Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1999-6-9
pubmed:abstractText
The interest in estimating the probability of cure has been increasing in cancer survival analysis as the curability of many cancer diseases is becoming a reality. Mixture survival models provide a way of modelling time to death when cure is possible, simultaneously estimating death hazard of fatal cases and the proportion of cured case. In this paper we propose an application of a parametric mixture model to relative survival rates of colon cancer patients from the Finnish population-based cancer registry, and including major survival determinants as explicative covariates. Disentangling survival into two different components greatly facilitates the analysis and the interpretation of the role of prognostic factors on survival patterns. For example, age plays a different role in determining, from one side, the probability of cure, and, from the other side, the life expectancy of fatal cases. The results support the hypothesis that observed survival trends are really due to a real prognostic gain for more recently diagnosed patients.
pubmed:keyword
http://linkedlifedata.com/resource/pubmed/keyword/Age Factors, http://linkedlifedata.com/resource/pubmed/keyword/Cancer, http://linkedlifedata.com/resource/pubmed/keyword/Causes Of Death, http://linkedlifedata.com/resource/pubmed/keyword/Demographic Factors, http://linkedlifedata.com/resource/pubmed/keyword/Developed Countries, http://linkedlifedata.com/resource/pubmed/keyword/Diseases, http://linkedlifedata.com/resource/pubmed/keyword/Europe, http://linkedlifedata.com/resource/pubmed/keyword/FINLAND, http://linkedlifedata.com/resource/pubmed/keyword/LIFE EXPECTANCY, http://linkedlifedata.com/resource/pubmed/keyword/Length Of Life, http://linkedlifedata.com/resource/pubmed/keyword/Models, Theoretical, http://linkedlifedata.com/resource/pubmed/keyword/Mortality, http://linkedlifedata.com/resource/pubmed/keyword/Neoplasms, http://linkedlifedata.com/resource/pubmed/keyword/Northern Europe, http://linkedlifedata.com/resource/pubmed/keyword/Population, http://linkedlifedata.com/resource/pubmed/keyword/Population Characteristics, http://linkedlifedata.com/resource/pubmed/keyword/Population Dynamics, http://linkedlifedata.com/resource/pubmed/keyword/Research Methodology, http://linkedlifedata.com/resource/pubmed/keyword/Scandinavia, http://linkedlifedata.com/resource/pubmed/keyword/Survivorship--determinants
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
28
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
441-54
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Mixture models for cancer survival analysis: application to population-based data with covariates.
pubmed:affiliation
Istituto Superiore di Sanità, Laboratory of Epidemiology and Biostatistics, Roma, Italy.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't