Survival Analyses without Risk Stratification Can Induce Non-Proportional Hazard Conditions

Music City Center 

In randomized clinical trials, survival analyses without risk stratification, or with stratification based on pre-selected factors revealed at the end of the trial to be at most weakly associated with event risk, are surprisingly common. We show that such analyses can unwittingly induce non-proportional hazard conditions and potentially deliver hazard ratio estimates that dilute the evidence of benefit for the test relative to the control treatment. To safeguard against this, we draw attention to 5-STAR, a novel methodology in which a treatment-blinded algorithm is applied to the survival times from the trial to partition patients into risk strata based on covariates observed to be jointly prognostic for event risk. A treatment comparison is subsequently done within each identified risk stratum and stratum-level results are averaged for overall inference. We illustrate the utility of 5-STAR using a reanalysis of data for the primary and key secondary endpoints from three published cardiovascular outcomes trials.

5-STAR

algorithm

average hazard ratio

conditional inference tree

elastic net

risk stratification