gms | German Medical Science

Kongress Medizin und Gesellschaft 2007

17. bis 21.09.2007, Augsburg

periodR – an R package to calculate long term cancer survival estimates using period analysis

Meeting Abstract

Search Medline for

  • Bernd Holleczek - Saarland Cancer Registry, Ministry for Justice, Health and Social Services, Saarbrücken
  • Adam Gondos - Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg
  • Hermann Brenner - Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg

Kongress Medizin und Gesellschaft 2007. Augsburg, 17.-21.09.2007. Düsseldorf: German Medical Science GMS Publishing House; 2007. Doc07gmds164

The electronic version of this article is the complete one and can be found online at:

Published: September 6, 2007

© 2007 Holleczek et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Introduction: Long-term survival estimates are key outcome measures reported by cancer registries. Period analysis provides up-to-date estimates of long term survival [1], [2]. It enables early detection of changes in survival trends and better predicts long term survival of recently

diagnosed patients compared to survival estimates derived by traditional cohort-based methods [3], [4], [5]. We present a software package for the R language and environment for statistical computing to perform period analysis.

Methods: The package implements proposed computer programs [6] and uses a life-table approach in which conditional survival probabilities for 1-year intervals following diagnosis are combined to derive cumulative absolute and relative survival proportions which exclusively reflect survival experience of patients within some most recent calendar period for which cancer incidence and mortality follow-up data is available.

Besides period analysis, the software can also be used to perform other analyses like cohort, complete or hybrid analysis [7]. Modified versions of the analysis procedures to compute age adjusted survival estimates are also included [8].

The software requires a dataset which must contain the following variables: month and year of diagnosis, month and year of end of follow-up, sex, age at diagnosis and vital status at end of follow-up. Conditional survival probabilities for the general population similar to the patient group with respect to sex and age are needed for the estimation of relative survival.

Application: R is available as free software and runs on many platforms [9]. In addition the package includes sample data, an example how to obtain conditional survival probabilities from publicly available life-tables as well as integrated documentation with examples of different analyses and graphical output.

Conclusions: The package is free software and is planned to be released shortly. The software will be available at the website of the Saarland Cancer Registry ( We hope that it will find a wide audience and enhance feasibility and application of period analysis of absolute and relative survival in the cancer registry setting.


Brenner H, Gefeller O. An alternative approach to monitoring cancer patient survival. Cancer. 1996;78(9):2004-10.
Brenner H, Gefeller O. Deriving more up-to-date estimates of long-term patient survival. J Clin Epidemiol. 1997;50(2):211-6.
Brenner H, Hakulinen T. Advanced detection of time trends in long-term cancer patient survival: experience from 50 years of cancer registration in Finland. Am J Epidemiol. 2002;156(6):566-77.
Brenner H, Hakulinen T. Up-to-date long-term survival curves of patients with cancer by period analysis. J Clin Oncol. 2002;20(3):826-32.
Brenner H, Soderman 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. 2002;31(2):456-62.
Brenner H, Gefeller O, Hakulinen T. A computer program for period analysis of cancer patient survival. Eur J Cancer. 2002;38(5):690-5.
Brenner H, Rachet B. Hybrid analysis for up-to-date long-term survival rates in cancer registries with delayed recording of incident cases. Eur J Cancer. 2004;40(16):2494-501.
Brenner H, Arndt V, Gefeller O, Hakulinen T. An alternative approach to age adjustment of cancer survival rates. Eur J Cancer. 2004;40(15):2317-22.
R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. 2006. External link