Integrating relative survival in multi-state models—a non-parametric approach

Manevski, Damjan (author), Putter, Hein (author), Pohar Perme, Maja (author), Bonneville, Edouard F (author), Schetelig, Johannes (author), Wreede, Liesbeth C. de (author)

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.

• Language: English
• Keywords: multi-state model, relative survival, mortality tables, competing risks, mstate
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: MF - Faculty of Medicine
• Publication status: Published
• Publication version: Version of Record
• Year: 2022
• Number of pages: Str. 997-1012
• Numbering: Vol. 31, iss. 6
• PID: 20.500.12556/RUL-144180
• UDC: 311
• ISSN on article: 0962-2802
• DOI: 10.1177/09622802221074156
• COBISS.SI-ID: 100836867
• Publication date in RUL: 02.02.2023

Record is a part of a journal

• Title: Statistical methods in medical research
• Shortened title: Stat. methods med. res.
• Publisher: SAGE
• ISSN: 0962-2802
• COBISS.SI-ID: 806420

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: model več stanj, relativno preživetje, tabele umrljivosti