Bayesian group sequential clinical trial design using total toxicity burden and progression-free survival
Brian P. Hobbs,
Peter F. Thall and
Steven H. Lin
Journal of the Royal Statistical Society Series C, 2016, vol. 65, issue 2, 273-297
Abstract:
type="main" xml:id="rssc12117-abs-0001">
Delivering radiation to eradicate a solid tumour while minimizing damage to nearby critical organs remains a challenge. For oesophageal cancer, radiation therapy may damage the heart or lungs, and several qualitatively different, possibly recurrent toxicities that are associated with chemoradiation or surgery may occur, each at two or more possible grades. We describe a Bayesian group sequential clinical trial design, based on total toxicity burden (TTB) and the duration of progression-free survival, for comparing two radiation therapy modalities for oesophageal cancer. Each patient's toxicities are modelled as a multivariate doubly stochastic Poisson point process, with marks identifying toxicity grades. Each grade of each type of toxicity is assigned a severity weight, elicited from clinical oncologists who are familiar with the disease and treatments. TTB is defined as a severity-weighted sum over the different toxicities that may occur up to 12 months from the start of treatment. Latent frailties are used to formulate a multivariate model for all outcomes. Group sequential decision rules are based on posterior mean TTB and progression-free survival time. The design proposed is shown to provide both larger power and smaller mean sample size when compared with a conventional bivariate group sequential design.
Date: 2016
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1111/rssc.2016.65.issue-2 (text/html)
Access to full text is restricted to subscribers.
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:bla:jorssc:v:65:y:2016:i:2:p:273-297
Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876
Access Statistics for this article
Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith
More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().