Journal Information
Vol. 18. Issue 5.
Pages 391-397 (September - October 2004)
Vol. 18. Issue 5.
Pages 391-397 (September - October 2004)
Open Access
Análisis de supervivencia en presencia de riesgos competitivos: estimadores de la probabilidad de suceso
Survival analysis with competing risks: estimating failure probability
Visits
7428
Javier Llorcaa,
Corresponding author
llorcaj@unican.es

Correspondencia: Medicina Preventiva y Salud Pública. Facultad de Medicina. Avda. Cardenal Herrera Oria, s/n. 39011 Santander. España.
, Miguel Delgado-Rodríguezb
a Medicina Preventiva y Salud Pública. Facultad de Medicina de la Universidad de Cantabria. Santander
b Medicina Preventiva y Salud Pública. Universidad de Jaén. España
This item has received

Under a Creative Commons license
Article information
Resumen
Objetivo

Mostrar el efecto de los riesgos competitivos de muerte en el análisis de supervivencia.

Métodos

Se presenta un ejemplo sobre la supervivencia libre de rechazo tras un trasplante cardíaco, en el que la muerte antes de desarrollar el rechazo actúa como riesgo competitivo. Mediante una simulación se comparan el estimador de Kaplan-Meier y el modelo de decrementos múltiples.

Resultados

El método de Kaplan-Meier sobrestima el riesgo de rechazo. A continuación, se expone la aplicación del modelo de decrementos múltiples para el análisis de acontecimientos secundarios (en el ejemplo, la muerte tras el rechazo). Finalmente, se discuten las asunciones propias del método de Kaplan-Meier y las razones por las que no puede ser aplicado en presencia de riesgos competitivos.

Conclusiones

El análisis de supervivencia debe ajustarse por los riesgos competitivos de muerte para evitar la sobrestimación del riesgo de fallo que se produce con el método de Kaplan-Meier.

Palabras clave:
Análisis de supervivencia
Kaplan-Meier
Modelo de decrementos múltiples
Riesgos competitivos
Trasplante cardíaco
Abstract
Objective

To show the impact of competing risks of death on survival analysis.

Method

We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model.

Results

The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks.

Conclusions

Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.

Key words:
Survival analysis
Kaplan-Meier
Multiple decrement model
Competing risks
Heart transplantation
Full text is only aviable in PDF
Bibliografía
[1.]
D.R. Cox.
Regression models and life-tables.
J Royal Stat Soc (B), 34 (1972), pp. 187-220
[2.]
T.A. Gooley, W. Leisenring, J. Crowley, B.E. Storer.
Estimation of failure probabilities in the presence of competing risks: new representations of old estimators.
Stat Med, 18 (1999), pp. 695-706
[3.]
W. Nelson.
Hazard plotting for incomplete failure data.
J Quality Technology, 1 (1969), pp. 27-52
[4.]
O.O. Aalen.
Nonparametric estimation of partial transition probabilities in multiple decrement models.
Annals Statistics, 6 (1978), pp. 534-545
[5.]
D.R. Hoover, Y. Peng, A.J. Saah, R.R. Detels, R.S. Day, J.P. Phair.
Using multiple decrement models to estimate risk and morbidity from specific AIDS illnesses.
[6.]
E.L. Kaplan, P. Meier.
Nonparametric estimation from incomplete observations.
J Am Stat Assoc, 53 (1958), pp. 457-481
[7.]
R.L. Prentice, J.D. Kalbfleisch, A.V. Peterson, N. Flournoy, V.T. Farewell, N.E. Breslow.
The analysis of failure times in the presence of competing risks.
Biometrics, 34 (1978), pp. 541-554
[8.]
J. Llorca, M. Delgado-Rodríguez.
Competing risks in absence of independence. Impact of AIDS on liver function failure mortality, and lung cancer on ischemic heart disease mortality.
J Clin Epidemiol, 53 (2000), pp. 1145-1149
[9.]
K.M. Leung, R.M. Elshoff, A.A. Afifi.
Censoring issues in survival analysis.
Annu Revue Public Health, 18 (1997), pp. 83-104
[10.]
Y. Yan, R.D. Moore, D.R. Hoover.
Competing risk adjustment reduces overstimation of opportunistic infection rates in AIDS.
J Clin Epidemiol, 53 (2000), pp. 817-822
[11.]
E.T. Lee, O.T. Go.
Survival analysis in Public Health research.
Annu Revue Public Health, 18 (1997), pp. 105-134
[12.]
Y. Yan, D.R. Hoever, R.D. Moore, X. Chengjie.
Multiariate estimation of cumulative incidence, prevalence, and morbidity time of a disease when death is likely.
J Clin Epidemiol, 56 (2003), pp. 546-552
[13.]
D.Y. Lin.
Non-parametric inference for cumulative incidence functions in competing risks studies.
Stat Med, 16 (1997), pp. 901-910
[14.]
C.L. Chiang.
Competing risks in mortality analysis.
Annu Rev Public Health, 12 (1991), pp. 281-307
[15.]
J. Llorca, M. Delgado-Rodríguez.
Competing risks analysis using Markov chains: impact of cerebro-vascular and ischaemic heart disease in cancer mortality.
Int J Epidemiol, 30 (2001), pp. 99-101
Copyright © 2004. Sociedad Española de Salud Pública y Administración Sanitaria
Download PDF
Idiomas
Gaceta Sanitaria
Article options
Tools
es en

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?