The Probability of Being in Response Function and Its Applications
Wei Yann Tsai (),
Xiaodong Luo () and
John Crowley ()
Additional contact information
Wei Yann Tsai: Columbia University, Department of Biostatistics
Xiaodong Luo: Sanofi, Research and Development
John Crowley: Cancer Research and Biostatistics
A chapter in Frontiers of Biostatistical Methods and Applications in Clinical Oncology, 2017, pp 151-164 from Springer
Abstract:
Abstract Cancer clinical trials usually have two or more types of related clinical events (i.e. response, progression and relapse). Hence, to compare treatments, efficacy is often measured using composite endpoints. Temkin (Biometrics 34: 571–580, [18]) proposed the probability of being in response as a function of time (PBRF) to analyze composite endpoints. The PBRF is a measure which considers the response rate and the duration of response jointly. In this article, we develop, study and propose estimators of PBRF based on multi-state survival data.
Keywords: Probability of being in response function; Nonparametric estimation (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-10-0126-0_10
Ordering information: This item can be ordered from
http://www.springer.com/9789811001260
DOI: 10.1007/978-981-10-0126-0_10
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().