Multistate Analysis of Interval-Censored Longitudinal Data for Examining Transitions in Performance Status Among Cancer Outpatients

• Activity Number: 84
• Type: Contributed
• Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Rinku Sutradhar*+
• Companies: Institute for Clinical Evaluative Sciences
• Keywords: interval-censoring ; Markov process ; multistate model ; palliative performance scale ; transitional probability matrix

Abstract

In observational studies on cancer patients, progression of performance status over time can be described by using a multistate model in which state-to-state transitions represent changes in a patient's health condition. Although a patient experiences transitions in continuous time, assessments on the patient are often made at irregularly spaced time points. This paper formulates a Markov multistate model for examining longitudinal data on performance status collected under intermittent observation. The model is extended to estimate the predicted probability of reaching the absorbing state, death, over various time intervals. We also illustrate what happens to the estimated transition intensities if the true observational scheme is overlooked. Methods for multistate analyses should be used by epidemiologists, as it proves particularly useful for examining the complexities of disease processes.