On longitudinal prediction with time-to-event outcome: Comparison of modeling options.

ABSTRACT: Long-term follow-up is common in many medical investigations where the interest lies in predicting patients' risks for a future adverse outcome using repeatedly measured predictors over time. A key quantity is the likelihood of developing an adverse outcome among individuals who survived up to time s given their covariate information up to time s. Simple, yet reliable, methodology for updating the predicted risk of disease progression using longitudinal markers remains elusive. Two main approaches have been considered in the literature. One approach, based on joint modeling (JM) of failure time and longitudinal covariate process (Tsiatis and Davidian, 2004), derives such longitudinal predictive probability from the joint probability of a longitudinal marker and an event at a given time. A

SUBMITTER: Maziarz M 

PROVIDER: S-EPMC5250577 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature