Tree-structured analysis of survival data—search for latent diagnostic factors in a tumour study
✍ Scribed by Brambilla, Carla ;Rossi, Carla ;Schinaia, Giuseppe
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 115 KB
- Volume
- 13
- Category
- Article
- ISSN
- 8755-0024
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✦ Synopsis
This paper presents a possible solution to the problem of identification of factors influencing long-term survival patients, using regression trees. The separation of the two classes of long-term survivors (cured patients) and of failed-to-cure patients is generalized to l* classes of survivors and is carried out via a latent variable, whose determinations are provided by the regression-tree classification. Two sets of factors are thus identified within the set of covariates: the factors influencing the prognosis and those influencing the survival classification (diagnostic factors). The relationship between the two sets is then explored, both theoretically and using an application to a data set of multiple myeloma patients.