TY  - JOUR
AU  - Lánczky, András
AU  - Győrffy, Balázs
PY  - 2021
DA  - 2021/7/26
TI  - Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation
JO  - J Med Internet Res
SP  - e27633
VL  - 23
IS  - 7
KW  - Kaplan-Meier plot
KW  - internet
KW  - Cox regression
KW  - follow-up
KW  - multivariate analysis
KW  - survival
AB  - Background: 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. Objective: 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. Methods: 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. Results: We established a registration-free web-based survival analysis tool capable of performing univariate and multivariate survival analysis using any custom-generated data. Conclusions: This tool fills a gap and will be an invaluable contribution to basic medical and clinical research. 
SN  - 1438-8871
UR  - https://www.jmir.org/2021/7/e27633
UR  - https://doi.org/10.2196/27633
UR  - http://www.ncbi.nlm.nih.gov/pubmed/34309564
DO  - 10.2196/27633
ID  - info:doi/10.2196/27633
ER  -