In a longitudinal clinical study to compare two groups, the primary end point is often the time to a specific event (eg, disease progression, death). The hazard ratio estimate is routinely used to empirically quantify the between-group difference under the assumption that the ratio of the two hazard functions is approximately constant over time. When this assumption is plausible, such a ratio estimate may capture the relative difference between two survival curves. However, the clinical meaning of such a ratio estimate is difficult, if not impossible, to interpret when the underlying proportional hazards assumption is violated. In this talk, I summarize several critical concerns regarding this conventional practice and discuss an attractive alternative for quantifying the underlying differences between groups based on restricted mean survival time (RMST). I will discuss various issues in employing RMST in practical analysis including result interpretation, study design, power comparison, regression adjustment and extensions to competing risk and recurrent events settings. I will also discuss the pros and cons of the RMST-based analysis and demonstrate that it is competitive to its hazard ratio-based conventional counterparts in many applications.