

Zürcher Kolloquium über anwendungsorientierte Statistik
Universität und ETH Zürich ----- Seminar für Statistik

Homepage:http://stat.ethz.ch/events/zukost

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jeweils donnerstags 16.15h bis ca. 17.30h
Zentrumsgebäude der*ETH - im  HG G 19.2*
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Nächste ZuKoSt-Veranstaltung:

*11. November 2010 mit Federico Ambrogi, Università degli Studi di Milano, Mailand*


/Titel:/
*Clinical useful measures for the study of competing risks in survival analysis
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/Abstract:/
In clinical studies where multiple events during patients follow-up are of interest,
the analysis of the crude cumulative incidence (CCI) is used to support clinical
decisions while the analysis of the cause specific hazard (CSH) provides information
on the disease dynamics for biological hypotheses generation and follow-up
planning. Treatment failure, as the event firstly occurring, may be due to causes having
different clinical implications in planning therapeutic strategies. The interest is
generally focused on some specific causes of failure. Since only one of them can be
actually observed on each patient, the competing risks methodology is appropriate.
In this context, the sub-distribution hazard model is applied to infer on the difference
among crude cumulative incidences. However, inference on sub-distribution
hazards are not directly interpretable from a clinical perspective. To assess treatment
or covariate effects, measures of clinical impact based on crude cumulative
incidence should be considered. In particular relative risks, excess of risks, relative
risk reduction and number of patients needed to be treated are known to be useful
to clinical practitioners. The aim of this work is to provide a straightforward approach
to obtain point and interval estimates of the above measures, by resorting
to the general framework of transformation models, through suitable link functions
in presence of competing risks. In particular, the proposal of Klein and Andersen,
based on pseudo-values, was considered as starting point. The baseline cumulative
risk was estimated resorting to regression spline functions on time. Time-varying
effects of covariates were tested through interaction with time functions. A literature
data set on a controlled clinical trial on prostate cancer, using causes of death as
end-points, was used for illustration. The critical aspects of competing risks analysis
will be illustrated using a study of the impact of micrometastases on patients
with unilateral breast cancer, classified as node negative at diagnosis, and who had
undergone surgery with axillary lymph node dissection. In this situation the endpoint
of interest is the subsequent development of distant metastases.

F. Ambrogi, Dipartimento di Medicina del Lavoro "Clinica del Lavoro Luigi Devoto"
Sezione di Statistica Medica e Biometria GA Maccacaro, Universit`a degli Studi di Milano,
Milan, Italy



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Eidgenoessische Technische Hochschule Zürich
Swiss Federal Institute of Technology Zurich
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