Purpose: Several genes on hereditary breast and ovarian cancer susceptibility test panels have not been systematically examined for strength of association with disease. We employed the Clinical Genome Resource (ClinGen) clinical validity framework to assess the strength of evidence between selected genes and breast or ovarian cancer.
Methods: Thirty-one genes offered on cancer panel testing were selected for evaluation. The strength of gene-disease relationship was systematically evaluated and a clinical validity classification of either Definitive, Strong, Moderate, Limited, Refuted, Disputed, or No Reported Evidence was assigned.
Results: Definitive clinical validity classifications were made for 10/31 and 10/32 gene-disease pairs for breast and ovarian cancer respectively. Two genes had a Moderate classification whereas, 6/31 and 6/32 genes had Limited classifications for breast and ovarian cancer respectively. Contradictory evidence resulted in Disputed or Refuted assertions for 9/31 genes for breast and 4/32 genes for ovarian cancer. No Reported Evidence of disease association was asserted for 5/31 genes for breast and 11/32 for ovarian cancer.
Conclusion: Evaluation of gene-disease association using the ClinGen clinical validity framework revealed a wide range of classifications. This information should aid laboratories in tailoring appropriate gene panels and assist health-care providers in interpreting results from panel testing.
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http://dx.doi.org/10.1038/s41436-018-0361-5 | DOI Listing |
J Med Internet Res
January 2025
Department of Radiation Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Background: Primary intracranial germ cell tumors (iGCTs) are highly malignant brain tumors that predominantly occur in children and adolescents, with an incidence rate ranking third among primary brain tumors in East Asia (8%-15%). Due to their insidious onset and impact on critical functional areas of the brain, these tumors often result in irreversible abnormalities in growth and development, as well as cognitive and motor impairments in affected children. Therefore, early diagnosis through advanced screening techniques is vital for improving patient outcomes and quality of life.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Gastroenterology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.
Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.
PLoS One
January 2025
Department of Radiation Physics, Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
Accurate and efficient automatic segmentation is essential for various clinical tasks such as radiotherapy treatment planning. However, atlas-based segmentation still faces challenges due to the lack of representative atlas dataset and the computational limitations of deformation algorithms. In this work, we have proposed an atlas selection procedure (subset atlas grouping approach, MAS-SAGA) which utilized both image similarity and volume features for selecting the best-fitting atlases for contour propagation.
View Article and Find Full Text PDFPLoS One
January 2025
Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, PR. China.
Objectives: The aim of this study was to develop and validate a nomogram model that predicts the risk of bone metastasis (BM) in a prostate cancer (PCa) population.
Methods: We retrospectively collected and analyzed the clinical data of patients with pathologic diagnosis of PCa from January 1, 2013 to December 31, 2022 in two hospitals in Yangzhou, China. Patients from the Affiliated Hospital of Yangzhou University were divided into a training set and patients from the Affiliated Clinical College of Traditional Chinese Medicine of Yangzhou University were divided into a validation set.
PLoS One
January 2025
Health Promotion Sciences Department, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, United States of America.
The complex healthcare system in the United States (US) poses significant challenges for people, particularly minorities such as refugees. Refugees often encounter additional layers of challenges to healthcare navigation due to unfamiliarity with the system, limited health literacy, and language barriers. Despite their challenges, it is difficult to identify the gaps as few tools exist to measure navigation competency among this population and many conventional tools assume English proficiency, making them inadequate for refugees and other immigrants.
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