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Vol. 13. Núm. 5.
Páginas 399-406 (septiembre - octubre 1999)
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Vol. 13. Núm. 5.
Páginas 399-406 (septiembre - octubre 1999)
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Riesgos competitivos de muerte
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J. Llorca*, M. Delgado-Rodríguez
Cátedra de Medicina Preventiva y Salud Pública, Facultad de Medicina, Universidad de Cantabria
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Resumen

La muerte de un individuo no es un hecho repetitivo, de suerte que si una causa de adelanta a otra para ocasionar la muerte del individuo, las tasas de mortalidad de la causa adelantada necesariamente disminuirán. Este fenómeno es conocido como riesgos competitivos de muerte y debe ser tenido en cuenta en cualquier análisis de mortalidad específica por causas. En este trabajo se formaliza el concepto de riesgos competitivos y se apuntan algunos datos sobre su historia; se presentan las principales herramientas para el análisis paramétrico de los riesgos competitivos, con especial atención a las funciones de Gompertz y Weibull. En cuanto a los modelos no paramétricos, se desarrolla especialmente el método de Chiang y se discute su aplicabilidad en causas de muerte dependientes e independientes. Finalmente, se enumeran otros instrumentos útiles especialmente en la epidemiología clínica, incluyendo la regresión de Cox, los métodos de Kaplan-Meier y de los rangos logarítmicos, y las interacciones entre el sesgo de riesgos competitivos y los sesgos de mala clasificación y selección.

Palabras clave:
Mortalidad
riesgos competitivos
métodos epidemiológicos
causas de muerte
Summary

The death of an individual is not a repetitive event, so if a cause of death overtakes another cause in producing death, mortality rates from the overtaken cause decrease. This phenomenon is known as competing risks of death and it must be taken into account in any cause-specific mortality analysis. In this work the competing risks concept is formalized and some historical data are described. The main parametric tools to analyze competing risks are displayed, with a special look at the Gompertz and Weibull functions. Regarding non-parametric models, the Chiang method is shown and its applicability on both dependent and independent causes of death is discussed. Finally, other tools specially useful in clinical epidemiology are enumerated, including Cox regresion, Kaplan-Meier and log-rank methods, as well as the interactions between competing risks and misclassification and selection biases.

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