Linked Life Data

15534347

Source:http://linkedlifedata.com/resource/pubmed/id/15534347

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2004-11-9
pubmed:abstractText
Tree-structured survival analysis (TSSA) is a popular alternative to the Cox proportional hazards regression in medical research of survival data. Several methods for constructing a tree of different survival profiles have been developed, including TSSA based on log-rank statistics, martingale residuals, Lp Wasserstein metrics between Kaplan-Meier survival curves, and a method based on a weighted average of the within-node impurity of the death indicator and the within-node loss function of follow-up times. Lu and others used variance of restricted mean lifetimes as an index of degree of separation (DOS) to measure the efficiency in separations of survival profiles by a classification method. Like tree-based regression analysis that uses variance as a criterion for node partition and pruning, the variance of restricted mean lifetimes between different groups can be an alternative index to log-rank test statistics in construction of survival trees. In this article, the authors explore the use of DOS in TSSA. They propose an algorithm similar to the least square regression tree for survival analysis based on the variance of the restricted mean lifetimes. They apply the proposed method to prospective cohort data from the Study of Osteoporotic Fracture that motivated the research and then compare their classification rule to those rules based on the conventional TSSA mentioned above. A limited simulation study suggests that the proposed algorithm is a competitive alternative to the log-rank or martingale residual-based TSSA approaches.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0272-989X
pubmed:author
pubmed:issnType
Print
pubmed:volume
24
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
670-80
pubmed:dateRevised
2011-9-22
pubmed:meshHeading
pubmed:articleTitle
Alternative tree-structured survival analysis based on variance of survival time.
pubmed:affiliation
Department of Radiology, the University of California at San Francisco, San Francisco, CA 94143-0946, USA. ying.lu@radiology.ucsf.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.