Cargando…

Visualizing the quantile survival time difference curve

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 straightforwardl...

Descripción completa

Detalles Bibliográficos
Autores principales: Heinzl, Harald, Mittlboeck, Martina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6099283/
https://www.ncbi.nlm.nih.gov/pubmed/29790230
http://dx.doi.org/10.1111/jep.12948
Descripción
Sumario: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.