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Gaceta Sanitaria

versão impressa ISSN 0213-9111

Resumo

NAVARRO, Albert; CASANOVAS, Georgina; ALVARADO, Sergio  e  MORINA, David. Analyzing recurrent events when the history of previous episodes is unknown or not taken into account: proceed with caution. Gac Sanit [online]. 2017, vol.31, n.3, pp.227-234. ISSN 0213-9111.  http://dx.doi.org/10.1016/j.gaceta.2016.09.004.

Objective:

Researchers in public health are often interested in examining the effect of several exposures on the incidence of a recurrent event. The aim of the present study is to assess how well the common-baseline hazard models perform to estimate the effect of multiple exposures on the hazard of presenting an episode of a recurrent event, in presence of event dependence and when the history of prior-episodes is unknown or is not taken into account.

Methods:

Through a comprehensive simulation study, using specific-baseline hazard models as the reference, we evaluate the performance of common-baseline hazard models by means of several criteria: bias, mean squared error, coverage, confidence intervals mean length and compliance with the assumption of proportional hazards.

Results:

Results indicate that the bias worsen as event dependence increases, leading to a considerable overestimation of the exposure effect; coverage levels and compliance with the proportional hazards assumption are low or extremely low, worsening with increasing event dependence, effects to be estimated, and sample sizes.

Conclusions:

Common-baseline hazard models cannot be recommended when we analyse recurrent events in the presence of event dependence. It is important to have access to the history of prior-episodes per subject, it can permit to obtain better estimations of the effects of the exposures.

Palavras-chave : Recurrence; Cohort studies; Risk assessment; Survival analysis; Bias.

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