Survivalanalysen mit Berücksichtigung der zeitlichen Kovariablenentwicklung in klinischen Studien

Data from the Stanford Heart Transplantation Study and our own
study on brain tumor include time-dependent covariates like
transplantation, which may switch only once, and others changing
their value several times during follow-up. But classical analyses
never used this additional information. In a comparative study we
applied the time-dependent Cox model, pooled Cox regression and the
linear counting process by Aalen to these data sets. All methods do
show similar results when they are carried out in their 'fixed'
version, i.e. using baseline information only, or when covariates
are being treated as time-dependent. But the estimated effects do
differ remarkably between fixed and time-dependent approaches, thus
leading to different interpretations of risks.