Abstract
Dealing with cancer is one of the big challenges of the German healthcare system. Todays efforts regarding the analysis of cancer data incorporate detection of spatial clusters as well as complex health services research and quality assurance. Recently, guidelines for a unified evaluation of German cancer data were developed which demand the execution of comparative survival analyses [1].
In this paper, we present how the CARLOS Epidemiological and Statistical Data Exploration System (CARESS), a sophisticated data warehouse system that is used by epidemiological cancer registries (ECR) in several German federal states, opens up survival analysis for a wider audience. We also discuss several performance optimizations for survival estimation, and illustrate the feasibility of our approach. Moreover we present the CARLOS Record Linkage System CARELIS, a companion tool to CARESS that enables matching new data against already existent disease reports in the ECR under consideration of potential cross references.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
See http://www.onkozert.de/ [last visited 2014/03/27].
- 2.
A relational database request would result in only a few hundred rows, when, for example, a rare diagnosis or a specific regional area is analyzed.
- 3.
Exporting a survival analysis to Excel is performed by the ExcelExportService, which uses the CachedSurvivalAnalysisDataService via theResultService.
References
Kriterien zur Frderung klinischer Krebsregister des GKV-Spitzenverbandes of 2013, GKV-Spitzenverband, 20 December 2012. German
Nennecke, A., Brenner, H., Eberle, A., Geiss, K., Holleczek, B., Kieschke, J., Kraywinkel, K.: Cancer survival analysis in Germany – heading towards representative and comparable findings. Gesundheitswesen 72, 692–699 (2010). German
Robert Koch-Institut und die Gesellschaft der epidemiologischen Krebsregister in Deutschland e.V. (eds.) Krebs in Deutschland 2007/2008. Berlin (2012). German
Gesetz über Krebsregister (Krebsregistergesetz – KRG) of 1994, BGBl. I pp. 3351–3355, 4 November 1994. German
Hentschel, S., Katalinic, A. (eds.): Das Manual der epidemiologischen Krebsregistrierung. Zuckerschwerdt Verlag, München (2008). German
Gesetz zur Weiterentwicklung der Krebsfrüherkennung und zur Qualitätssicherung durch klinische Krebsregister (Krebsfrüherkennungs- und -registergesetz KFRG) of 2013, BGBl. I pp. 617–623, 3 April 2013. German
Bauer, A., Günzel, H.: Data Warehouse Systeme, 3rd edn. dpunkt.verlag, Heidelberg (2009). German
Kleinbaum, D.G., Klein, M.: Survival Analysis, 3rd edn. Springer, New York (2012)
Wietek, F.: Spatial statistics for cancer epidemiology - the Cancer Registry’s Epidemiological and Statistical Data Exploration System (CARESS). In: Fehr, R., Berger, J., Ranft, U. (eds.) Environmental Health Surveillance. Fortschritte in der Umweltmedizin, pp. 157–171. ecomed-Verlag, Landsberg (1999)
Kamp, V., Sitzmann, L., Wietek, F: A spatial data cube concept to support data analysis in environmental epidemiology. In: Proceedings of the 9th International Conference on Scientific and Statistical Database Management, Olympia, WA, 11–13 August 1997. IEEE (1997)
Brumfield, B., Cox, G., Hill, D., Noyes, B., Puleo, M., Shifflet, K.: Developer’s Guide to Microsoft Prism 4: Building Modulare MVVM Applications with Windows Presentation Foundation and Microsoft Silverlight. Microsoft Press, Redmond (2010)
Altman, D.G., Bland, J.M.: Time to event (survival) data. Br. Med. J. 317, 468–469 (1998)
Holleczek, B., Gondos, A., Brenner, H.: periodR - an R package to calculate long-term cancer survival estimates using period analysis. Methods Inf. Med. 48, 123–128 (2009)
Brenner, H., Söderman, B., Hakulinen, T.: Use of period analysis for providing more up-to-date estimates of long-term survival rates: empirical evaluation among 370 000 cancer patients in Finland. Int. J. Epidemiol. 31, 456–462 (2002)
Talbäck, M., Stenbeck, M., Rosn, M.: Up-to-date long-term survival of cancer patients: an evaluation of period analysis on Swedish Cancer Registry data. Eur. J. Cancer 40, 1361–1372 (2004)
Ellison, L.F.: An empirical evaluation of period survival analysis using data from the Canadian Cancer Registry. Ann. Epidemiol. 16, 191–196 (2006)
Georges, A., Buytaert, D., Eeckhout, L.: Statistically rigorous java performance evaluation. In: Proceedings of the 22nd Annual ACM SIGPLAN Conference on Object-Oriented Programming Systems and Applications, vol. 42(10), p. 5776 (2007)
Registerstelle des Epidemiologischen Krebsregisters Niedersachsen (ed.) Krebs in Niedersachsen 2010. Oldenburg, p. 117 (2012). German
Gesetz über das Epidemiologische Krebsregister Niedersachsen (GEKN) of 2012, Nds. GVBl. Nr. 31/2012, 13 December 2012. German
Lai, X., Massey, J.L.: A proposal for a new block encryption standard. In: Damgård, I.B. (ed.) EUROCRYPT 1990. LNCS, vol. 473, pp. 389–404. Springer, Heidelberg (1991)
Brenner, H., Schmidtmann, I., Stegmaier, C.: Effects of record linkage errors on registry-based follow-up studies. Stat. Med. 16, 2633–2643 (1997)
Hinrichs, H.: Abschlußbericht des Projektes “Bundesweite Einfhrung eines einheitlichen Record Linkage Verfahrens in den Krebsregistern der Bundeslnder nach dem KRG” (1999). http://www.krebsregister-niedersachsen.de/dateien/veroeffentlichungen/Reports/UNICON/unicon.pdf. German
Felligi, I.P., Sunter, A.B.: A theory for record linkage. Am. Stat. Assoc. J. 64, 1183–1220 (1969)
Bachteler, T., Reicher, J.: TDGen: A Test Data Generator for Evaluating Record Linkage Methods. German Record Linkage Center, WP-GRLC-2012-01 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Korfkamp, D. et al. (2016). 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. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49784-5_4
Download citation
DOI: https://doi.org/10.1007/978-3-662-49784-5_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-49783-8
Online ISBN: 978-3-662-49784-5
eBook Packages: Computer ScienceComputer Science (R0)