Lánczky András, Győrffy Balázs
Department of Bioinformatics, Semmelweis University, Budapest, Hungary.
TTK Lendület Cancer Biomarker Research Group, Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Hungary.
J Med Internet Res. 2021 Jul 26;23(7):e27633. doi: 10.2196/27633.
Survival analysis is a cornerstone of medical research, enabling the assessment of clinical outcomes for disease progression and treatment efficiency. Despite its central importance, no commonly used spreadsheet software can handle survival analysis and there is no web server available for its computation.
Here, we introduce a web-based tool capable of performing univariate and multivariate Cox proportional hazards survival analysis using data generated by genomic, transcriptomic, proteomic, or metabolomic studies.
We implemented different methods to establish cut-off values for the trichotomization or dichotomization of continuous data. The false discovery rate is computed to correct for multiple hypothesis testing. A multivariate analysis option enables comparing omics data with clinical variables.
We established a registration-free web-based survival analysis tool capable of performing univariate and multivariate survival analysis using any custom-generated data.
This tool fills a gap and will be an invaluable contribution to basic medical and clinical research.
生存分析是医学研究的基石，能够评估疾病进展的临床结局和治疗效果。尽管其至关重要，但常用的电子表格软件都无法处理生存分析，也没有可用于其计算的网络服务器。
在此，我们介绍一种基于网络的工具，它能够使用基因组、转录组、蛋白质组或代谢组学研究生成的数据进行单变量和多变量Cox比例风险生存分析。
我们采用不同方法为连续数据的三分法或二分法确定截断值。计算错误发现率以校正多重假设检验。多变量分析选项可将组学数据与临床变量进行比较。
我们建立了一个无需注册的基于网络的生存分析工具，该工具能够使用任何自定义生成的数据进行单变量和多变量生存分析。
此工具填补了一项空白，将为基础医学和临床研究做出宝贵贡献。
