Modeling Data With Semicompeting Risks: An ApModeling Data With Semicompeting Risks: An Aplication to Chronic Kidney Disease in Colombia

• Autores: Elizabeth González Patiño, Gisela Tunes, Maria Isabel Munera
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 42, Nº. 1, 2019, págs. 35-59
• Idioma: inglés
• DOI: 10.15446/rce.v42n1.68572
• Títulos paralelos:
  • Modelo para datos con riesgos semi competitivos: una aplicación a insuficiencia renal crónica en Colombia
• Enlaces
  • Texto completo
• Resumen
  • español

    Resumen En este trabajo se estudia la estructura de datos con riesgos semicompetitivos definida por Fine et al. (2001). En esta estructura existen dos eventos de interés; uno intermedio y otro terminal, este último puede censurar el evento intermedio, pero no viceversa. Dada la posible dependencia, entre los tiempos hasta la ocurrencia de tales eventos, dos tipos de enfoques son evaluados: uno, modelando la función de supervivencia bivariada a través de cópulas Arquimedianas y el otro por medio de un modelo con fragilidad compartida. El desempeño se observa a través de simulación. Ambos enfoques son aplicados a un conjunto de datos reales de pacientes con insuficiencia renal crónica, que pueden o no presentar una recaída de la enfermedad luego de ser tratados con diálisis.

  • English

    Abstract In this paper, the structure of semicompeting risks data, defined by Fine, Jiang & Chappell (2001), is studied. Two events are of interest: a nonterminal and a terminal event, the last one, can censor the non-terminal event, but not vice versa. Due to the possible dependence between the times until the occurrence of such events, two approaches are evaluated: modelling the bivariate survival function through Archimedean copulas and a shared frailty model. A simulation is conducted to examine its performance and both approaches are applied to a real data set of patients with chronic kidney disease (CKD).

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