Tackling dynamic prediction of death in patients with recurrent cardiovascular events

In the field of cardiovascular disease, recurrent events such as stroke or myocardial infarction (MI) are often encountered, leading to an increase in the risk of death. Accurately evaluating the prognosis of patients and dynamically predicting the risk of death by considering the historical recurre...

Full description

Saved in:
Bibliographic Details
Published inStatistics in medicine Vol. 42; no. 19; pp. 3487 - 3507
Main Authors Liang, Menglu, Li, Zheng, Li, Liang, Chinchilli, Vernon M., Zhang, Lijun, Wang, Ming
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 30.08.2023
Wiley Subscription Services, Inc
Subjects
Online AccessGet full text
ISSN0277-6715
1097-0258
1097-0258
DOI10.1002/sim.9815

Cover

Loading…
More Information
Summary:In the field of cardiovascular disease, recurrent events such as stroke or myocardial infarction (MI) are often encountered, leading to an increase in the risk of death. Accurately evaluating the prognosis of patients and dynamically predicting the risk of death by considering the historical recurrent events can improve medical decisions and lead to better health care outcomes. Recently proposed joint modeling approaches within the Bayesian framework have inspired the development of a dynamic prediction tool, which can be applied for subject‐level prediction of death with implementation in software packages. The prediction model incorporates subject heterogeneity with subject‐level random effects that account for unobserved time‐invariant factors and an extra copula function capturing the part caused by unmeasured time‐dependent factors. Thereafter, given the prespecified landmark time t′$$ {t}^{\prime } $$, the survival probability for a prediction horizon time of interest t$$ t $$ can be estimated for each individual. The prediction accuracy is assessed by time‐dependent receiving operating characteristic curve and the area under the curve and the Brier score with calibration plots is compared to traditional joint frailty models. Finally, the tool is applied to patients with multiple attacks of stroke or MI in the Cardiovascular Health study and the Atherosclerosis Risk in Communities study for illustration.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0277-6715
1097-0258
1097-0258
DOI:10.1002/sim.9815