Abstract
While pathology and laboratory medicine are the cornerstones of diagnostic medicine, they also play a crucial and central role in prognostication. One of the most important prognostic questions is survival. The aim of prognostication often is to determine the survival outlook for patients. For anatomic pathologists, the staging and grading of tumors is performed because of proven survival differences between different tumor grades and stages.
Survival data is different from other data types that we have discussed thus far; the survival data captures the time to failure event (often death or recurrence of the disease). The statistical tools that deal with survival data are also different and are derived from a specific probability distribution known as the survival function.
In this chapter, we will explain the concept of survival and introduce the statistical tools used in survival analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kleinbaum DG, Klein M. Survival analysis: a self-learning text. Springer Science & Business Media: USA; 2006.
Singh R, Mukhopadhyay K. Survival analysis in clinical trials: Basics and must know areas. Perspect Clin Res. 2011;2(4):145.
Lindsey JC, Ryan LM. Methods for interval-censored data. Stat Med. 1998;17(2):219–38.
Cox C, Chu H, Schneider MF, Muñoz A. Parametric survival analysis and taxonomy of hazard functions for the generalized gamma distribution. Stat Med. 2007;26(23):4352–74.
Rodrıguez G. Parametric survival models. Technical report. Princeton: Princeton University; 2010.
Kestenbaum B. Epidemiology and biostatistics: an introduction to clinical research. Springer Science & Business Media: USA; 2009.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Momeni, A., Pincus, M., Libien, J. (2018). Survival Analysis. In: Introduction to Statistical Methods in Pathology . Springer, Cham. https://doi.org/10.1007/978-3-319-60543-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-60543-2_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60542-5
Online ISBN: 978-3-319-60543-2
eBook Packages: MedicineMedicine (R0)