open access

Vol 7, No 2 (2011)
Review paper
Published online: 2011-06-22
Get Citation

Methods of survival analysis applied in oncology — assumptions, methods and common pitfalls

Wojciech Fendler, Justyna Chałubińska, Wojciech Młynarski
Onkol. Prak. Klin 2011;7(2):89-101.

open access

Vol 7, No 2 (2011)
REVIEW ARTICLES
Published online: 2011-06-22

Abstract

Survival analysis is the analytical foundation of studies on cancer-related mortality or disease progression. Analytical techniques used for this purpose share one common trait — the uncertainty of the event’s occurrence in individuals, whose observation time has been censored due to study termination, withdrawal due to events other than prespecified endpoints or loss to follow-up. The main advantage of such analytical methods is the possibility to estimate individual hazard (risk of event occurrence) at any given timepoint of observation and consequently of expected survival time depending on a plethora of clinical variables and treatment modalities. Due to a huge and ever-expanding amount of oncologic data using survival analysis as a primary measure of outcome, the ability to interpret such results and to know the assumptions and workings of particular methods is slowly becoming ubiquitous. Analytical methods deployed on survival data feature univariate nonparametric ones (the log-rank test), multivariate modeling techniques (assuming proportional or additive risk), automated neural networks and classification-regression trees. The purpose of this review was to present and discuss in detail the available range of analytic and exploratory methods used in biostatistics and oncology. The spectrum of common analytical and interpretative problems, methods of designing and planning clinical trials and verifying the veracity of published data may provide a valuable addition in the process of clinical application of evidence based oncology.
Onkol. Prak. Klin. 2011; 7, 2: 89–101

Abstract

Survival analysis is the analytical foundation of studies on cancer-related mortality or disease progression. Analytical techniques used for this purpose share one common trait — the uncertainty of the event’s occurrence in individuals, whose observation time has been censored due to study termination, withdrawal due to events other than prespecified endpoints or loss to follow-up. The main advantage of such analytical methods is the possibility to estimate individual hazard (risk of event occurrence) at any given timepoint of observation and consequently of expected survival time depending on a plethora of clinical variables and treatment modalities. Due to a huge and ever-expanding amount of oncologic data using survival analysis as a primary measure of outcome, the ability to interpret such results and to know the assumptions and workings of particular methods is slowly becoming ubiquitous. Analytical methods deployed on survival data feature univariate nonparametric ones (the log-rank test), multivariate modeling techniques (assuming proportional or additive risk), automated neural networks and classification-regression trees. The purpose of this review was to present and discuss in detail the available range of analytic and exploratory methods used in biostatistics and oncology. The spectrum of common analytical and interpretative problems, methods of designing and planning clinical trials and verifying the veracity of published data may provide a valuable addition in the process of clinical application of evidence based oncology.
Onkol. Prak. Klin. 2011; 7, 2: 89–101
Get Citation

Keywords

survival analysis; hazard; prognostic models

About this article
Title

Methods of survival analysis applied in oncology — assumptions, methods and common pitfalls

Journal

Oncology in Clinical Practice

Issue

Vol 7, No 2 (2011)

Article type

Review paper

Pages

89-101

Published online

2011-06-22

Bibliographic record

Onkol. Prak. Klin 2011;7(2):89-101.

Keywords

survival analysis
hazard
prognostic models

Authors

Wojciech Fendler
Justyna Chałubińska
Wojciech Młynarski

Important: This website uses cookies. More >>

The cookies allow us to identify your computer and find out details about your last visit. They remembering whether you've visited the site before, so that you remain logged in - or to help us work out how many new website visitors we get each month. Most internet browsers accept cookies automatically, but you can change the settings of your browser to erase cookies or prevent automatic acceptance if you prefer.

Wydawcą serwisu jest  "Via Medica sp. z o.o." sp.k., ul. Świętokrzyska 73, 80–180 Gdańsk

tel.:+48 58 320 94 94, faks:+48 58 320 94 60, e-mail:  viamedica@viamedica.pl