  Crossing survival curves complicate how we interpret results from a clinical
trial's primary endpoint. We find the function to determine a crossing point's
location depends exponentially on individual survival curves. This exponential
relationship between survival curves and the crossing point transforms small
survival curve errors into large crossing point errors. In most cases, crossing
points are sensitive to individual survival errors and may make accurately
locating a crossing point unsuccessful. We argue more complicated analyses for
mitigating crossing points should be reserved only after first exploring a
crossing point's variability, or hypothesis tests account for crossing point
variability.
