Novel R Shiny Tool for Survival Analysis With Time-Varying Covariate in Oncology Studies: Overcoming Biases and Enhancing Collaboration
We recommend TD Cox models and Smith-Zee curves for robust TVC analysis. Our R Shiny tool supports standardized analyses without requiring data sharing, thereby promoting collaboration across different institutions and providing a practical tool to advance survival analysis in oncology research.
Authors
- Jordan Gauthier (ORCID: https://orcid.org/0000-0002-5769-8409)
- Ted Alan Gooley (ORCID: https://orcid.org/0000-0002-8182-3652)
- Qian Wu (ORCID: https://orcid.org/0000-0002-2292-4816)
- Yimei B. Li
- Alexandre V. Hirayama (ORCID: https://orcid.org/0000-0001-7980-3882)
- Q. Zhang
- Jenna Voutsinas (ORCID: https://orcid.org/0000-0002-7474-4892)
- Corinne Summers (ORCID: https://orcid.org/0000-0003-1769-7388)
- Cameron J. Turtle (ORCID: https://orcid.org/0000-0002-4722-4461)
- Rebecca Gardner
- Yang Qiao
- Fei Gao
- Wendy Leisenring
- Jarcy Zee
Institutions
- Seattle Children's Hospital (US)
- The University of Sydney (AU)
- St. Jude Children's Research Hospital (US)
- Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa (ZA)
- Thomas Jefferson University (US)
- Iowa State University (US)
- Royal North Shore Hospital (AU)
- Fred Hutch Cancer Center (US)
- University of Pennsylvania (US)
- Wills Eye Hospital (US)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2026-01-30
- DOI
- https://doi.org/10.1200/cci-25-00225
- Primary Topic
- Statistical Methods and Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00