Landmark Prediction of Survival
Contributors: Cai, Tianxi; Wei, Lee-Jen; Harrington, David
Published: 2012
Language: eng
Description: The importance of developing personalized risk prediction estimates has become increasingly evident in recent years. In general, patient populations may be heterogenous and represent a mixture of different unknown subtypes of disease. When the source of this heterogeneity and resulting subtypes of disease are unknown, accurate prediction of survival may be difficult. However, in certain disease settings the onset time of an observable intermediate event may be highly associated with these unknown subtypes of disease and thus may be useful in predicting long term survival. Throughout this dissertation, we examine an approach to incorporate intermediate event information for the prediction of long term survival: the landmark model.
Notes: Keywords: landmark model, resampling, risk prediction, survival analysis.

Thesis Ph.D. Harvard University 2012