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A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions. - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

* Corresponding author 1 MSDMA CEDRIC - Centre d-Etude et De Recherche en Informatique et Communications 2 Freiburg Center for Data Analysis and Modeling 3 Service d-hématologie clinique et de thérapie cellulaire CHU Saint-Antoine 4 Department Biostatistics University of North Carolina

Abstract : Competing risks endpoints are frequently encountered in hematopoietic stem cell transplantation where patients are exposed to relapse and treatment-related mortality. Both cause-specific hazards and direct models for the cumulative incidence functions have been used for analyzing such competing risks endpoints. For both approaches, the popular models are of a proportional hazards type. Such models have been used for studying prognostic factors in acute and chronic leukemias. We argue that a complete understanding of the event dynamics requires that both hazards and cumulative incidence be analyzed side by side, and that this is generally the most rigorous scientific approach to analyzing competing risks data. That is, understanding the effects of covariates on cause-specific hazards and cumulative incidence functions go hand in hand. A case study illustrates our proposal.

Keywords : Competing risks Cumulative incidence Endpoints Bone marrow transplant Proportional hazards Survival analysis





Autor: Aurelien Latouche - Arthur Allignol - Jan Beyersmann - Myriam Labopin - Jason P Fine -

Fuente: https://hal.archives-ouvertes.fr/



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