Dynamic prediction of repeated events data based on landmarking model: application to colorectal liver metastases data.

ABSTRACT:

Background

In some clinical situations, patients experience repeated events of the same type. Among these, cancer recurrences can result in terminal events such as death. Therefore, here we dynamically predicted the risks of repeated and terminal events given longitudinal histories observed before prediction time using dynamic pseudo-observations (DPOs) in a landmarking model.

Methods

The proposed DPOs were calculated using Aalen-Johansen estimator for the event processes described in the multi-state model. Furthermore, in the absence of a terminal event, a more convenient approach without matrix operation was described using the ordering of repeated events. Finally, generalized estimating equations were used to calculate probabilities of repeated and terminal events, which

SUBMITTER: Yokota I 

PROVIDER: S-EPMC6376774 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature