DoSurvive: A webtool for investigating the prognostic power of a single or combined cancer biomarker

Hao Wei Wu, Jian De Wu, Yen Ping Yeh, Timothy H. Wu, Chi Hong Chao, Weijing Wang, Ting Wen Chen*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review


We present DoSurvive, a user-friendly survival analysis web tool and a cancer prognostic biomarker centered database. DoSurvive is the first database that allows users to perform multivariant survival analysis for cancers with customized gene/patient list. DoSurvive offers three survival analysis methods, Log rank test, Cox regression and accelerated failure time model (AFT), for users to analyze five types of quantitative features (mRNA, miRNA, lncRNA, protein and methylation of CpG islands) with four survival types, i.e. overall survival, disease-specific survival, disease-free interval, and progression-free interval, in 33 cancer types. Notably, the implemented AFT model provides an alternative method for genes/features which failed the proportional hazard assumption in Cox regression. With the unprecedented number of survival models implemented and high flexibility in analysis, DoSurvive is a unique platform for the identification of clinically relevant targets for cancer researcher and practitioners. DoSurvive is freely available at

Original languageEnglish
Article number107269
Pages (from-to)107269
Issue number8
StatePublished - 18 08 2023
Externally publishedYes

Bibliographical note

© 2023 The Author(s).


  • Cancer systems biology
  • Epigenetics
  • Proteomics
  • Transcriptomics


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