inception until April 2025, for randomized controlled trials comparing outcomes with different commercially available TAVI devices relative to other TAVI counterparts or SAVR.
Crit Rev Toxicol
September 2025
Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
There is a concern on the safety of cosmetic ingredients and their endocrine-disrupting (ED) potential. Frequent use as well as the use of a diverse range of cosmetics pose a concern for a potential health risk via aggregate exposure to endocrine disrupting chemicals (EDCs). In this study, a list of ingredients available in cosmetic products that were recently introduced to the Dutch market was retrieved from the commercially accessible Mintel database and screened for the presence of EDCs.
View Article and Find Full Text PDFRev Med Liege
September 2025
Service de Chimie clinique, CHU Liège, Belgique.
Chronic kidney disease (CKD), heart failure (HF) and atherosclerotic cardiovascular disease (ASCVD) are pathologies that may remain silent for a long time and thus are largely underdiagnosed in clinical practice. The use of biomarkers may help detect people already suffering from these diseases at an early stage or at increased risk to develop them in a near future. The aim of this article is to discuss the place of the assays of albuminuria, natriuretic peptide (BNP/proBNP) and high-sensitivity troponin as well as lipoprotein(a) to help in the diagnosis and prognosis assessment of individuals at risk of presenting or developing a CKD, HF or ASCVD.
View Article and Find Full Text PDFJ Dance Med Sci
September 2025
Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
The aim of this study was to propose reference values for the Dynamic Evaluation Method of Lower Limb Joint Alignment (MADAAMI II). During the 2023 Joinville Dance Festival, 346 dancers (315 females and 31 males), aged between 15 and 58 years, with a minimum of 5 years of ballet experience, were randomly evaluated. The dancers were filmed performing the three-step sequence (demi plié, grand plié, and fondu) of the MADAAMI II, in the first foot position, with self-selected turnout and at 120 degrees.
View Article and Find Full Text PDFKnee Surg Relat Res
September 2025
Florida Orthopaedic Institute, Gainesville, FL, 32607, USA.
Background: A clear understanding of minimal clinically important difference (MCID) and substantial clinical benefit (SCB) is essential for effectively implementing patient-reported outcome measurements (PROMs) as a performance measure for total knee arthroplasty (TKA). Since not achieving MCID and SCB may reflect suboptimal surgical benefit, the primary aim of this study was to use machine learning to predict patients who may not achieve the threshold-based outcomes (i.e.
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