Abstract
Dealing with cancer is one of the big challenges of the German healthcare system. Originally, efforts regarding the analysis of cancer data focused on the detection of spatial clusters of cancer incidences. Nowadays, the emphasis also incorporates complex health services research and quality assurance. In 2013, a law was enacted in Germany forcing the spatially all-encompassing expansion of clinical cancer registries, each of them covering a commuting area of about 1 to 2 million inhabitants [1]. Guidelines for a unified evaluation of data are currently in development, and it is very probable that these guidelines will demand the execution of comparative survival analyses.
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 (ECRs) in several German federal states, opens up data analysis for a wider audience. We show that by applying the principles of integration and abstraction, CARESS copes with the challenges posed by the diversity of the cancer registry landscape in Germany. Survival estimates are calculated by the software package periodR seamlessly integrated in CARESS. We also discuss several performance optimizations for survival estimation, and illustrate the feasibility of our approach by an experiment on cancer survival estimation performance and by an example on the application of cancer survival analysis with CARESS.
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References
Gesetz zur Weiterentwicklung der Krebsfrüherkennung und zur Qualitätssicherung durch klinische Krebsregister (Krebsfrüherkennungs- und -registergesetz – KFRG) of 2013, BGBl. I, pp. 617–623 (April 3, 2013) (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., editors. Krebs in Deutschland 2007/2008, Berlin (2012) (German)
Gesetz u ̈ber Krebsregister (Krebsregistergesetz – KRG) of 1994, BGBl. I pp. 3351–3355 (November 4, 1994) (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)
Altman, D.G., Bland, J.M.: Time to event (survival) data. British Medical Journal 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., Rosén, 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)
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, August 11-13. IEEE, Olympia (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 (2010)
Georges, A., Buytaert, D., Eeckhout, L.: Statistically Rigorous Java Performance Evaluation. ACM SIGPLAN Notices - Proceedings of the 2007 OOPSLA Conference 42(10), 57–76 (2007)
Registerstelle des Epidemiologischen Krebsregisters Niedersachsen, editor. Krebs in Niedersachsen, Oldenburg, 117 p. (2010) (German)
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Korfkamp, D., Gudenkauf, S., Rohde, M., Sirri, E., Kieschke, J., Appelrath, H.J. (2014). Opening up Data Analysis for Medical Health Services: Cancer Survival Analysis with CARESS. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2014. Lecture Notes in Computer Science, vol 8646. Springer, Cham. https://doi.org/10.1007/978-3-319-10160-6_34
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DOI: https://doi.org/10.1007/978-3-319-10160-6_34
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10159-0
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