Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jclinepi.2008.12.004 | DOI Listing |
BMJ Open
January 2025
Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran (the Islamic Republic of).
Objectives: Microbial threats pose a growing concern worldwide. This paper reports the analysis of Iran's policy process against microbial threats.
Design: This is a qualitative study.
Accid Anal Prev
January 2025
School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK.
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technologies face significant challenges in handling spatiotemporal data and multi-feature fusion, including difficulties in big data processing, and have room for improvement in these areas. To address these issues, this paper proposes a novel method that combines autoencoders, Mahalanobis distance, and dynamic Bayesian networks for anomaly detection.
View Article and Find Full Text PDFMol Biol Rep
January 2025
Department of Neuromuscular Disorders, UCL Queen Square Institute of Neurology, Queen Square House, London, WC1N 3BG, UK.
Background: Male EBP disorder with neurologic defects (MEND syndrome) is an extremely rare disorder with a prevalence of less than 1/1,000,000 individuals worldwide. It is inherited as an X-linked recessive disorder caused by impaired sterol biosynthesis due to nonmosaic hypomorphic EBP variants. MEND syndrome is characterized by variable clinical manifestations including intellectual disability, short stature, scoliosis, digital abnormalities, cataracts, and dermatologic abnormalities.
View Article and Find Full Text PDFTrials
January 2025
MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, 90 High Holborn, London, WC1V 6LJ, UK.
Need For A Strategic Approach To Knowledge Transfer And Exchange: Late-phase clinical trials and systematic reviews find results that have the potential to improve health outcomes for people. However, there are often delays in these results influencing clinical practice. We developed a knowledge transfer and exchange strategy to support research teams, aiming to identify activities along the research process to maximise and accelerate the research impact.
View Article and Find Full Text PDFJ Neurooncol
January 2025
Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans St, Baltimore, MD, 21287, USA.
Purpose: Social determinants of health including neighborhood socioeconomic status, have been established to play a profound role in overall access to care and outcomes in numerous specialized disease entities. To provide glioblastoma multiforme (GBM) patients with high-quality care, it is crucial to identify predictors of hospital length of stay (LOS), discharge disposition, and access to postoperative adjuvant chemoradiation. In this study, we incorporate a novel neighborhood socioeconomic status index (NSES) and develop three predictive algorithms for assessing post-operative outcomes in GBM patients, offering a tool for preoperative risk stratification of GBM patients.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!