Abstract
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.
Keywords
UnivariateWeb applicationMultivariate analysisComputer scienceMultivariate statisticsProportional hazards modelData miningSurvival analysisData scienceMedicineWorld Wide WebMachine learningInternal medicine
MeSH Terms
Biomedical ResearchHumansInternetProteomicsSoftwareSurvival Analysis
Affiliated Institutions
Related Publications
Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis
Abstract MetaboAnalyst (https://www.metaboanalyst.ca) is an easy‐to‐use web‐based tool suite for comprehensive metabolomic data analysis, interpretation, and integration with ot...
Independent prognostic significance of a nuclear proliferation antigen in diffuse large cell lymphomas as determined by the monoclonal antibody Ki-67
Abstract To assess the prognostic significance of the growth fraction in diffuse large cell lymphoma (DLCL), we studied 105 DLCL patients with the monoclonal antibody Ki-67 appl...
Establishing Reporting Standards for Metabolomic and Metabonomic Studies: A Call for Participation
Metabolite concentrations in cellular systems are very much dependent on the physiological, environmental, and genetic status of an organism and are regarded as the ultimate res...
IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures
Recent advances in next-generation sequencing (NGS) technologies have triggered the rapid accumulation of publicly available multi-omics datasets. The application of integrated ...
Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer
Extensive research is directed to uncover new biomarkers capable to stratify breast cancer patients into clinically relevant cohorts. However, the overall performance ranking of...
Publication Info
- Year
- 2021
- Type
- article
- Volume
- 23
- Issue
- 7
- Pages
- e27633-e27633
- Citations
- 1690
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
1690
OpenAlex
58
Influential
1250
CrossRef
Cite This
András Lánczky,
Balázs Győrffy
(2021).
Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation.
Journal of Medical Internet Research
, 23
(7)
, e27633-e27633.
https://doi.org/10.2196/27633
Identifiers
- DOI
- 10.2196/27633
- PMID
- 34309564
- PMCID
- PMC8367126