Download PDF
Methods Inf Med 2009; 48(02): 123-128
DOI: 10.3414/ME0563
Original Articles
Schattauer GmbH

periodR – an R Package to Calculate Long-term Cancer Survival Estimates Using Period Analysis

B. Holleczek
1   Saarland Cancer Registry, Saarbrücken, Germany
,
A. Gondos
2   German Cancer Research Center, Division for Clinical Epidemiology and Aging Research, Heidelberg, Germany
,
H. Brenner
2   German Cancer Research Center, Division for Clinical Epidemiology and Aging Research, Heidelberg, Germany
› Author Affiliations
Further Information

Publication History

received: 15 April 2008

accepted: 13 February 2008

Publication Date:
17 January 2018 (online)

    Permissions and Reprints

Summary

Objective: In this paper, a software package for the R language and system for statistical computing is presented for computation of long-term cancer survival estimates based on the period analysis approach. The period analysis approach provides up-to-date long-term survival estimates of concurrently diagnosed patients, enables early detection of recent changes in long-term prognosis of cancer patients and provides better survival predictions for recently and currently diagnosed patients than traditional cohort-based approaches.

Methods: Computation of absolute and relative survival estimates (both conditional follow-up year-specific and cumulative survival estimates) and their standard errors is based on standard actuarial methodology. For relative survival estimation the “Ederer II” and “Hakulinen” method were implemented.

Results: The package may be used for period analysis as well as traditional cohort-based survival estimation. The package further provides functions for the export of survival estimates for use with spreadsheet programs and for plotting survival curves. The application of period analysis is illustrated using stomach cancer data included in the package.

Conclusion: Application of period analysis has gradually increased in recent years but continues to be limited by availability of affordable and easy-to-use software tools. The presented R package aims at closing this gap and will further facilitate the use of period analysis for the research community working with population-based cancer registry data. The software is freely available for download on the website of the Saarland Cancer Registry at http://www.krebsregister.saarland.de improve/periodR_en.html.

Keywords

Neoplasms - survival - period analysis - software tool
 

  • References

  • 1 Berrino F, De Angelis R, Sant M, Rosso S, BielskaLasota M, Coebergh JW. et al. Survival for eight major cancers and all cancers combined for European adults diagnosed in 1995-99: results of the EUROCARE-4 study. Lancet Oncol 2007; 8: 773-783.
    CrossrefPubMedGoogle Scholar
  • 2 Verdecchia A, Francisci S, Brenner H, Gatta G, Micheli A, Mangone L. et al. Recent cancer survival in Europe: a 2000-02 period analysis of EUROCARE-4 data. Lancet Oncol 2007; 8: 784-796.
    CrossrefPubMedGoogle Scholar
  • 3 Coleman MP, Rachet B, Woods LM, Mitry E, Riga M, Cooper N. et al. Trends and socioeconomic inequalities in cancer survival in England and Wales up to 2001. Br J Cancer 2004; 90: 1367-1373.
    CrossrefPubMedGoogle Scholar
  • 4 Ellison LF, Gibbons L. Survival from cancer – up-to-date predictions using period analysis. Health Rep 2006; 17: 19-30.
    PubMedGoogle Scholar
  • 5 Ederer F, Axtell LM, Cutler SJ. The relative survival rate: a statistical methodology. Natl Cancer Inst Monogr 1961; 6: 101-121.
    PubMedGoogle Scholar
  • 6 Henson DE, Ries LA. The relative survival rate. Cancer 1995; 76: 1687-1688.
    CrossrefPubMedGoogle Scholar
  • 7 Parkin DM, Hakulinen T. Cancer registration: principles and methods. Analysis of survival. IARC Sci Publ; 1991. pp 159-176.
    Google Scholar
  • 8 Brenner H, Gefeller O. An alternative approach to monitoring cancer patient survival. Cancer 1996; 78: 2004-2010.
    CrossrefPubMedGoogle Scholar
  • 9 Brenner H, Gefeller O. Deriving more up-to-date estimates of long-term patient survival. J Clin Epidemiol 1997; 50: 211-216.
    CrossrefPubMedGoogle Scholar
  • 10 Brenner H, Hakulinen T. Up-to-date long-term survival curves of patients with cancer by period analysis. J Clin Oncol 2002; 20: 826-832.
    CrossrefPubMedGoogle Scholar
  • 11 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 2002; 31: 456-462.
    CrossrefPubMedGoogle Scholar
  • 12 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 2004; 40: 1361-1372.
    CrossrefPubMedGoogle Scholar
  • 13 Ellison LF. An empirical evaluation of period survival analysis using data from the Canadian Cancer Registry. Ann Epidemiol 2006; 16: 191-196.
    CrossrefPubMedGoogle Scholar
  • 14 Brenner H, Gefeller O, Stegmaier C, Ziegler H. More Up-To-Date Monitoring of Long-Term Survival Rates by Cancer Registries: An Empirical Example. Methods Inf Med 2001; 40: 248-252.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 15 Aareleid T, Brenner H. Trends in cancer patient survival in Estonia before and after the transition from a Soviet republic to an open-market economy. Int J Cancer 2002; 102: 45-50.
    CrossrefPubMedGoogle Scholar
  • 16 Brenner H. Long-term survival rates of cancer patients achieved by the end of the 20th century: a period analysis. Lancet 2002; 360: 1131-1135.
    CrossrefPubMedGoogle Scholar
  • 17 Talbäck M, Rosén M, Stenbeck M, Dickman PW. Cancer patient survival in Sweden at the beginning of the third millennium – predictions using period analysis. Cancer Causes Control 2004; 15: 967-976.
    CrossrefPubMedGoogle Scholar
  • 18 Brenner H, Stegmaier C, Ziegler H. Long-term survival of cancer patients in Germany achieved by the beginning of the third millenium. Ann Oncol 2005; 16: 981-986.
    CrossrefPubMedGoogle Scholar
  • 19 Houterman S, Janssen-Heijnen ML, van de Poll-Franse LV, Brenner H, Coebergh JW. Higher long-term cancer survival rates in southeastern Netherlands using up-to-date period analysis. Ann Oncol 2006; 17: 709-712.
    CrossrefPubMedGoogle Scholar
  • 20 Gondos A, Arndt V, Holleczek B, Stegmaier C, Ziegler H, Brenner H. Cancer survival in Germany and the United States at the beginning of the 21st century: an up-to-date comparison by period analysis. Int J Cancer 2007; 121: 395-400.
    CrossrefPubMedGoogle Scholar
  • 21 Brenner H, Gefeller O, Hakulinen T. Period analysis for ‘up-to-date’ cancer survival data: theory, empirical evaluation, computational realisation and applications. Eur J Cancer 2004; 40: 326-335.
    CrossrefPubMedGoogle Scholar
  • 22 Greenwood M. The natural duration of cancer. In: Reports on Public Health and Medical Subjects. London: Her Majesty´s Stationery Office; 1926. pp 1-26.
    Google Scholar
  • 23 R Development Core Team.. R: A Language and Environment for Statistical Computing. 2007. URL: http://www.r-project.org (26.08.2008 14:00 CET).
    PubMedGoogle Scholar
  • 24 Brenner H, Gefeller O, Hakulinen T. A computer program for period analysis of cancer patient survival. Eur J Cancer 2002; 38: 690-695.
    CrossrefPubMedGoogle Scholar
  • 25 Web site of IMBE Statistical Software Archive Network.. URL: http://www.imbe.med.uni-erlangen. de/issan/issan.htm (26.08.2008 14:00 CET).
    PubMed
  • 26 Web site of Saarland Cancer Registry.. URL: http://www.krebsregister.saarland.de improve/ periodR_en.html (09.09.2008 16:00 CET).
    PubMed
  • 27 Ederer F, Heise H. Instructions to IBM 650 programmers in processing survival computations. Methodological note No. 10, End Results Section. Bethesda (MD): National Cancer Institute; 1959
    Google Scholar
  • 28 Hakulinen T. Cancer survival corrected for heterogeneity in patient withdrawal. Biometrics 1982; 38: 933-942.
    CrossrefPubMedGoogle Scholar
  • 29 Brenner H, Arndt V, Gefeller O, Hakulinen T. An alternative approach to age adjustment of cancer survival rates. Eur J Cancer 2004; 40: 2317-2322.
    CrossrefPubMedGoogle Scholar
  • 30 Estève J, Benhamou E, Raymond L. Statistical methods in cancer research. Volume IV Descriptive epidemiology. IARC Sci Publ; 1994. pp 229-245.
    Google Scholar
  • 31 Brenner H, Stegmaier C, Ziegler H. Estimating completeness of cancer registration in Saarland/ Germany with capture-recapture methods. Eur J Cancer 1994; 30A: 1659-1663.
    PubMedGoogle Scholar
  • 32 Haberland J, Schön D, Bertz J, Görsch B. Vollzähligkeitsschätzungen von Krebsregisterdaten in Deutschland. Bundesgesundheitsbl-Gesundheitsforsch-Gesundheitsschutz 2003; 46: 770-774.
    PubMedGoogle Scholar
  • 33 Parkin DM, Whelan SL, Ferlay J, Teppo L, Thomas DB. editors. Cancer incidence in five continents. Volume VIII IARC Sci Publ.; 2002: 352-353.
    Google Scholar
  • 34 Federal Statistical Office Germany.. Period life tables for Germany 1871/1881 to 2004/2006. Wiesbaden: Federal Statistical Office; 2008. URL: https://wwwec.destatis.de/csp/shop/sfgbpm.html.cms.cBroker.cls?cmspath=struktur,vollanzeige.csp&ID=1021889 (26.08.2008 14:00 CET)
    Google Scholar
  • 35 Brenner H, Hakulinen T. Up-to-date and precise estimates of cancer patient survival: model-based period analysis. Am J Epidemiol 2006; 164: 689-696.
    CrossrefPubMedGoogle Scholar