  The purpose of this paper is to construct confidence intervals for the
regression coefficients in high-dimensional Cox proportional hazards regression
models where the number of covariates may be larger than the sample size. Our
debiased estimator construction is similar to those in Zhang and Zhang (2014)
and van de Geer et al. (2014), but the time-dependent covariates and censored
risk sets introduce considerable additional challenges. Our theoretical
results, which provide conditions under which our confidence intervals are
asymptotically valid, are supported by extensive numerical experiments.
