20.500.12556/RUL-144180 Integrating relative survival in multi-state models—a non-parametric approach Multi-state models provide an extension of the usual survival/event-history analysis setting. In the medical domain, multi-state models give the possibility of further investigating intermediate events such as relapse and remission. In this work, a further extension is proposed using relative survival, where mortality due to population causes (i.e. non-disease-related mortality) is evaluated. The objective is to split all mortality in disease and non-disease-related mortality, with and without intermediate events, in datasets where cause of death is not recorded or is uncertain. To this end, population mortality tables are integrated into the estimation process, while using the basic relative survival idea that the overall mortality hazard can be written as a sum of a population and an excess part. Hence, we propose an upgraded non-parametric approach to estimation, where population mortality is taken into account. Precise definitions and suitable estimators are given for both the transition hazards and probabilities. Variance estimating techniques and confidence intervals are introduced and the behaviour of the new method is investigated through simulations. The newly developed methodology is illustrated by the analysis of a cohort of patients followed after an allogeneic hematopoietic stem cell transplantation. The work has been implemented in the R package mstate. multi-state model relative survival mortality tables competing risks mstate model več stanj relativno preživetje tabele umrljivosti true false true Angleški jezik Slovenski jezik Članek v reviji 2023-02-02 16:32:44 2023-02-02 16:32:51 2023-02-04 03:20:34 0000-00-00 00:00:00 2022 0 0 Str. 997-1012 iss. 6 Vol. 31 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 311 0962-2802 10.1177/09622802221074156 100836867 09622802221074156.pdf 09622802221074156.pdf 1 F7F7575AD1B69F9285317A63C8BBD4FC 84a956f53111da634d71fcb2010520d7e535f391cdc047294b7e8f8b1d9f0cba f4afed1d-a30e-11ed-9c94-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=166373 https://journals.sagepub.com/doi/10.1177/09622802221074156 0 d3d832bd-a30e-11ed-9c94-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=166372 Medicinska fakulteta 0 0 0