Analyzing Recurrent Marker Data in the Presence of a Terminal Event: Does the Terminal Event Form a Source of Informative Censoring?

• Activity Number: 44 - Joint Modeling of Longitudinal Data, Recurrent Events, and a Terminal Event
• Type: Invited
• Date/Time: Sunday, July 30, 2017 : 4:00 PM to 5:50 PM
• Sponsor: ENAR
• Author(s): Mei-Cheng Wang*
• Companies: Johns Hopkins University
• Keywords: Backward time model ; Competing risks ; Recurrent events ; Recurrent marker process ; Shared frailty

Abstract

Recurrent events and marker data arise in many follow-up and surveillance studies where the observation is ended by a terminal event or censoring. In the study the three different types of outcome (recurrent events, marker and time to terminal event) are possibly correlated. We consider modeling and estimation for such data by forward, backward and time-adjusted models: (i) Forward recurrent marker process starts at a time origin, 0, and moves forward along time t in the conventional way. (ii) Backward recurrent marker process considers the terminal event as the time origin and counts time backward. (iii) Time-adjusted models characterize the association of recurrent events, markers and time to terminal event by rescaling the time units with some additional adjustments. In this talk we argue that the presence of a terminal event may or may not generate a problem of informative censoring, depending on the goal of targeted research. Various data examples are used to illustrate the concepts and the proposed approaches.