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Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation

Journal of medical Internet research, 2021-07, Vol.23 (7), p.e27633-e27633 [Peer Reviewed Journal]

2021. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;András Lánczky, Balázs Győrffy. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.07.2021. 2021 ;ISSN: 1438-8871 ;ISSN: 1439-4456 ;EISSN: 1438-8871 ;DOI: 10.2196/27633 ;PMID: 34309564

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  • Title:
    Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation
  • Author: Lánczky, András ; Győrffy, Balázs
  • Subjects: Analysis ; Clinical assessment ; Clinical outcomes ; Clinical research ; Clinical variables ; Computer based ; Continuous data ; Gene expression ; Hypotheses ; Hypothesis testing ; Internet ; Mathematical functions ; Medical prognosis ; Medical research ; Multivariate analysis ; Original Paper ; Software packages ; Survival analysis ; Variables
  • Is Part Of: Journal of medical Internet research, 2021-07, Vol.23 (7), p.e27633-e27633
  • Description: 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.
  • Publisher: Toronto: Gunther Eysenbach MD MPH, Associate Professor
  • Language: English
  • Identifier: ISSN: 1438-8871
    ISSN: 1439-4456
    EISSN: 1438-8871
    DOI: 10.2196/27633
    PMID: 34309564
  • Source: Geneva Foundation Free Medical Journals at publisher websites
    PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
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