Comparing predictions among competing risks models with time-dependent covariates

TY - JOUR

T1 - Comparing predictions among competing risks models with time-dependent covariates

AU - Cortese, G

AU - Gerds, TA

AU - Andersen, Per Kragh

PY - 2013/8/15

Y1 - 2013/8/15

N2 - Prediction of cumulative incidences is often a primary goal in clinical studies with several endpoints. We compare predictions among competing risks models with time-dependent covariates. For a series of landmark time points, we study the predictive accuracy of a multi-state regression model, where the time-dependent covariate represents an intermediate state, and two alternative landmark approaches. At each landmark time point, the prediction performance is measured as the t-year expected Brier score where pseudovalues are constructed in order to deal with right-censored event times. We apply the methods to data from a bone marrow transplant study where graft versus host disease is considered a time-dependent covariate for predicting relapse and death in remission.

AB - Prediction of cumulative incidences is often a primary goal in clinical studies with several endpoints. We compare predictions among competing risks models with time-dependent covariates. For a series of landmark time points, we study the predictive accuracy of a multi-state regression model, where the time-dependent covariate represents an intermediate state, and two alternative landmark approaches. At each landmark time point, the prediction performance is measured as the t-year expected Brier score where pseudovalues are constructed in order to deal with right-censored event times. We apply the methods to data from a bone marrow transplant study where graft versus host disease is considered a time-dependent covariate for predicting relapse and death in remission.

M3 - Tidsskriftartikel

SN - 0277-6715

VL - 32

SP - 3089

EP - 3101

JO - Statistics in Medicine

JF - Statistics in Medicine

IS - 18

ER -