Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/11862
Título: | Flexible hazard ratio curves for continuous predictors in multi-state models: application to breast cancer data |
Autor(es): | Machado, Luís Meira Kneib, Thomas Gude, Francisco Cardarso-Suarez, Carmen |
Palavras-chave: | Cox model Hazard Ratio Multi-state model Penalized splines |
Data: | Out-2010 |
Editora: | SAGE Publications |
Revista: | Statistical Modelling |
Citação: | Cadarso-Suárez, C., Meira-Machado, L., Kneib, T., & Gude, F. (2010, September 28). Flexible hazard ratio curves for continuous predictors in multi-state models. Statistical Modelling. SAGE Publications. http://doi.org/10.1177/1471082x0801000303 |
Resumo(s): | Multi-state models (MSMs) are very useful for describing complicated event history data. These models may be considered a generalization of survival analysis where survival is the ultimate outcome of interest but where intermediate (transient) states are identified. One major goal in clinical applications of multi-state models is to study the relationship between the different covariates and disease evolution. Usually, MSMs are assumed to be parametric, and the effects of continuous predictors on log-hazards are modeled linearly. In practice, however, the effect of a given continuous predictor can be unknown, and its form may be different in all permitted transitions. In this paper, we propose a P-spline approach that allows for non-linear relationships between continuous predictors and survival in the multi-state framework. To better understand the effects that each continuous covariate has on the outcome at each transition, results are expressed in terms of hazard ratio curves, taking a specific covariate value as reference. Confidence bands for these curves are also derived. The proposed methodology was applied to a database on breast cancer, using a progressive three-state model, and the results were compared against those obtained through the traditional Cox regression model. This application revealed hitherto unreported effects: whereas DNA index is only an important nonlinear predictor of recurrence, the percentage of cells in phase S is a significant predictor of both recurrence and mortality. All analyses were performed using software written by the authors. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/11862 |
DOI: | 10.1177/1471082X0801000303 |
ISSN: | 1471-082X |
Versão da editora: | https://journals.sagepub.com/doi/10.1177/1471082X0801000303 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
STATMOD_2010.pdf Acesso restrito! | Documento com abstract e referências | 51,7 kB | Adobe PDF | Ver/Abrir |
SM_2010.pdf Acesso restrito! | Paper completo | 592,78 kB | Adobe PDF | Ver/Abrir |