Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Eur J Hum Genet. 2011 Aug;19(8):833-6. doi: 10.1038/ejhg.2011.25. Epub 2011 Mar 16.
The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but the quality and completeness of reporting varies. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies, building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct, or analysis. A detailed Explanation and Elaboration document is published on the EJHG website.
基因发现技术在复杂疾病领域的快速持续进步,激发了人们对于遗传风险模型在临床和公共卫生实践中潜在应用的兴趣。评估预测能力的研究数量在稳步增加,但报告的质量和完整性却存在差异。人类基因组流行病学网络(HuGE)组织的一次多学科研讨会,基于先前报告准则所确立的原则,提出了一份 25 项项目的清单,以加强遗传风险预测研究的报告。这些建议旨在提高研究报告的透明度,从而促进对可能在设计、实施或分析方面存在差异的多项研究信息的综合和应用。详细的解释和说明文件发布在 EJHG 网站上。