The difference between the pth quantiles of 2 survival functions can be used to compare patients' survival between 2 therapies. Setting p = 0.5 yields the median survival time difference. Varying p between 0 and 1 defines the quantile survival time difference curve which can be straightforwardly estimated by the horizontal differences between 2 Kaplan-Meier curves. The estimate's variability can be visualized by adding either a bundle of resampled bootstrap step functions or, alternatively, approximate bootstrap confidence bands. The user-friendly SAS software macro %kmdiff enables the straightforward application of this exploratory graphical approach. The macro is described, and its application is exemplified with breast cancer data. The advantages and limitations of the approach are discussed.
Keywords: Kaplan-Meier curves; SAS macro; bootstrap samples; confidence bands; exploratory data analysis.
© 2018 The Authors Journal of Evaluation in Clinical Practice Published by John Wiley & Sons Ltd.