Describing and analyzing complex disease history in retrospective studies.
Joint models
Landmark
Longitudinal measurements
Multi-state models
Observational studies
Outcomes
Time-dependent variables
Time-to-event analysis
Journal
Best practice & research. Clinical haematology
ISSN: 1532-1924
Titre abrégé: Best Pract Res Clin Haematol
Pays: Netherlands
ID NLM: 101120659
Informations de publication
Date de publication:
09 2023
09 2023
Historique:
received:
27
05
2023
accepted:
31
05
2023
medline:
25
8
2023
pubmed:
24
8
2023
entrez:
23
8
2023
Statut:
ppublish
Résumé
Blood-related diseases are complex diseases with diverse origins, treatments and prognosis. In haematology studies, investigators are interested in multiple outcomes and multiple prognostic variables that may change value over the course of follow-up. These time-dependent variables can be of different nature. Time-dependent events such as treatment with haematopoeitic stem cell transplant (HCT) and acute or chronic graft-versus-host disease (GVHD) typically interact with outcomes respectively after diagnosis or HCT. Longitudinal measurement such as immune response do influence survival after HCT. Effect of these time-dependent variables on outcomes can be investigated using different approaches, such as time-dependent Cox regression, landmark analysis, multi-state models or joint modelisation. In this paper we review basic principles of these different approaches using examples from haematological studies.
Identifiants
pubmed: 37612001
pii: S1521-6926(23)00044-0
doi: 10.1016/j.beha.2023.101483
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
101483Informations de copyright
Copyright © 2023 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest All authors declare that they have no conflicts of interest.