Conditional MLE for the proportional hazards model with left-truncated and interval-censored data

We consider conditional maximum likelihood estimator (cMLE) for the proportional hazards model with left-truncated and interval-censored data. We show that when the covariates are discrete the cMLE is the MLE, and under some regularity conditions the cMLE for the regression parameter is asymptotically normal and efficient.