Article
Disease-Free and Relapse-Free Cancer Survival Analysis with CARESS
Search Medline for
Authors
Published: | August 29, 2017 |
---|
Outline
Text
Survival analysis is used in cancer research to estimate the lifetime of cancer patients. Besides the duration until death, it is interesting to investigate additional events, for example, the reappearance of cancer after successful treatment. To do so, cancer registries use a variety of tools to carry out survival analysis. These, however, typically require the user manually providing a prepared set of cancer data. In the CARESS data warehouse system, data preparation is automated using OLAP cubes, and data analysis is supported by different R packages that users can conveniently use via an elaborate user interface. To date, survival analysis in CARESS was limited to the death of a patient. In this paper, we describe how we extended the data warehouse of the CARESS system at the example of the Epidemiological Cancer Registry of Lower Saxony (EKN) with additional OLAP cubes in order to support disease-free (DFS) and relapse-free survival (RFS). While these methods are unlikely to be used in epidemiological cancer research, they are important for the analysis of clinical cancer data.
Die Autoren geben an, dass kein Interessenkonflikt besteht.
Die Autoren geben an, dass kein Ethikvotum erforderlich ist.
References
- 1.
- Eberle-Bartholdt A. Möglichkeiten und Grenzen der Datenauswertung in epidemiologischen Krebsregistern, Dissertation. 2016. Available online: https://elib.suub.uni-bremen.de/edocs/00105438-1.pdf
- 2.
- GEKID Empfehlungen zur Analyse von Überlebensraten. 2015. Available online: http://www.gekid.de/Doc/Empfehlungen_zur_Analyse_von_Ueberlebensraten.pdf
- 3.
- Korfkamp D, et al. Opening Up Data Analysis for Medical Health Services: Data Integration and Analysis in Cancer Registries with CARESS. In: Hameurlain A, Küng J, Wagner R, Bellatreche L, Mohania M, eds. Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVI. Lecture Notes in Computer Science. Vol 9670. Berlin, Heidelberg: Springer; 2016. pp 89-107.
- 4.
- Nennecke A, Brenner H, Eberle A, et al. Überlebenschancen von Krebspatienten in Deutschland - auf dem Weg zu repräsentativen, vergleichbaren Aussagen – Cancer Survival Analysis in Germany - Heading Towards Representative and Comparable Findings. Das Gesundheitswesen. 2010;72:692-699.
- 5.
- Therneau TM. A Package for Survival Analysis in S. 2015. Available online: https://CRAN.R-project.org/package=survival
- 6.
- Holleczek B, Gondos A, Brenner H. periodR – an R Package to Calculate Long-term Cancer Survival Estimates Using Period Analysis. Methods Inf Med. 2009;48:123-128.