Appraisal of Several Methods to Model Time to Multiple Events per Subject: Modelling Time to Hospitalizations and Death

• JAVIER CASTAÑEDA ^[1] ; BART GERRITSE ^[1]
  1. [1] Medtronic Bakken Research Center Cardiac Rhythm Disease Management Clinical Outcomes, Research and Biometry
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 33, Nº. 1, 2010, págs. 43-61
• Idioma: inglés
• Títulos paralelos:
  • Revisión de varios métodos para modelar tiempo a múltiples eventos por sujeto: modelamiento de tiempo a hospitalizaciones y muerte
• Enlaces
  • Texto completo
• Resumen
  • español

    Algunos ensayos clínicos para estudiar el efecto de nuevos tratamientos en pacientes con insuficiencia cardiaca (IC) se basan en la evaluación de hospitalizaciones relacionadas con IC y muerte. Frecuentemente el análisis se enfoca en el tiempo a la primera ocurrencia de alguno de estos dos desenlaces. Este tipo de análisis ignora importantes eventos como nuevas hospitalizaciones relacionadas con IC, que permiten una mejor descripción y compresión del proceso de recuperación de estos pacientes. En este trabajo se describen y exploran varias estrategias para el análisis de tiempo a repetidas hospitalizaciones relacionadas con IC y tiempo a la muerte. Se estudian modelos marginales para incorporar la correlación intra-sujeto y riesgos competitivos propios de este tipo de ensayos clínicos. Finalmente, se recomienda un modelo multi-estado como una estrategia sencilla y flexible que incorpora elementos importantes en el análisis de hospitalizaciones relacionadas con IC y muerte, y a la vez extiende características relevantes de los modelos de Andersen & Gill (1982), Wei et al. (1989) and Prentice et al. (1981).

  • English

    During the disease-recovery process of many diseases, such as in Heart Failure (HF), often more than one type of event plays a role. Some clinical trials use the combined endpoint of death and a secondary event; for instance, HF-related hospitalizations. This is often analyzed with time-to-first-event survival analysis which ignores possible subsequent events, such as several HF-related hospitalizations. Accounting for multiple events provides more detailed information on the disease-control process, and allows a more precise understanding of the prognosis of patients. In this paper we explore and illustrate several modelling strategies to study time to repeated events of disease-related hospitalizations and death per subject. Marginal models are revised in order to account for intra-subject correlation and competing risks. Finally, we recommend a Multi-state model which allows a flexible modelling strategy that incorporates important features in the analysis of HF-related hospitalizations and death, and at the same time extends relevant characteristics of the Andersen & Gill (1982), Wei et al. (1989) and Prentice et al. (1981) models.

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