A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.
Identifieur interne : 001489 ( Main/Exploration ); précédent : 001488; suivant : 001490A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.
Auteurs : Matthias Schmid [Allemagne] ; Helmut Küchenhoff [Allemagne] ; Achim Hoerauf [Allemagne] ; Gerhard Tutz [Allemagne]Source :
- Statistics in medicine [ 1097-0258 ] ; 2016.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- statistics & numerical data : Risk Assessment.
- Algorithms, Epidemiologic Studies, Humans, Models, Statistical, Regression Analysis, Survival Analysis.
Abstract
Survival trees are a popular alternative to parametric survival modeling when there are interactions between the predictor variables or when the aim is to stratify patients into prognostic subgroups. A limitation of classical survival tree methodology is that most algorithms for tree construction are designed for continuous outcome variables. Hence, classical methods might not be appropriate if failure time data are measured on a discrete time scale (as is often the case in longitudinal studies where data are collected, e.g., quarterly or yearly). To address this issue, we develop a method for discrete survival tree construction. The proposed technique is based on the result that the likelihood of a discrete survival model is equivalent to the likelihood of a regression model for binary outcome data. Hence, we modify tree construction methods for binary outcomes such that they result in optimized partitions for the estimation of discrete hazard functions. By applying the proposed method to data from a randomized trial in patients with filarial lymphedema, we demonstrate how discrete survival trees can be used to identify clinically relevant patient groups with similar survival behavior.
DOI: 10.1002/sim.6729
PubMed: 26358826
Affiliations:
- Allemagne
- Bavière, District de Cologne, District de Haute-Bavière, Rhénanie-du-Nord-Westphalie
- Bonn, Munich
- Université Louis-et-Maximilien de Munich
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Le document en format XML
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into prognostic subgroups. A limitation of classical survival tree methodology is that most algorithms for tree construction are designed for continuous outcome variables. Hence, classical methods might not be appropriate if failure time data are measured on a discrete time scale (as is often the case in longitudinal studies where data are collected, e.g., quarterly or yearly). To address this issue, we develop a method for discrete survival tree construction. The proposed technique is based on the result that the likelihood of a discrete survival model is equivalent to the likelihood of a regression model for binary outcome data. Hence, we modify tree construction methods for binary outcomes such that they result in optimized partitions for the estimation of discrete hazard functions. By applying the proposed method to data from a randomized trial in patients with filarial lymphedema, we demonstrate how discrete survival trees can be used to identify clinically relevant patient groups with similar survival behavior.</div></front></TEI><affiliations><list><country><li>Allemagne</li></country><region><li>Bavière</li><li>District de Cologne</li><li>District de Haute-Bavière</li><li>Rhénanie-du-Nord-Westphalie</li></region><settlement><li>Bonn</li><li>Munich</li></settlement><orgName><li>Université Louis-et-Maximilien de Munich</li></orgName></list><tree><country name="Allemagne"><region name="Rhénanie-du-Nord-Westphalie"><name sortKey="Schmid, Matthias" sort="Schmid, Matthias" uniqKey="Schmid M" first="Matthias" last="Schmid">Matthias Schmid</name></region><name sortKey="Hoerauf, Achim" sort="Hoerauf, Achim" uniqKey="Hoerauf A" first="Achim" last="Hoerauf">Achim Hoerauf</name><name sortKey="Kuchenhoff, Helmut" sort="Kuchenhoff, Helmut" uniqKey="Kuchenhoff H" first="Helmut" last="Küchenhoff">Helmut Küchenhoff</name><name sortKey="Tutz, Gerhard" sort="Tutz, Gerhard" uniqKey="Tutz G" first="Gerhard" last="Tutz">Gerhard Tutz</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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