Web-based survival analysis tool tailored for medical research (KMplot): Development and implementation
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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.
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- Authors
- Lánczky, A., & Győrffy, B.
- Affiliations
- Semmelweis University (HU)
- Corresponding author
- Győrffy, Balázs
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2021-07-26
- Volume
- 23
- Issue
- 7
- Pages
- e27633
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC8367126
- OpenAlex
- W3162350134
- Cited by
- 1,694
- References
- 26
- Citations by year
- 2026: 134 · 2025: 235 · 2024: 383 · 2023: 578 · 2022: 356 · 2021: 8
- FWCI
- 107.02
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Semmelweis Egyetem (2020-4.1.1.-TKP2020, TKP2020)
- Innovációs és Technológiai Minisztérium (2020.1.16-Jövő-2021-00013, 2020-4.1.1-TKP2020, TKP2020, 2018-2.1.17-TET-KR-00001, 2018-1.3.1-VKE-2018-00032)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- survival analysis, Cox proportional hazards model, web-based tool, omics data, multivariate survival analysis, false discovery rate, clinical outcome prediction, bioinformatics software
- MeSH terms
- Humans, Software, Survival Analysis, Internet, Biomedical Research, Proteomics
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